PBEE Faculty

The three types of GDBBS membership are Full Graduate Faculty, Affiliate Graduate Faculty, and Adjunct Faculty. The definition of membership rights and responsibilities are as follows:

Full graduate faculty members have full rights and privileges, including the right to act as Dissertation Advisors, to serve on any GDBBS Committee, or in an administrative position. Full members must be faculty at Emory in good standing. They should be engaged in research, research funding, and peer reviewed publication in the biological and biomedicals sciences. To assure a stable training environment, full members must have independent funding, or likelihood of obtaining funding in the near future, and sufficient research space.

Full members are reported as doctoral faculty for the purpose of institutional research and evaluation that is both internal and external to the University.

Affiliate graduate faculty members should have at least a 50% appointment at Emory. Affiliate members have the privileges of Graduate Faculty except: (1) they may only serve as co-advisors; (2) they are not eligible to serve in LGS governance bodies; and (3) they are not eligible to serve on LGS competitive fellowship/funding committees. Their level of participation in curricular design and governance of the graduate program is subject to the program’s discretion. Generally, this membership is for faculty who contribute to the mission of the graduate program but are not in a position to directly serve as an advisor for new students in their research group, or those who have been judged to be non-participatory during the annual program review of participation.

Affiliate members are not reported as Graduate Faculty for the purpose of institutional research and evaluation that is both internal and external to the University.

Adjunct faculty members are faculty or staff of another research institution (e.g., Center for Disease Control, Georgia Tech) who have credentials similar to those of full members. They have all the rights and privileges of full members, except that they may only serve on University or GDBBS committees in an unofficial capacity and they may only serve as dissertation co-advisors. Adjunct members do not count toward the minimum number of required Emory dissertation committee members.

Adjunct members are not reported as graduate faculty for the purpose of institutional research and evaluation that is both internal and external to the University.

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Faculty Listing
Faculty Member	Research	Program
Rustom Antia, PhD Full Member - Immunology and Molecular Pathogenesis Full Member - Population Biology, Ecology, and Evolution rantia@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences Modeling the dynamics of immune responses and infections.	Modeling the dynamics of immune responses and infections.My research interests encompass a broad area of theoretical and empirical studies of the interaction between pathogens and the immune response. I use mathematical models and computer simulations in conjunction with experimental work to: understand the complex and often counter-intuitive dynamics of pathogens and immune responses in vivo; estimate important biological parameters that are not directly measurable by experimentation; and generate empirical tests of different models and hypotheses. Almost all my theoretical work is based on experiments, mostly done in collaboration with other experimental immunologists at Emory, and some done in my laboratory. Some areas I am interested in are: (i) the measurement of birth and death rates of immune cells; (ii) the generation of a theoretical framework to understand immune memory; (iii) theory and modeling to describe the dynamics of viral and bacterial infections; (iv) the use of antimicrobial agents to control infections; and (v) the evolution of pathogens and their hosts.	IMPImmunology and Molecular Pathogenesis - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Antia	Rustom		Full Member
Michal Arbilly, PhD Affiliate Member - Population Biology, Ecology, and Evolution michal.arbilly@emory.edu \| Faculty Profile Assistant Teaching Professor, Department of Biology, Emory College of Arts and Sciences Teaching biology with a focus on quantitative methods; evolution and evolutionary genetics; behavioral ecology.	Teaching biology with a focus on quantitative methods; evolution and evolutionary genetics; behavioral ecology.I use computer models to simulate the evolution of learning in social animals, in an attempt to shed light on variations in learning and in degree of social interaction we see in nature. I am especially interested in the interaction between sociality and cognition, and how they co-evolve to produce complex cognitive abilities, like theory of mind. My simulations combine behavioral ecology models of animal interaction with population genetics models, and with models of cognitive processing. I am also interested in the biologically wired traits that promote the evolution of culture, and shape its complexity.	PBEEPopulation Biology, Ecology, and Evolution - Affiliate Member	Arbilly	Michal		Affiliate Member
Yegor Bazykin, PhD (he/him) Full Member - Population Biology, Ecology, and Evolution gbazyki@emory.edu \| Faculty Profile \| Lab Website Visiting Professor, Department of Biology, Emory College of Arts and Sciences I use comparative genomics and bioinformatics to investigate sequence variation and evolution, and theory to interpret the observed patterns.	I use comparative genomics and bioinformatics to investigate sequence variation and evolution, and theory to interpret the observed patterns.We perform computational analysis of biological evolution in a broad range of biological systems – from viruses to humans. We develop and apply methods to measure and disentangle the roles of evolutionary forces – mutation, selection, gene flow, recombination and genetic drift – in shaping evolution and variation. We use comparative genomics and bioinformatics to investigate different aspects of sequence variation and evolution, and theory to interpret the observed patterns. Current research in the lab falls into three general directions: Inference of Natural Selection and Genetic Interactions from Genomic Data. Mutations may be advantageous or deleterious. Whether a particular mutation harms the cell carrying it, or does it good, may be inferred from its rate of spread, which can in turn be inferred from sequencing data. Moreover, interactions between mutations shape the phenotype. We develop approaches for inference of selection forces and interactions from genetic data, and apply them to a broad range of organisms. Mutations in Germline and in Cancer. Mutations arise due to a wide range of processes. Changes in these processes, e.g. exposure to ultraviolet rays or a modification of a protein involved in handling of DNA, may increase the rate of mutations and/or change their character. We infer changes in mutagenesis from changes in the mutation rates and patterns observed in large-scale sequencing data. Ultimately, such approaches might improve understanding of heritable mutagenesis and cancer diagnosis and treatment. Predicting Evolutionary Dynamics of Pathogens. Evolution of pathogens allows them to evade host immune system, contributing to disease and death caused by them. We are trying to predict such dynamics, notably in Influenza A and SARS-CoV-2.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Bazykin	Yegor		Full Member
Chris Beck, PhD (he/him) Affiliate Member - Population Biology, Ecology, and Evolution cbeck@emory.edu \| Faculty Profile \| Lab Website Professor of Pedagogy, Department of Biology, Emory College of Arts and Sciences Approaches to scientific teaching; Effects of resource quality on life history traits; Effects of plant secondary compounds on insect microbiomes	Approaches to scientific teaching; Effects of resource quality on life history traits; Effects of plant secondary compounds on insect microbiomesnull	PBEEPopulation Biology, Ecology, and Evolution - Affiliate Member	Beck	Chris		Affiliate Member
Sarah Bowden, PhD Adjunct Member - Population Biology, Ecology, and Evolution sebowdenphd@gmail.com \| Faculty Profile Data Scientist Contractor, Office of Innovation, Development, Evaluation, and Analytics, Division of Global Migration and Quarantine, Centers for Disease Control and Prevention I use machine learning, mathematical and statistical modeling, and spatial analysis to address questions at the interface of ecology and public health.	I use machine learning, mathematical and statistical modeling, and spatial analysis to address questions at the interface of ecology and public health.My research uses quantitative techniques, such as machine learning, mathematical and statistical modeling, and spatial analysis, to address questions at the interface of ecology and public health. My interests lie mostly within the realm of vector-borne and zoonotic diseases. I am also interested in how data science can be applied within ecology and public health, as well as which analytic tools and platforms can best support reproducibility and open science research. Some important themes and questions of my research include: (1) How do trans-boundary ecosystem effects alter infectious disease transmission? Some species, such as mosquitoes, undergo an ontogenetic niche shift where they spend part of their life cycle (egg, larval, and pupal stages) in the aquatic environment and the remainder of their life cycle (adult stage) in the terrestrial environment. This niche shift makes it possible for interactions during the aquatic life stages (e.g., biotic interactions like interspecific competition and abiotic interactions like temperature) to impact population dynamics of the terrestrial life stage -- a phenomenon known as trans-boundary ecosystem effects. The ability of mosquitoes to produce such effects is of interest to both ecologists and epidemiologists because many mosquito species serve as disease vectors during the adult life stage. My research in this area includes laboratory microcosm experiments to measure the effect of interspecific competition on the vital rates of three important vector mosquito species, which showed a competitive hierarchy among these species. I have also studied the sensitivity of these vital rates to temperature and interspecific competition simultaneously, showing that a vector's thermal niche can be altered by competitive interactions in the larval stage. (2) Which locations and/or animals are likely to give rise to infectious disease spillover? The current approach to disease outbreaks is fully reactive, where a response is mounted only after an outbreak is detected. Using machine learning algorithms borrowed from the field of computer science, I am interested in how we can move toward a proactive approach to disease outbreaks by determine where and from which species outbreaks are most likely to occur. I have collaborated on research in this area that includes implementing a supervised learning algorithm to determine which rodent species are most likely to be undiscovered or future reservoirs of zoonotic pathogens, as well as which bat species are likely to be undiscovered or future reservoirs of filoviruses, based on trait similarity to known reservoir species. My postdoctoral research took this methodology and added a temporal component where I attempted to predict the probability that a county would see human West Nile virus cases in a given year based on past land cover changes in that county. In my research at the CDC, I am also implementing these algorithms on large socio-demographic and public health datasets. (3) How can scientists make our research more open and reproducible? As a data scientist, I spend a lot of time thinking, learning, and teaching others about data, quantitative methods, and how to combine them to get interpretable results. New methods for analyzing data are constantly being developed, so keep up to date on how to implement new methodologies and sharing that information with my colleagues is very important. Finally, joining data with an appropriate method to extract and communicate new insights is what research is all about. I do this using code in the R language and RStudio development environment. While I have been using R for over a decade, I thoroughly enjoy learning new things on a daily basis, as well as creating presentations and workshops to share with scientists at all career stages to help them optimize the analysis, visualization, and communication of their research.	PBEEPopulation Biology, Ecology, and Evolution - Adjunct Member	Bowden	Sarah		Adjunct Member
