Dr. Dushanka V. Kleinman, D.D.S., MScD
Professor and Associate Dean for Research of UMD SPH

Dr. Dushanka V. Kleinman is the Associate Dean for Research and Professor, Department of Epidemiology and Biostatistics in the University of Maryland School of Public Health. She is a senior science leader at the University of Maryland College Park and in these roles works closely with faculty at the School, University and across the University System campuses to contribute to identifying and supporting proposals for emerging research and research training opportunities. Her recent research interests include prevention of oral health disparities, health literacy, and strategies to integrate oral and general health as well as primary care with public health and social services.

Dr. Boris Lushniak, MD, MPH
Professor and Dean of UMD SPH

Boris D. Lushniak, MD, MPH, RADM (Ret.) is dean of the School of Public Health at the University of Maryland. He has launched a new global health initiative to build and expand the school’s education, research and service activities to improve health across the globe and is also prioritizing “public health action for civic engagement” around issues such as preventing gun violence.

Dr. Lushniak served 27 years in the USPHS, culminating in Deputy Surgeon General (2010-15) and Acting Surgeon General roles (2013-14). He earned bachelor’s and medical degrees from Northwestern University and a master of public health from Harvard University.

Headshot of David Broniatowski

Dr. David Broniatowski, PhD                                                                                Associate Professor, Engineering Management & Systems Engineering, GWU

Professor David Broniatowski conducts research in decision-making under risk, group decision-making, system architecture, and behavioral epidemiology. This research program draws upon a wide range of techniques including formal mathematical modeling, experimental design, automated text analysis and natural language processing, social and technical network analysis, and big data. Current projects include a text network analysis of transcripts from the US Food and Drug Administration's Circulatory Systems Advisory Panel meetings, a mathematical formalization of Fuzzy Trace Theory -- a leading theory of decision-making under risk, derivation of metrics for flexibility and controllability for complex engineered socio-technical systems, and using Twitter data to conduct surveillance of influenza infection and the resulting social response.

Dr. Lisa Singh, PhD                                                                                                Professor, Computer Science, Georgetown University

Dr. Lisa Singh is a Professor in the Department of Computer Science at Georgetown University. Broadly, her research interests are in data-centric computing – data mining, data privacy, data science, data visualization, and databases. She has authored/co-authored over 50 peer reviewed publications and book chapters. With ISIM, LLNL, York University and other NGOs she works on understanding different ways to use big data to better understand movement patterns of forced migration. Some of her other interdisciplinary projects include studying privacy on the web (adversarial inference), dolphin social structures with the Shark Bay Dolphin Research project (graph inference and social mining using incomplete and uncertain data), and learning from open source big data for social science research related to public opinion, election dynamics, and child behavior. Dr. Singh's research related to the 2016 election has been cited by the Huffington Post, CNN, and the Hill. Dr. Singh has also helped organize three workshops involving future directions of big data research, has served on numerous organizing and program committees, and is currently involved in different organizations working on increasing participation of women in computing and integrating computational thinking into K-12 curricula. 

Quynh Nguyen Headshot

Dr. Quynh Nguyen, PhD                                                                                         Assistant Professor, Epidemiology and Biostatistics, UMD

Dr. Quynh Nguyen is a social epidemiologist focusing on contextual and economic factors as they relate to health. She has extensive experience using numerous national and international population-based health surveys to examine social and economic predictors of health, and to quantify national and international patterns in health disparities. Her current research program focuses on creating and validating neighborhood indicators constructed from nontraditional Big Data sources such as social media data. She is principal investigator of two NIH K-award career development grants through the Big Data to Knowledge Initiative (BD2K) to pursue this research program (K01ES025433; K01ES025433-03S1). She has been recently awarded an R01 grant from the National Institutes of Health (NIH)/National Library of Medicine for her project titled, “Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects Research.”

Photo of Mihai Pop

Dr. Mihai Pop, PhD
Professor and Director of Institute for Advanced Computer Studies (UMIACS)

Dr. Pop received his Ph.D. in Computer Science at Johns Hopkins University where he focused on algorithms for computer graphics and Geographic Information Systems (GIS) applications. He then joined The Institute for Genomic Research (TIGR) as a Bioinformatics Scientist, where he was responsible for the development of genome assembly algorithms. During this time, Dr. Pop participated in a number of bacterial and eukaryotic genome projects including important human pathogens such as Bacillus