Yana Bromberg, PhD Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution yana.bromberg@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences The lab is currently working on implementing machine learning-based models for understanding of what protein function aspects (if any) are captured by large language models, whether metagenome functionality can be inferred from sequencing reads, and how genome variants impact molecular function in association with disease.	The lab is currently working on implementing machine learning-based models for understanding of what protein function aspects (if any) are captured by large language models, whether metagenome functionality can be inferred from sequencing reads, and how genome variants impact molecular function in association with disease.The primary focus of the research in my lab can be summarized two words – molecular function. Where does the molecular functional machinery of life come from? Why and how does it run? Is there a minimum set of the functional gears that represents a viable entity? Biological machinery is a complex system of many molecular interactions, both within and outside a single cell. I believe that the DNA blueprint of this machinery, the understanding of which is currently being improved with increasingly high-throughput techniques, holds many of the answers to our questions. Thus, my long-term goal is to understand how biological functionality is encoded in genomic data, whether by a single gene, a genome, a metagenome, or some combination of these. To this end, my lab develops computational, machine learning, and network- based methods for annotation and analysis of molecular functions. My research aims to explore the origins and details of protein function and to make sense of the available genome and metagenome data. Specifically, we are: (1) Correlating genome variation to phenotype, (2) Identifying the specifics of sequence-encoded molecular functions, and (3) Elucidating complex microbial community (and host) interactions. Functional effects of genomic variants. Nearly 20 years ago, we developed SNAP, a neural network- based method for predicting non-synonymous variant functional effects. Since then, despite the rapid proliferation of variant effect prediction tools, there remains a crucial gap in our understanding of variants within the molecular function context. Pioneering positive-unlabeled learning approaches, we propose to improve existing tools by extracting significantly larger variant effect training sets directly from genome data, with potential implications for disease diagnostics and treatment. Recent advances in protein and DNA language models (LLMs) also provide an unsupervised manner for improving our prediction techniques. Whole-genome variation in disease. We've discovered that common non-synonymous variants, often dismissed as irrelevant, actually often carry more functional effects than rare variants. Based on this inference, we've developed AVA,Dx, an SVM-based model that maps whole-genome variation to functional changes associated with diseases like Crohn's Disease, Tourette Syndrome, and Chronic Obstructive Pulmonary Disease. While we are investigating other applications and improvements of AVA,Dx, we're also actively exploring other methods for identifying the molecular function failures that underlie various disorders. Exploring unknown functionality of microbes and microbiomes. Our lab has developed network- based classifiers, such as fusionDB, pEffect, mi-faser, and LookingGlass to identify microbial bacterial functionality. These tools have been instrumental in uncovering microbiome functional signatures in diverse environmental conditions. Currently, we're working on expanding these tools to annotate microbiome functions directly from reads and exploring emergent bacterial functional abilities encoded in metagenomic data. Furthermore, we also recently proposed a novel way of identifying microbial proteins of similar function, without defining the function itself. This approach opens new avenues for exploration of bacterial functionality, particularly as related to environmental preferences, microbial evolution, and microbe-host interactions. Evolution of function at the origins of life. Our expertise lies in studying protein evolutionary timelines, common origins of transition metal-binding structures, and the ancient evolution of peptides. Tools like sahle and mebipred have been developed for structural analysis, identifying protein structural repeats, and exploring the history of life on Earth and potentially other planets. We are currently building tools that would allow discovery of previously unseen proteins, likely deep in the oceanic metagenomes, carrying out well known functions. These functions, we propose, lie at the origins of life on this planet, and possibly others.	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Bromberg	Yana		Full Member
Dave Civitello, PhD (he/him) Full Member - Population Biology, Ecology, and Evolution dcivite@emory.edu \| Faculty Profile Associate Professor, Department of Biology, Emory College of Arts and Sciences Program Director, PBEE I study the ecological and environmental drivers of parasite transmission in animal populations. My research aims to mechanistically link physiology, individual-level traits, and population- or community-level disease dynamics.	I study the ecological and environmental drivers of parasite transmission in animal populations. My research aims to mechanistically link physiology, individual-level traits, and population- or community-level disease dynamics.Parasites are ubiquitous, but severe outbreaks of disease erupt sporadically in space and time. I seek to understand the mechanisms that drive variation in natural epidemics the consequences for host populations by taking a trait-based approach to disease ecology. Thus, an overarching goal of my research is to mechanistically link physiology, individual-level traits, and population- or community-level disease dynamics. My approach combines observations of natural systems, theoretical models, and experiments in the laboratory and field. I primarily focus on disease in aquatic systems that are relevant for basic research, conservation, and human health, but many insights arising from my work can apply generally. I describe some of my central research themes below: 1. Parasite transmission is a critical determinant of epidemiological dynamics in human and wildlife populations. My research builds mechanistic understanding of transmission in dynamic host populations and communities and consequences for host populations. For example, classic theory suggests that epidemics start most easily and become largest in dense host populations. I recently illustrated how the parasite depletion and interference among hosts can drive the opposite pattern: high host density can depress parasitism by decreasing the exposure of hosts to parasites (Civitello et al. 2013, Ecology Letters). Similarly, non-host predators that consume (deplete) parasites generally reduce disease in hosts, however, if predators also consume hosts, they can concentrate parasites into the few remaining hosts, amplifying infection intensity (Rohr, Civitello, et al. 2015, PNAS). I also recently demonstrated that non- host species broadly reduce disease in their hosts, often through this parasite depletion mechanism, but also via competitive effects on host density (Civitello et al. 2015a, PNAS). A current major focus of my research is to build and test transmission models for heterogeneous host populations, specifically focusing on body size, because it can simultaneously affect host-parasite contact rates and susceptibility to infection. Altogether, this research has key implications for fundamental parasite ecology, biocontrol, and conservation. 2. Host energetic condition can drive epidemics by simultaneously modulating host and parasite reproductive rates. This can explain how seemingly diverse environmental factors similarly shape disease outbreaks. Specifically, my work has demonstrated that factors that promote host growth (e.g., high resource (food) availability and good water quality) can drive larger epidemics in host populations by jointly increasing the birth rate of hosts (which boosts host densities) and the production rate of parasites within infected hosts (which determines infectiousness; Civitello et al. 2013, Ecology; Civitello et al. 2015, J. Animal Ecology). Conversely, factors that erode host energetic condition (e.g., toxicants) inhibit epidemics by reducing host reproduction and infectiousness (Civitello et al. 2012, PRSL-B). Although these effects can be independent from effects on transmission (e.g., water quality), this work also address scenarios when these factors also influence transmission (e.g., toxicants). A current major focus of my research is to build and test bioenergetics models for individual infection dynamics, which can ultimately yield a unified, mechanistic framework to predict the consequences of many ecological factors (e.g., resources, temperature, pollution, host density, population size structure, etc.) on disease spread through their effects on physiological traits of hosts and parasites. 3. Collaborative research: Collaboration is an essential element of successful science, and I believe it is important train advisees to work well with others. I collaborate with several amphibian disease ecologists on a project that aims to assess the potential of boosting amphibian immunity to the virulent pathogen Bd through exposure to the dead parasite (essentially an inactivated vaccination; McMahon et al. 2014, Nature). My role involves building and testing eco-epidemiological models that predict the population- level consequences of disease and "vaccination" by scaling up the individual-level protective effects we've previously documented.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Civitello	Dave		Full Member
Karen N. Conneely, PhD Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution kconnee@emory.edu \| Faculty Profile Associate Professor, Department of Biostatistics and Bioinformatics, Rollins School of Public Health Associate Professor, Department of Human Genetics, School of Medicine Biomarkers and genetic variants predisposing to disease; DNA methylation as a mediator between environment and phenotype.	Biomarkers and genetic variants predisposing to disease; DNA methylation as a mediator between environment and phenotype.My research focuses on statistical methods for detecting genetic and epigenetic variation associated with complex traits. Through the development of novel techniques and the application of existing ones, my work seeks to 1) identify biomarkers and variants predisposing to disease, and 2) explore the role of DNA methylation as a mediator between environment and phenotype. As part of my involvement in a genome-wide association study (GWAS) of type 2 diabetes and numerous candidate gene studies, I developed statistical methods and software to adjust for multiple testing in large-scale genetic association studies and meta-analyses. My lab also develops and applies statistical methods for detecting epigenetic variation associated with complex traits. A current focus is on integrative studies of aging and disease phenotypes using genomic, epigenomic, and transcriptomic sequencing data, with a particular interest in the epigenomic and transcriptomic consequences of clonal hematopoiesis.	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Conneely	Karen		Full Member
Jacobus C. de Roode, PhD Full Member - Population Biology, Ecology, and Evolution jderood@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences Director, Infectious Diseases Across Scales Training Program (IDASTP) Parasite virulence evolution, animal self-medication and evolution of drug resistance.	Parasite virulence evolution, animal self-medication and evolution of drug resistance.My research focuses on the ecology and evolution of host-parasite interactions. This field has won in popularity in the last few decades because it has become apparent that parasites can importantly drive the ecology and evolution of their hosts. Moreover, a proper understanding of the basic ecology and evolution of parasites is required for devising optimal public health strategies to protect humans and agricultural animals against their own infectious diseases. Leading questions in the field of host-parasite ecology and evolution are how parasites evolve to be more or less harmful to their hosts, how hosts evolve to optimally protect themselves against disease, and how human practices may affect the evolution of parasites. My research addresses these questions in the following ways. Virulence evolution Using protozoan parasites in monarch butterflies, I am studying how parasite virulence can be selected for and be maintained in natural populations. So far, my work has shown that virulence may evolve as a by-product of natural selection acting on between-host parasite transmission and as a consequence of competition between different parasites inhabiting the same host. We are currently studying how the environment in which hosts and parasites interact with each other can drive the evolution of parasite virulence. In particular, we are testing the hypothesis that toxic plants that monarchs use as larval food can select for more harmful parasites. Evolution of self-medication in nature Hosts can defend themselves against parasites in many different ways. We are studying several of these ways in monarch butterflies, and are especially interested in how monarch butterflies can use behavioral mechanisms to fight against disease. We have shown that infected female butterflies can protect their offspring by laying their eggs on larval food plants that are toxic to the parasites. We are currently exploring how such medication evolves in nature, using natural populations in which monarch butterflies vary in their infection risks. Evolution of parasitic mites of honeybees We have recently started a collaborative project to apply the basic principles by which parasites evolve virulence to a current societal problem: the collapse of our honeybee populations. Honeybees are declining worldwide, and the leading cause for these declines is a parasitic mite that can wipe out entire bee hives. We are testing the hypothesis that current bee keeping practices are selecting for harmful mites by facilitating between-hive mite transmission. Finding support for this hypothesis would provide direct relevance to mitigating honeybee disease risks by providing alternative methods of beekeeping. Evolution of drug resistance Malaria infections often consist of drug-resistant and -sensitive strains, resulting in potential competition between these strains. In collaboration with the CDC we are studying such competition in human malaria cases. Our goal is to understand the role of within-host competition in the spread of drug resistance. Microbiomes and disease We use monarch butterflies to study how host diets change gut microbiomes and alter resistance to disease. Animal migration We use genomics to understand the genetic basis of migration, using monarch butterflies as a model system	PBEEPopulation Biology, Ecology, and Evolution - Full Member	de Roode	Jacobus		Full Member
Mike Epstein, PhD (he/him) Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution mpepste@emory.edu \| Faculty Profile Professor, Department of Human Genetics, School of Medicine Statistical genetics and genetic epidemiology of complex human traits.	Statistical genetics and genetic epidemiology of complex human traits.My research focuses on statistical techniques for human gene mapping of complex traits. This work involves two synergistic components: a methodological component focused on developing novel statistical techniques for improved gene mapping and an applied component focused on using existing methods to map genes involved in diseases such as Alzheimer's disease, breast cancer, epilepsy, and orofacial clefting.	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Epstein	Mike		Full Member
Nicole Marie Gerardo, PhD (she/her) Full Member - Population Biology, Ecology, and Evolution ngerard@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences Director, GDBBS Investigates the evolutionary ecology of host-microbe interactions using insect systems	Investigates the evolutionary ecology of host-microbe interactions using insect systemsI use an integrative, evolutionary ecology approach to study the dynamics of host-microbe interactions. I have utilized large-scale field surveys, molecular genetics, and laboratory experiments to understand the adaptive mechanisms by which hosts and microbes establish and maintain associations. To address such questions, I focus on insect-microbe associations amenable to long-term laboratory maintenance and experimental manipulation. These systems include true bugs and their beneficial bacterial associates, and symbionts associated with fungus-growing ants. I am particularly interested in understanding these systems from the perspective of microbial ecology and evolution.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Gerardo	Nicole		Full Member
Thomas R. Gillespie, PhD Full Member - Population Biology, Ecology, and Evolution thomas.gillespie@emory.edu \| Faculty Profile \| Lab Website Professor and Chair, Department of Environmental Sciences, Emory College of Arts and Sciences Professor, Department of Environmental Health, Rollins School of Public Health Anthropogenic environmental change: biodiversity, ecology and emergence of pathogens of people, wildlife, and domestic animals.	Anthropogenic environmental change: biodiversity, ecology and emergence of pathogens of people, wildlife, and domestic animals.The overall goal of our work is to determine how and why anthropogenic changes to tropical forests place people and wildlife living in such ecosystems at increased risk of pathogen exchange. The central hypothesis of this work is that key human behaviors, wildlife behaviors, ecological conditions, and landscape features increase the risks of interspecific disease transmission. This effort entails a combination of epidemiology, molecular ecology, behavioral ecology, social and clinical survey, and spatially explicit modeling. The ultimate product will be an implementable plan for protecting human and wildlife health, while simultaneously ensuring the sustainability of the ecosystems within which they live.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Gillespie	Thomas	Environmental Effects Epidemiology Infectious Diseases / Agents Microbiology Parasitology Veterinary Medicine	Full Member
John W. Glasser, PhD, MPH Adjunct Member - Population Biology, Ecology, and Evolution jglasser@skybest.com \| Faculty Profile Adjunct Associate Professor, Department of Biology, Emory College of Arts and Sciences Mathematical modeling, largely of vaccine-preventable diseases, to design or evaluate and occasionally improve public policy.	Mathematical modeling, largely of vaccine-preventable diseases, to design or evaluate and occasionally improve public policy.I studied biology at Princeton, population biology at Duke, and international health, biostatistics and epidemiology at Harvard. After Epidemic Intelligence Service in the CDC's Division of Reproductive Health, I returned to Harvard to study mathematical biology with the late Richard Levins. By comparing scenarios differing solely in phenomena of interest, realistic mathematical modeling is among the most reliable, if not only means of evaluating public health programs. Such evaluations can be prospective, involving hypothetical interventions being contemplated, or retrospective, involving alternatives to ongoing programs. Since resuming my CDC duties, I have assisted in designing, or evaluating and occasionally improving public health programs at home and abroad by modeling transmission of the pathogens causing chlamydia, COVID-19, herpes simplex 2, AIDS, influenza, measles, pertussis, rotavirus, rubella and congenital rubella syndrome, SARS, smallpox, and both chickenpox and shingles, together with various mitigation strategies. The CDCs in China and Taiwan; the Ministries of Health in Bolivia, Costa Rica, Jamaica, Jujuy Province, Argentina, São Paulo State, Brazil, and Morelos State, Mexico; the Romanian Public Health Institute; Swedish Institute for Infectious Disease Control (now Public Agency of Sweden); and World Health Organization have consulted me. Besides serving as an epidemiologist in the Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, I have adjunct appointments in population biology, ecology and evolution at Emory University, where I serve on student committees and lecture on dynamic models in the quantitative methods core course, and mathematics at Purdue University, where I also contribute to an infectious disease modeling seminar. I helped to formulate the US response were Variola major reintroduced by terrorists. And my colleagues and I explained why earlier care-seeking for symptoms that might herald SARS, together with increasingly accurate diagnoses and effective isolation, had far more impact than quarantine. As mixing is the essence of meta-population modeling, we generalized Annette Nold's (Math Biosci 1980; 52:227-40) function to include a) preferential contacts between parents and children as well as contemporaries and b) age-independent contacts among co-workers. We also developed a method for estimating age-specific rates of infection from cross-sectional serological surveys when passively acquired maternal antibodies decay and active immunity wanes, allowing re-infection with clinical consequences that depend on residual immunity. Assuming that vaccination is responsible for secular changes in the epidemiology of pertussis throughout the developed world – by reducing the exposures to infectious children that used to boost immunity – we deduced the optimal number and timing of revaccinations in Sweden. We also explored the impact of heterogeneity in factors affecting effective reproduction numbers, and hence our ability to prevent or control outbreaks, and applied our insights to spatial heterogeneity in vaccine coverage due to personal-belief exemptions, together with preferential mixing among like-minded people. And, perhaps most significantly, we promoted gradients of effective reproduction numbers as means of identifying optimal prevention or control programs. Recent projects include devising vaccination strategies for accelerating elimination of measles, rubella and other vaccine-preventable diseases from China and controlling COVID-19 (stage III of most vaccination programs, stages I and II generally being healthcare and other essential workers and those at risk of serious disease, hospitalization and death, respectively) in Jamaica, where we also evaluated myriad non-pharmaceutical interventions. I am also modeling SARS-CoV-2 transmission and control for public health officials in Argentina, Canada, and the United States.	PBEEPopulation Biology, Ecology, and Evolution - Adjunct Member	Glasser	John		Adjunct Member
Joanna B. Goldberg, PhD Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution joanna.goldberg@emory.edu \| Faculty Profile \| Lab Website Professor, Division of Pulmonary Medicine, Department of Pediatrics, School of Medicine Synthesis and regulation of surface polysaccharides and other adhesins, to develop rational strategies to disrupt pathogenesis.	Synthesis and regulation of surface polysaccharides and other adhesins, to develop rational strategies to disrupt pathogenesis.The Goldberg laboratory focuses on the strategies used by bacteria to cause diseases in humans, in particular respiratory infections in individuals with the genetic disease cystic fibrosis. We study various bacterial factors, especially surface polysaccharides and other potential adhesins and assess their contribution to virulence and the physiology of the bacterium and their effects on host. We also examine and dissect essential metabolic pathways in these bacteria as targets for the development of novel therapeutics and vaccines to combat these naturally antibiotic-resistant pathogens.	MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Goldberg	Joanna		Full Member
Samuel M Jenness, PhD, MPH Full Member - Population Biology, Ecology, and Evolution samuel.m.jenness@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Epidemiology, Rollins School of Public Health I use network science and mechanistic modeling approaches to investigate the drivers of and prevention strategies for infectious disease transmission.	I use network science and mechanistic modeling approaches to investigate the drivers of and prevention strategies for infectious disease transmission.My research focuses on solving problems in infectious disease epidemiology with complex dependencies that render traditional statistical and epidemiological methods unworkable. This involves working at the intersection of methods development and applications that span complex dynamic systems, network science, and economic decision analytics. My research asks questions about what drives transmission of infectious diseases and what we should do to contain them. My primary focus is on sexually transmitted infections (including HIV) and respiratory infectious diseases. This research directly supports decision making about allocating public health resources and selecting optimal disease prevention strategies. In my methodological research, I build tools to improve the science of my lab and other researchers. My main contribution in this area is the development of epidemiological methods and software for infectious disease transmission modeling that explicitly incorporate network structures. These methods use networks as a framework to investigate how diseases travel across social contacts that form and dissolve over time. My primary contribution has been the creation of EpiModel, an open-source software tool for network modeling. I am the lead developer as it continues to evolve. The software has been downloaded over 120,000 times, been featured in 53 scientific publications, and partially supports around $5.4 million in research projects funded by NIH and CDC. In July 2018, I received my first NIH R01 grant to develop EpiModel into a mature platform. For my applied research, I investigate the structural, network, behavioral, and biological risk factors for STIs and respiratory infectious diseases (TB, influenza, SARS-CoV-2). Much of this work involves understanding how to optimize pharmaceutical therapies for the prevention and treatment of HIV and bacterial STIs. Projects have evaluated the impact of CDC's HIV preexposure prophylaxis (PrEP) guidelines on HIV incidence given uncertainty in clinical interpretation and the other that evaluates the role of HIV PrEP on closing the black/white racial disparities gap in the United States. Although my research projects are methodological and computational, much of my research experience involves hands-on primary data collection. This started with my work at the New York City health department in behavioral studies of key populations, developed internationally during my PhD through fieldwork in Ghana, and continues today through a massive web-based study of men who have sex with men (my first NIH grant, an R21). I am an active co-investigator on several observational and experimental studies of infectious disease in the United States and internationally. My background as a infectious disease modeler and methodologist strengthens this empirical work, as models often identify key gaps in our knowledge about complex systems. My long-term goal is to produce research that advances our knowledge about infectious disease risk through empirical and computational epidemiology. My future research will focus on the intersection between networks, co-circulating infections that offer the potential for synergy in disease prevention efforts, and health disparities. My research portfolio will continue to expand into respiratory infectious diseases through collaborations with faculty and students in my department. This new research on TB and SARS-CoV-2 will bring the innovations of my mechanistic modeling and network science frameworks to bear on these urgent public health problems.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Jenness	Samuel		Full Member
Minsu Kim, PhD Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution minsu.kim@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Physics, Emory College of Arts and Sciences Stochastic responses of bacteria to antibiotics and random clearance of bacterial populations	Stochastic responses of bacteria to antibiotics and random clearance of bacterial populationsCells function through complicated interactions of multiple components (genes, proteins, metabolites, etc.). Using a system-level approach, we investigate how interactions of these components at the molecular level lead to the function of cells at the cellular level. Experimentally, we employ advanced biophysical techniques as well as conventional microbial techniques to characterize biological processes at the molecular and cellular levels. To establish a quantitative bridge between the two levels, we employ mathematical modeling. Our research is highly interdisciplinary, at the intersection of microbiology, biophysics, synthetic biology, and theoretical biology. One research area that we are actively pursuing is "random" clearance of bacteria using antibiotics. We found that bacteria respond to antibiotics stochastically, and this stochasticity may be manipulated to clear infections at low antibiotic concentrations that were previously deemed inefficacious. Our research aims at understanding the origin and implications of the inherent stochasticity and utilizing this stochasticity to improve antibiotic treatments.	MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Kim	Minsu		Full Member
Uriel Dan Kitron, PhD, MPH Emeritus Member - Population Biology, Ecology, and Evolution ukitron@emory.edu \| Faculty Profile Emeritus Professor, Department of Environmental Sciences, Emory College of Arts and Sciences Ecology and epidemiology of malaria, Chagas disease, dengue, Zika, polyparasitism, West Nile virus and Lyme disease in the US and around the world.	Ecology and epidemiology of malaria, Chagas disease, dengue, Zika, polyparasitism, West Nile virus and Lyme disease in the US and around the world.My research and teaching interests center around the eco-epidemiology of infectious diseases, particularly those carried by insects and ticks (vector-borne), and the zoonoses (diseases that are common to humans and other animals). Many emerging and tropical diseases belong to these groups. For diseases such as Malaria, Dengue, West Nile Fever, Lyme disease and Chagas disease my group studies the ecology of the arthropod vectors and the mammalian reservoir hosts incorporating a strong field component (trapping mammals, collecting insects, identifying environmental features), as well as laboratory work. In my laboratory we apply tools such as geographic information systems and remote sensing to gather and manage environmental data that can explain the spatial distribution of disease and vectors, and assess risk of transmission. Following quantitative spatial analysis and mathematical modeling, maps can then be produced to target further research efforts, as well as in support of surveillance and control efforts by public health agencies. Current research efforts funded, among others, by NIH, NSF and CDC, include a study of the urban ecology of West Nile virus in Chicago, and international studies of malaria and schistosomiasis in Kenya and of dengue and Zika virus in Brazil and Peru. Teaching interests include epidemiology of infectious diseases, spatial epidemiology and ecological parasitology. Because of the applied nature of some of my research, I am also interested in the transmitting of scientific information.	PBEEPopulation Biology, Ecology, and Evolution - Emeritus Member	Kitron	Uriel	Environmental Effects Epidemiology Infectious Diseases / Agents Parasitology	Emeritus Member
Katia Koelle, PhD (she/her) Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution katia.koelle@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences I use quantitative approaches to study the ecological, evolutionary, and within-host dynamics of RNA viruses affecting humans.	I use quantitative approaches to study the ecological, evolutionary, and within-host dynamics of RNA viruses affecting humans.I am a population ecologist and evolutionary biologist whose primary interests lie in using quantitative approaches to understand how and why populations change in size and genetic composition over time and space. My research focuses on viral populations) particularly human infectious diseases caused by viruses that have as their genetic material RNA. Due to their error-prone replication) RNA viruses evolve on the same timescale as they spread through populations. such that understanding fluctuations in the population size of infected individuals and observed evolutionary changes to the viral population requires joint consideration. The types of analyses I develop and rely on to study viral dynamics include the design of mathematical models and the statistical fitting of these models to data. My current research program spans five topics of inquiry: 1. The interplay between viral evolution and the epidemiological spread of viral infectious diseases. A large part of my research focuses on developing 'phylodynamic' models to better understand the interplay between viral evolution and population level infectious disease spread. One of my earliest contributions to this area found that patterns of seasonal influenza's antigenic evolution could be reproduced under the assumption of a genotype-phenotype map comprising neutral networks. This work paved the way to the development of more general modeling frameworks for antigenically variable pathogens to yield a more theoretical basis for understanding the topologies of viral phylogenies. 2. Constraints on viral adaptation. While RNA viruses are known to rapidly evolve, they also face constraints in their ability to adapt to new or changing environments. I am interested in understanding these constraints through both modeling and statistical analyses of viral sequence data. I have contributed to this area with a phylodynamic study of influenza that showed that genetic linkage within and to a lesser extent across gene segments can account for characteristic features of influenza evolution. My group has further found evidence of strong genetic linkage across gene segments within a human influenza challenge study) indicating that genetic linkage can constrain viral adaptation within an infected individual. Finally, we have recently developed methods for inferring transmission bottleneck sizes between donor and recipient hosts. By applying this method to influenza virus deep-sequencing samples, we found that bottleneck sizes are relatively loose, indicating that influenza virus adaptation is unlikely to be constrained by this factor. 3. Interindividual variation in within-host viral dynamics and evolution. Considerable heterogeneity exists across hosts in their susceptibility, infectivity, and response to infection with viral pathogens. My group's contributions to understanding the causes and consequences of this heterogeneity focus on how host immune status) as determined by infection history, impact selection pressures experienced by a viral population within a host. We have found that hosts with some degree of immunity serve as a source for new antigenic variants if viral antigenicity is directly a target of selection. We have also further studied in detail the within-host viral dynamics of dengue virus, showing that immune status and the identity of the infecting dengue serotype are both important factors impacting viral load dynamics within infected hosts. 4. The impact of control measures of the epidemiological and evolutionary dynamics of viral infectious diseases. Due to the nonlinearity of infectious disease transmission dynamics, mathematical models are useful tools to evaluate the effect of targeted disease control measures. My research contributes to understanding the potential effects of disease control for dengue virus, the world's most prevalent vector-borne viral disease. My research has found that vector control policies that reduce transmission only moderately have the potential to inadvertently increase dengue disease incidence. More recent work focuses on evaluating the long-term epidemiological effects of dengue vaccines that are currently under development or recently licensed. I have also been involved in a modeling consortium to provide input to the World Health Organization's Strategic Advisory Group of Experts who makes global recommendations of vaccine use. 5. Phylodynamic methods for statistically interfacing mathematical models with viral sequence data. A large statistical literature exists for interfacing nonlinear epidemiological models with time series data on disease cases to estimate model parameters and select between alternative models. With major advances in sequencing technologies over the last decade, long-term time series data are becoming sparse relative to sequence data. In recent years, my group has contributed significantly to the development of statistical approaches that would enable using viral genealogies, in addition to or instead of time series data, to infer epidemiological model parameters. We have specifically developed coalescent-based approaches using particle filtering approaches and have shown how coalescent processes theoretically map to infection disease models.	MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Koelle	Katia		Full Member
Subra Kugathasan, MD (he/him) Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution skugath@emory.edu \| Faculty Profile \| Lab Website Marcus Professor, Division of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine Professor, Department of Human Genetics, School of Medicine Genetic variation and phenotypic characterization of early and adult onset inflammatory bowel disease in Caucasians and African Americans.	Genetic variation and phenotypic characterization of early and adult onset inflammatory bowel disease in Caucasians and African Americans. Dr. Kugathasan's research has focused on understanding the genetics and genomic advances of inflammatory bowel disease (IBD). Inflammatory bowel disease (IBD), which comprises Crohn's disease (CD) and ulcerative colitis (UC), is estimated to affect approximately 3 million Americans. IBD is a destructive, life-long, chronic inflammatory disorder that results in gastrointestinal bleeding, weight loss and poor quality of life. IBD affects all races and onset of the disease is usually in children and young adults. Familial, twin, linkage and GWAS studies suggest that IBD is highly heritable. His goal is to further extend novel genetic discoveries in IBD, in particular common and rare susceptibility variants that underlie the onset and disease outcome in IBD. Since he moved to Emory in 2008, one of his focus has been the identification of genetic and epigenetic mechanisms of IBD in diverse population (non-whites mainly African Americans). This genetic / epigenetic studies have progressed to multi-omic studies now including single-cell transcriptomics, metabolomics and . In addition, he has been investigating the immunogenetic mechanisms that underlie this chronic intestinal inflammation in children and adults with IBD. His research interests include: To determine and identify genetic associations in very young onset IBD in comparison to those found in older patients with adult onset disease. In particular, to identify high effect, highly penetrant but rare variants that cannot be identified by genome wide association studies. Genome wide association studies of IBD in African Americans with IBD and the use of latest generation sequencing technologies to comprehensively ascertain variation that predispose or confer IBD risk to both African Americans and Caucasians. To identify susceptibility and modifying through Genotype, serotype, bacteriotype and gene expression studies in carefully and prospectively identified incident cases of early onset IBD. This would lead to risk stratification and personalized medicine in IBD. Transcriptomics including single cell RNA sequencing of human gut as part of the GUT ATLAS project Risk stratification and personalized therapy approaches using genomic in IBD	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Kugathasan	Subra		Full Member
Max Lau, PhD Full Member - Population Biology, Ecology, and Evolution msy.lau@emory.edu \| Faculty Profile Assistant Professor, Department of Biostatistics and Bioinformatics, Rollins School of Public Health My research focuses on developing novel statistical and computational approaches for understanding infectious disease dynamics, at the interface of statistics, disease ecology and epidemiology.	My research focuses on developing novel statistical and computational approaches for understanding infectious disease dynamics, at the interface of statistics, disease ecology and epidemiology.My research focuses on developing and applying rigorous novel statistical and machine learning approaches for infectious disease outbreaks. I have substantial experience in developing new integrative and cross-scale modelling approaches for studying disease dynamics at genomic, individual and population levels in spatial and temporal settings. My research has helped improved our understanding of the dynamics of and effects of controls for key disease systems including measles, influenza, Ebola and more recently COVID-19. I have published in high- profile journals including Proceedings of National Academy Sciences, Nature Ecology and Evolution, PloS Computational Biology and Journal of Royal Society Interface. a. Comparing and linking machine learning and semi-mechanistic models for the predictability of endemic measles dynamics. PLoS computational biology. 2022 b. Lau MSY et al. Characterizing super-spreading events and age-specific infectiousness of SARs-CoV-2 transmission in Georgia, USA. Proceedings of the National Academy of Sciences. 2020 September 8; 117(36). c. Lau MSY, et al. A competing-risks model explains hierarchical spatial coupling of measles l elimination. Nature Ecology & Evolution (2020): 1-6.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Lau	Max		Full Member
Bruce R. Levin, PhD Affiliate Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution blevin@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Biology, Emory College of Arts and Sciences Population biology and evolution of bacteria and bacteriophage and evolution, and treatment of infectious diseases.	Population biology and evolution of bacteria and bacteriophage and evolution, and treatment of infectious diseases.We do theoretical and empirical studies of the population biology and evolution of bacteria, their phages and plasmids, and the population dynamics, evolution, and control of infectious diseases. Our theoretical work involves the development and analysis of the properties of mathematical and computer simulation models. Our empirical studies include experiments with laboratory populations (chemostat and serial transfer culture) of bacteria (primarily, but not exclusively, E. coli) and Staphylococcus aureus) and their plasmids, temperate and lytic phage transposons. We also do studies of bacteria and their plasmids and phage isolated from natural populations. Currently, we, the students, postdocs, and Lab manager working with me and I, are engaged in four projects 1- The pharmacodynamics of antibiotics and bacteria and population and evolutionary biology of antibiotic and phage therapy of bacterial infections. 2- Studies of the population and evolutionary dynamics of temperate bacteriophage and lysogeny. 3- Studies of the population and evolutionary dynamics of lytic phage and bacteria with abortive infection mechanisms 4- Studies of the role of bacteriophages in determining the densities and species and strain composition in the enteric flora of humans using Fecal Microbiome Transplant samples. 5- Theoretical and experimental studies of the role of phagocytes in the treatment of bacterial infections using a Galleria melonella model,	MMGMicrobiology and Molecular Genetics - Affiliate Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Levin	Bruce		Full Member
John Lindo, PhD Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution john.lindo@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Anthropology, Emory College of Arts and Sciences My lab specializes in both the molecular and computational aspects of Ancient DNA research in humans and other animals. By utilizing an integrative approach, including ancient whole genomes, statistical modeling, and functional methods, the lab examines genetic fluctuations that have occurred in different environments over time, thereby pointing to genetic traits that can inform more fine-grained hypotheses of adaptation.	My lab specializes in both the molecular and computational aspects of Ancient DNA research in humans and other animals. By utilizing an integrative approach, including ancient whole genomes, statistical modeling, and functional methods, the lab examines genetic fluctuations that have occurred in different environments over time, thereby pointing to genetic traits that can inform more fine-grained hypotheses of adaptation.The recent development of high-throughput sequencing methods and dramatic increases in computational power have enabled geneticists to ask evolutionary questions that would have previously been intractable. The very same technological advances that have allowed geneticists to sequence the DNA of extant species on a grand scale have also dramatically increased the possibilities of ancient DNA studies. Only recently, however, have ancient genomes begun to become available in sufficiently large numbers to allow for population analyses-including those of humans. The use of ancient DNA to study evolutionary processes is, however, still in its infancy, and much of its power to help characterize the nature of adaptive events has yet to be fully realized. The field of ancient genomics, thus far, has mainly focused on human population movements, which for the most part have centered on Europe. However, ancient DNA can also be used to discover previously unknown genetic features underlying specific adaptive events to a specific environmental variable. Temporal studies can also extend beyond DNA, where changes in the ancient epigenome could be linked to environmental stress in humans due to warfare, nutrition, and colonialism. Furthermore, the juxtaposition of ancient and contemporary DNA from related populations lends itself well to the study of adaptive evolution because it allows for the examination of genetic fluctuations that occurred in different environments over time, thereby pointing to genetic traits that can inform more fine-grained hypotheses of adaptation. For example, one could identify loci that have experienced selection since their divergence with the ancient population, which may have been missed by examining the extant population alone. In addition, by utilizing whole genomes, rather than an a priori approach involving a set of candidate genes, changes involving gene function and regulation can be detected, which may be an integral part of adaptive evolution within species in differing environments. Ancient genomic data thus allow for a more precise identification of variants that contribute to the molecular mechanisms of an adaptive phenotype. Considering this, ancient DNA has tremendous power to supplement evolutionary adaptive studies by directly examining temporal relationships between pathogen-host selection, changes in food sources, domestication events, climatic changes, and even changes in social structures. Therefore, the use of ancient DNA, can deal with much more complex and comprehensive questions when used as an integrative approach. The objective of my research program is, accordingly, to clarify these expanded uses of ancient DNA in the framework of biological anthropology and in understanding the intricate history of the Americas, specifically in the regions categorized as "Latin America." In conjunction with this objective are interactive educational goals that will be key in revealing the full scope of "Latin American" ancestry, which, from a popular sense, draws heavily from post-colonial categorizations. Through ancient DNA research, outreach, and education, the grand vision of the program aims to comprehensively investigate three distinct periods of human evolutionary history in the Americas. The first being the thousands of years of ancient indigenous history, from hunter-gatherer groups to densely populated civilizations. The second, the radical social and environmental changes brought on by European contact. And the third, the link between ancient civilizations and modern communities currently living in the same regions, as well as their descendants in the United States. To accomplish this goal, ancient whole genomes will be utilized to enhance the study of adaptive evolution to local environments by revealing genetic features that may have become obscured in contemporary populations by demographic forces. I will exemplify this in a variety of populations, including Mexico, Guatemala, Colombia, and Peru, all of which have undergone major demographic shifts due to of European colonization.	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Lindo	John		Full Member
Anice Lowen, PhD (she/her) Full Member - Immunology and Molecular Pathogenesis Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution anice.lowen@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Microbiology and Immunology, School of Medicine Our research aims to reveal features of influenza A virus biology that support the rapid evolution of this pathogen.	Our research aims to reveal features of influenza A virus biology that support the rapid evolution of this pathogen.The Lowen Lab exploits molecular tools, classical virology, and animal models of infection to study the biology of RNA viruses, including influenza A virus and mammalian orthoreovirus . We are particularly interested in features of their biology that shape evolutionary dynamics and, in the case of influenza A virus, the mechanisms governing transmission between individuals. Much of our prior and current work focuses on reassortment and recombination – mechanisms by which co-infecting viruses exchange genetic information. In broader terms, we are interested in interactions among co-infecting viruses and the implications of these interactions for the evolution of viral populations. We also have active programs related to influenza A virus escape from humoral immunity, within-host viral diversity, influenza A virus emergence in new host species, viral detection by cytoplasmic dsRNA sensors and factors that determine the efficiency of respiratory virus transmission.	IMPImmunology and Molecular Pathogenesis - Full Member MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Lowen	Anice	Infectious Diseases / Agents Virology	Full Member
Dave Lynn, PhD (he/him) Full Member - Biochemistry, Cell and Developmental Biology Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution dlynn2@emory.edu \| Faculty Profile \| Lab Website Asa Griggs Candler Professor, Department of Chemistry, Emory College of Arts and Sciences HHMI Professor, Department of Chemistry, Emory College of Arts and Sciences Rhizosphere/human brain comparisons, symbiotic interactions and neuroscience, intelligent materials and the living/non-living continuum, origins of complex molecular functions.	Rhizosphere/human brain comparisons, symbiotic interactions and neuroscience, intelligent materials and the living/non-living continuum, origins of complex molecular functions.During the last century the view of the living cell as a collection of machines driving metabolic cycles was both developed and rejected, as the layers of cellular diversity and complexity were uncovered. Most remarkable has been our realization that phenomenally complex biological structures are capable of spontaneous self-assembly. From protein folding, to vesicle formation, to the organogenesis of multicellular organisms, a genome clearly encodes not only the information for synthesizing the biological macromolecules, but instructions for their precise 3D self-assembly. Increasingly, genomics and proteomics methods are enabling the large-scale analysis of biological macromolecules such that the energies of supramolecular self-assemblies might now be understood and extended into new materials. Several specific systems are currently being studied: 1. Parasitic angiosperms have developed novel developmental strategies that enable avoidance of host defenses. The molecular basis and evolution of these strategies are studied, 2. Agrobacterium tumefaciens is the only organism that employs lateral gene transfer to eukaryotic cells as a routine adaptive strategy; the molecular basis and evolution of this strategy are of interest, 3. Amyloid diseases, or mis-folding diseases, offer unique opportunities to analyze tertiary and quaternary structure formation. In 2002, I was awarded one of 20 inaugural Howard Hughes Medical Institute Professorships nationwide and pioneered several new educational strategies including science/arts collaborations for communicating science. These efforts culminated with the initiation of the annual Atlanta Science Festival that brought science to over 45,000 people last year and the new Gordon Research Conference on Systems Chemistry.	BCDBBiochemistry, Cell and Developmental Biology - Full Member MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Lynn	Dave		Full Member
Donna L. Maney, PhD Affiliate Member - Neuroscience Affiliate Member - Population Biology, Ecology, and Evolution dmaney@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Psychology, Emory College of Arts and Sciences Rigor and reproducibility in sex variability research; approaches to sex/gender-informed, inclusive biomedical and psychological research	Rigor and reproducibility in sex variability research; approaches to sex/gender-informed, inclusive biomedical and psychological researchI am interested in rigor and reproducibility in the field of sex variability and how it impacts education and public health. A major focus of my work is to investigate how sex differences are tested for and reported in biomedical research. Scientists have a responsibility not only to include females in our studies but also to minimize bias and sexism in the design and the reporting of research. It is therefore a major mission of my lab to promote inclusivity and scientific rigor in the study of sex variability and women's health. Members of my lab collaborate on analyses of extant literature, re-analysis of published data, interviews with investigators, and development of effective training materials for researchers.	NSNeuroscience - Affiliate Member PBEEPopulation Biology, Ecology, and Evolution - Affiliate Member	Maney	Donna	Genetics, Molecular Neuroendocrinology Neuroscience Reproductive Physiology	Affiliate Member
Levi Morran, PhD (he/him) Full Member - Population Biology, Ecology, and Evolution levi.morran@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Biology, Emory College of Arts and Sciences Experimental evolution, mating system evolution, coevolutionary dynamics of antagonistic and mutualistic interactions.	Experimental evolution, mating system evolution, coevolutionary dynamics of antagonistic and mutualistic interactions.Adaptation driven by natural selection is a fundamental mechanism of evolutionary change. However, the underlying selective pressures and genetic underpinnings that shape the evolutionary process within and among populations are not always clear. The primary goal of my research program is to identify and characterize factors that either facilitate or constrain adaptive evolution. I seek to determine the influence of such factors on the genetic architecture and evolutionary trajectory of populations. I utilize experimental evolution coupled with microbiology as a means to test evolutionary theory, which allows me to study the adaptive process in real-time at the phenotypic, genotypic, and genomic levels. My current research explores both coevolutionary dynamics and mating system evolution as factors that influence and potentially dictate the role of adaptive evolution in populations. Coevolution accounts for a significant proportion of the evolutionary change that occurs in nature. My goal is to determine the role that selective pressures derived from reciprocal interspecific interactions play in shaping the genetic composition and evolutionary trajectories of coevolving populations. The nature of these interspecific interactions spans a continuum from highly mutualistic to highly parasitic, and I seek to understand the evolutionary implications of interactions at both ends of the spectrum using several nematode/bacteria systems. My work on mating system evolution utilizes the nematode Caenorhabditis elegans and is built upon a hypothesis-testing framework that is motivated by evolutionary theory. My goal is to understand the widespread maintenance of outcrossing in nature that seems to defy evolutionary theory. My previous work established two selective pressures, both elevated mutation rates and exposure to novel environments (including pathogens), as conditions that can favor outcrossing over self-fertilization. Additionally, my research demonstrated the ability of coevolving pathogens to favor the evolution and maintenance of outcrossing despite the cost of males. This work further established the Red Queen hypothesis as a plausible explanation for the widespread prevalence of outcrossing in nature. I am now working to understand the underlying genetic change and phenotypic evolution that occurred as result of antagonistic coevolution.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Morran	Levi	Disease Genetics, Molecular Microbiology	Full Member
Maya Nadimpalli, PhD (she/her) Full Member - Population Biology, Ecology, and Evolution mnadimp@emory.edu \| Faculty Profile \| Lab Website Assistant Professor, Department of Environmental Health, Rollins School of Public Health I use genomic and epidemiological methods to examine how exposures to animals and the environment can impact human colonization and infection with drug-resistant bacteria.	I use genomic and epidemiological methods to examine how exposures to animals and the environment can impact human colonization and infection with drug-resistant bacteria.Global dietary changes are leading to widespread increases in the amount of antibiotics administered to animals raised for food. My research combines tools from multiple disciplines (environmental microbiology, epidemiology, genomics) to understand the consequences of this practice on the selection and spread of emerging, resistant pathogens to vulnerable human communities, both in the US and across the globe. In addition, I am exploring how behavioral, dietary, and infrastructural interventions could prevent the dissemination of antibiotic resistance in low-resource settings, particularly to young children living in urban informal settlements. In my current position as junior faculty at Tufts University, I was awarded a NIH/NCATS KL2 Career Development award from Tufts' Clinical and Translational Science Institute to investigate the role of the developing gut microbiome in conferring protection against multidrug-resistant pathogens in an urban informal settlement of Lima, Peru. As an Assistant Professor in Environmental Health in the RSPH, my research group will address four main areas: 1. Track the spill-over of antibiotic resistance at the human-animal interface in countries where meat production is increasing most rapidly, with the goals of pinpointing where spill-over is occurring (e.g., in the household, fresh food markets, or along the food chain). Select publications: M. Nadimpalli et al. (2019). Meat and fish as sources of extended-spectrum β-lactamase- producing Escherichia coli, Cambodia. Emerg Infect Dis. 25 (1). 2. Determine how improvements in the built environment – e.g., water, sanitation and hygiene (WASH) services in communities and hospitals; hygiene infrastructure in food markets; and biosecurity measures – might disrupt the circular transmission of pathogens and mobile resistance elements between humans and food- producing animals in low-resource settings. Select publications: M.L. Nadimpalli et al. Drinking water chlorination has minor effects on the intestinal flora and resistomes of Bangladeshi children. In press at Nat. Microbiol. 3. Investigate the role of the developing gut microbiome in conferring protection against multidrug-resistant pathogens in young children living in low-resource settings. I am particularly interested in the role of human milk components and breastfeeding in strengthening (and conversely, the role of formula feeding in potentially weakening) children's gut colonization resistance. Select publication and presentations: M.L. Nadimpalli et al. Breastfeeding reduces children's risk of acquiring ESBL-producing Enterobacteriaceae in an urban informal settlement of Lima, Peru. (2022). Annual Meeting of the Association for Clinical and Translational Science. April 20-22. Chicago, USA. M.L. Nadimpalli, C.D. Bourke, R.C. Roberston, E. Delarocque-Astagneau, A.R. Manges, and A.J. Pickering. (2020). Can Breastfeeding Protect Against Antimicrobial Resistance? BMC Med. 18: 392. 4. Assess whether antibiotic-resistant infections are disproportionately impacting racial/ethnic minority communities in the US and develop innovative strategies to mitigate this. I am currently examining clinical datasets for evidence of disparities and plan to expand this research at Emory by conducting community- based wastewater surveillance of antibiotic-resistant pathogens and resistance genes across socioeconomically diverse neighborhoods in the city of Atlanta (applied for URC pilot funding, January 2022). Select publications: M.L. Nadimpalli, C. Chan, S. Doron. (2021). Antimicrobial Resistance: A Call to Action to Prevent the Next Epidemic of Inequality. Nat Med. 27: 187-188. My research goals at Emory require the application of novel bioinformatics and genomics methods to investigate emerging public health concerns related to antibiotic resistance and One Health. The integration of these tools in public health research is relatively new, but has the potential to fundamentally transform our understanding of health and disease. I am looking forward to mentoring students who are interested in training at this interface. There is substantial overlap between my research interests and expertise both within Emory (e.g., RSPH, Schools of Medicine and Nursing, Emory Antibiotic Resistance Center) as well as at neighboring institutions (e.g., CDC and University of Georgia's Center for Food Safety). I also plan to leverage Emory's longstanding collaborations with Ethiopia, India, and Peru (all of which have recently developed National Antibiotic Resistance Action Plans) to further develop my research program. Collectively, I expect that these synergies will result in unique training opportunities for GDBBS students, both in the United States and internationally. I have previously been funded by the US EPA and the NIH and am leading or collaborating on proposals under review at the NSF, NIH, and internally at Emory (see CV for further information). My future lab on the 6th floor of the Claudia Nance Rollins Building will be equipped to handle BSL 2 level projects and accommodate culture and molecular assays of biological and environmental samples, and I expect to be ready to welcome students by Fall 2022.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Nadimpalli	Maya		Full Member
Ilya M. Nemenman, PhD Full Member - Neuroscience Full Member - Population Biology, Ecology, and Evolution ilya.nemenman@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Physics, Emory College of Arts and Sciences Professor, Department of Biology, Emory College of Arts and Sciences Using methods of theoretical physics and machine learning to develop functional, coarse-grained models of information processing in systems biology.	Using methods of theoretical physics and machine learning to develop functional, coarse-grained models of information processing in systems biology.My group is applying methods of theoretical physics and information theory to understand how biological systems, from molecular circuits, to brains, and to entire populations learn from their surrounding environment and respond to it (we call such phenomena biological information processing, learning, adaptation, memory, or evolution depending on the context). Put simply, often problems solved by such different biological systems are, essentially, the same, while the solution mechanisms are context-dependent. Focusing on the problems, instead of the solutions, reveals general principles underlying biological organization and allows transfer of knowledge across different biological domains.	NSNeuroscience - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Nemenman	Ilya		Full Member
Anne Piantadosi, MD, PhD (she/her) Full Member - Population Biology, Ecology, and Evolution anne.piantadosi@emory.edu \| Faculty Profile Assistant Professor, Department of Pathology and Laboratory Medicine, School of Medicine We study virus emergence, evolution, and pathogenesis using a combination of clinical/translational, laboratory, and computational approaches.	We study virus emergence, evolution, and pathogenesis using a combination of clinical/translational, laboratory, and computational approaches.Overview: Translational viral genomics. The repeated, unpredictable threat of emerging viruses is evident in the spread of known viruses, such as Zika and Ebola, and the identification of new viruses, such as SARS-CoV-2. There is a growing need for clinicians who can recognize syndromes that may suggest emerging viruses and scientists who can use cutting-edge techniques to study them. The field of viral genomic epidemiology lies at a critical intersection of these spaces since it can guide studies of viral discovery, pathogenicity, treatment, and prevention. As a physician-scientist in Pathology and Infectious Disease, I lead a laboratory that investigates the emergence, evolution, and pathogenesis of viruses of public health importance using a combination of clinical/translational, wet lab, and computational approaches. Examples of ongoing projects include: Dengue virus. Dengue is the most common mosquito-borne infection, affecting 400 million people per year, and it encompasses an extremely diverse group of viruses across four serotypes. Disease severity is influenced by a complex interplay between between virus serotype and host pre-existing immunity. To address the hypothesis that similar relationships between virus genotype and host immune response also drive dengue dynamics at the population level, we are investigating dengue virus diversity across space and time in combination with precise immunological profiling to define a virus susceptibility landscape. Tick-borne viruses. We study the emerging tick-borne viruses Powassan virus and Heartland virus through collaborative projects that employ field, molecular, and sequence analysis approaches to understand virus diversity, evolution, and enzootic transmission. Virus detection and discovery using metagenomic sequencing. Metagenomic sequencing is a powerful technique in which all nucleic acid in a sample is sequenced in an unbiased fashion, reads are computationally classified to identify the organisms present, and individual viral genomes are assembled. This approach can be used to detect known viruses and discover new viruses. In parallel with the studies described above, we use metagenomic analysis to identify potential alternative infections in symptomatic patients who screen negative for the virus of interest (e.g. respiratory symptoms without SARS-CoV-2, fever without dengue), and to identify known and novel viruses present in mosquito and tick vectors.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Piantadosi	Anne		Full Member
Steve Qin, PhD Full Member - Population Biology, Ecology, and Evolution zhaohui.qin@emory.edu \| Faculty Profile Professor, Department of Biostatistics and Bioinformatics, Rollins School of Public Health My research interest is on developing statistical and computational methods to analyze complex biomedical data and extract insights from them.	My research interest is on developing statistical and computational methods to analyze complex biomedical data and extract insights from them.With the rapid development of biotechnologies, there is an urgent need for biostatistics and bioinformatics research directed toward extracting and analyzing complex high dimensional and high volume data from these high-throughput technologies. Over the past decade, I have been devoted to establish a probability model-based framework to extract biological insights from messy omics data effectively and reliably. Utilizing state-of-the-art statistical models such as mixture models, hidden Markov models and hierarchical models, I have (i) developed new variations of the above-mentioned classical models, (ii) apply these models to better characterize data produced from high throughput technologies such as next generation sequencing. 1) Statistical model-based methods applied to genomics and epigenomics. My research in genomics is focused on developing probability models and computational algorithms to extract biological knowledge from noisy, high dimensional and high volume data. I am devoted to develop effective and efficient probability models and algorithms for making sense from massive and noisy omics data such that substantial uncertainties in such data are properly accommodated and rigorous statistical inference can be performed. The programs we developed have shown superior performance on real data in multiple performance comparison studies. Most of our methods are explicitly built on probability models such as hidden Markov model (HMM), hierarchical model and mixture model. 2) Statistical model-based methods applied to statistical genetics. Starting from my postdoctoral training, I played a major role in the development of HAPLOTYPER and PL-EM software for haplotype inference. Later I extended the PL-EM algorithm to allow haplotype inference for related individuals. Working with colleagues, I devised an effective software tool FESTA for tagSNP selection using the pairwise LD criterion. Our method has been well-received and extended by other researchers. FESTA has been used in real genetics studies. For example, I applied FESTA to design a SNP panel in a candidate region study of bipolar disorder. 3) Bioinformatics software for integrated analysis of multiple genomics and epigenomics data. Develop effective computational tools to process and analyze biomedical data is a critical component in bioinformatics research. I have focused on computational tool development ever since my postdoctoral training. Through my career, I have developed over 20 computation tools, spanning statistical genetics, genomics and epigenomics. In these computational tools, we have incorporated the novel probability models we have designed for these high throughput omics data. For microarray, we developed CRC (clustering), BEST (query gene expression profile) and IPBT (detect differentially expressed genes). For chip-seq, we developed HPeak (peak calling), ChiP-meta (combined analysis of ChiP-chip and ChiP-seq) and HMS (motif finding). For RNA-seq, we developed POME (quantifying gene expression). For WGBS or BS-seq, we developed Methylphet (predict transcription factor (TF) binding in vivo). 4) Collaborative research on Bioinformatics analysis. I am committed to scientific collaboration. Working with scientists and clinicians to make scientific discoveries and develop novel diagnostics and treatments is perhaps the most important component of the mission of our profession. I have collaborated extensively with biomedical researchers throughout my career. In many such projects, I have been in charge of the data analysis and management (I was second or second from last authors on 15 such papers) and often times, these projects led to the development of new bioinformatics methods. I have collaborated with the Chinnaiyan lab at University of Michigan, where we discovered close cross-talk between transcription factors AR and ERG. Through collaboration with the Dou lab at University of Michigan, we discovered that histone acetyltransferase MOF is a key regulator of the embryonic stem cell core transcriptional network. Through collaboration with the Corces lab at Emory University, we uncovered wide spread chromosomal organization change when cells underwent heat shock.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Qin	Steve		Full Member
Timothy D. Read, PhD Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution tread@emory.edu \| Faculty Profile \| Lab Website Professor, Division of Infectious Diseases, Department of Medicine, School of Medicine Professor, Department of Human Genetics, School of Medicine Using genomics to improve detection of infectious disease pathogens and understand evolution of virulence and antibiotic resistance	Using genomics to improve detection of infectious disease pathogens and understand evolution of virulence and antibiotic resistanceMy research centers on genomics of infectious diseases, focusing on bacterial pathogens such as Chlamydia trachomatis, Staphylococcus aureus and Bacillus anthracis. I use comparative approaches to understand evolution of traits such as virulence and antibiotic resistance phenotypes and develop countermeasures and diagnostics. As a microbial geneticist by training I have a long-standing fascination with the movement of genes between bacteria by lateral gene transfer. As someone who loves genetics in the broadest sense, I also am involved in several projects analyzing microbiome data.	MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Read	Timothy	Antibiotics Genetics, Molecular Microbiology	Full Member
Gonzalo M. Vazquez-Prokopec, PhD Full Member - Population Biology, Ecology, and Evolution gmvazqu@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Environmental Sciences, Emory College of Arts and Sciences To understand the major determinants in the occurrence, transmission and local propagation of major vector-borne and parasitic diseases.	To understand the major determinants in the occurrence, transmission and local propagation of major vector-borne and parasitic diseases.Understanding the transmission, persistence and propagation of infectious agents is an inherently complex task that requires the integration of multiple approaches rooted in different fields of knowledge. I base my research program on the notion that epidemiological outcomes (i.e., the occurrence of human or animal disease) are the result of intricate and complex interactions between hosts, parasites, and environment. By accounting for such complexity, current efforts geared to control infectious diseases of global health significance can be significantly improved. Primary research areas at my lab are disease ecology, vector ecology and spatial epidemiology. In particular, my work aims to understand the major determinants in the occurrence, transmission and local propagation of major urban vector-borne diseases, the contribution of the urban landscape to their patterns of occurrence, the biology and ecology of the insect vectors and reservoir hosts, the contribution of human and vector behavior to the dynamics of pathogen transmission and, particularly, in how to take advantage of such knowledge to improve disease prevention and control.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Vazquez-Prokopec	Gonzalo		Full Member
Nic Vega, PhD (they/them) Full Member - Microbiology and Molecular Genetics Full Member - Population Biology, Ecology, and Evolution nvega@emory.edu \| Faculty Profile \| Lab Website Assistant Professor, Department of Biology, Emory College of Arts and Sciences Physics Graduate Program Affiliate, Department of Physics, Emory College of Arts and Sciences Host-microbe ecology and evolution; antibiotic response; community dynamics modeling	Host-microbe ecology and evolution; antibiotic response; community dynamics modelingThough considerable progress has been made in characterizing the structure and natural variation of microbial communities, despite considerable interest and effort, the forces that create and maintain order and diversity in these communities are still not well understood. Understanding and controlling these forces will be critical for engineering these communities toward a desired composition and function. The Vega lab therefore uses a range of experimental and computational tools to analyze, modify, and control environmental and host-associated microbial communities, to better understand the interactions between microbes, their host, and the environment. One set of projects is focused on understanding and predicting composition and stability of a host-associated microbiome, using C. elegans as an experimental system. This work makes use of the unique advantages of C. eiegans, including ease and rapidity of use and existence of numerous well-characterized mutants, to isolate the factors driving host-microbe interactions. This research integrates laboratory experiments, statistics, and computational modeling to arrive at a systems-level understanding of the ecological and evolutionary factors involved in assembly of stable and unstable host-associated microbial communities. We are additionally interested in the properties of these microbial populations under stresses including antibiotic perturbation and invasion, e.g. in cases of pathogen infection. We have already demonstrated the utility of the C. elegans model for studying bacterial populations during antibiotic treatment, and we are extending this work to study evolution of antibiotic resistance in the host. We have preliminary data indicating that antibiotic response is qualitatively different in the host vs. the in vitro environment; studying the population-wide response to antibiotics and subsequent evolutionary dynamics in the host will provide insights into how host-associated microbial populations respond to antibiotic treatment. Another set of projects focuses on heterogeneity in transmission dynamics of microbes, again using the worm as a tractable model. The high level of control possible in this experimental system allows us to replicate and "copy-paste" transmission events into large numbers of well-controlled susceptible populations, where secondary transmission can be easily measured. These data are useful for model fitting and allow us to explore how heterogeneity in host and microbial populations combines with the inherent stochasticity of transmission events to generate different trajectories in infection chains. In summary, the Vega lab is an interdisciplinary lab where experiments, modeling, and analysis are combined to gain insight into the complex dynamics of microbial systems. This research will make use of a tractable, versatile host system, the nematode worm C. elegans, along with other host and environmental systems as appropriate to the questions being asked. This work will provide unique insights into the ecological and evolutionary dynamics of host-associated microbial systems.	MMGMicrobiology and Molecular Genetics - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Vega	Nic		Full Member
Irwin D. Waldman, PhD Full Member - Population Biology, Ecology, and Evolution psyiw@emory.edu \| Faculty Profile \| Lab Website Professor, Department of Psychology, Emory College of Arts and Sciences Classification, causes, and development of childhood behavior disorders; quantitative and molecular genetic approaches to child psychopathology.	Classification, causes, and development of childhood behavior disorders; quantitative and molecular genetic approaches to child psychopathology.- The classification, development and causes of psychopathology, at both the phenotypic and genetic / genomic levels - Developmental psychopathology, particularly the classification, development and causes of childhood externalizing problems (e.g., hyperactivity, aggression). - Behavioral and molecular genetic studies of developmental psychopathology. - Methodological and statistical issues in studying the development of psychopathology. - Social information processing and social competenece in children. - Behavior genetic, developmental and psychometric aspects of intellectual abilities. Current Projects Underway Use of GWAS of psychopathology in general, and Externalizing disorders and traits in particular, to understand their classification and underlying genetics and biological pathways. Large-scale twin and molecular genetic studies of genetic and environmental influences on childhood externalizing and internalizing behavior problems, their development and their correlated (e.g., studies based in Georgia and in Australia). Studies of fundamental issues in the classification of childhood externalizing disorders (e.g. whether these disorders are categorical or dimensional, the relations and borders among different disorders). Investigation of inattention/impulsivity and social perception in several childhood disorders (e.g. Attention-Deficit Hyperactivity Disorder, Oppositional Defiant Disorder, Conduct Disorder as well as comparisons with internalizing disorders).	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Waldman	Irwin		Full Member
Lance Waller, PhD (he/him) Full Member - Population Biology, Ecology, and Evolution lwaller@emory.edu \| Faculty Profile Professor, Department of Biostatistics and Bioinformatics, Rollins School of Public Health Development of statistical methodology for the analysis of spatially referenced public health data.	Development of statistical methodology for the analysis of spatially referenced public health data.My research involves the development, application, and assessment of statistical methods for the analysis of public health data, with a particular focus on spatial statistics, geographic information systems with applications in disease ecology, public health surveillance, and modeling of infectious disease.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Waller	Lance	Biometry Disease Model Environmental Effects Epidemiology Mathematical Modeling Public Health	Full Member
Daniel B. Weissman, PhD Full Member - Population Biology, Ecology, and Evolution daniel.weissman@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Physics, Emory College of Arts and Sciences DGS, PBEE Theoretical evolutionary biology. What determines the tempo and mode of adaptation? What can we infer from population genomic data?	Theoretical evolutionary biology. What determines the tempo and mode of adaptation? What can we infer from population genomic data?We build and analyze models of biological populations to predict their future evolution. Ultimately, we would like to understand evolution well enough that when, for example, a new antibiotic is developed, a reasonable number of experiments would be enough to learn how long it would take for bacteria to become resistant. This goal is just starting to become realistic due to rapid advances in sequencing technology. Now we need to solve a pair of theoretical problems in order to translate this sequence data into evolutionary predictions. First, we need to understand how to infer prevailing population dynamics from population genomic data---given a set of sequenced individuals, what can we learn about patterns of reproduction, gene flow, and adaptation in the population that they came from? Second, given these patterns, what do we expect the population to do in the future? We work both on pure theory and on a wide variety of organisms, especially viral and bacterial pathogens. Much of current work focuses on recombination and horizontal gene transfer, and the effects of spatial structure and fitness landscapes on adaptation.	PBEEPopulation Biology, Ecology, and Evolution - Full Member	Weissman	Daniel		Full Member
Jingjing Yang, PhD (she/her) Full Member - Genetics and Molecular Biology Full Member - Population Biology, Ecology, and Evolution jingjing.yang@emory.edu \| Faculty Profile \| Lab Website Associate Professor, Department of Human Genetics, School of Medicine My research includes developing statistical and computational methods for quantitative genomics studies, including integrating summary xQTL and GWAS data, differential gene expression analysis, and developing risk prediction models for complex diseases. My research also includes application studies of genetics and genomics data of complex human diseases, such as Alzheimer's disease, breast cancer, and skin toxicity due to radiation therapy.	My research includes developing statistical and computational methods for quantitative genomics studies, including integrating summary xQTL and GWAS data, differential gene expression analysis, and developing risk prediction models for complex diseases. My research also includes application studies of genetics and genomics data of complex human diseases, such as Alzheimer's disease, breast cancer, and skin toxicity due to radiation therapy.Transcriptome-wide Association Study (TWAS) and Proteomie-wide Association Study (PWAS): TWAS (PWAS) has been widely used for integrating reference transcriptomic (proteomic) data with GWAS data for studying complex traits and diseases. Our lab has been working on developing a series of TWAS methods and tools to improve the power of identifying risk genes for complex diseases, and by using only summary-level xQTL and GWAS summary data. Our lab has been working on using TWAS tools to study Alzheimer's dementia and related phenotypes. The study involves statistical modeling, programming, simulation studies, and application studies. Sequence data analysis: In addition to method and tool development, I also work on analyzing the real DNA and RNA data (microarray/sequence/sc-RNAseq) for studying complex traits. The data analysis procedure includes standard quality control, alignment of raw sequence reads, variant calling, quantifying gene expression and methylation, and association study. We also work extensively with single-nucleus RNA-seq, single-nucleus ATAC-seq, and spatial transcriptomic data for studying complex human diseases. Machine Learning and Deep Learning: My lab has also been working on using machine learning and deep learning techniques to develop risk prediction models for complex diseases and analyze biomedical signal and image data. The study involves data analysis, programming, simulation studies, and application studies.	GMBGenetics and Molecular Biology - Full Member PBEEPopulation Biology, Ecology, and Evolution - Full Member	Yang	Jingjing		Full Member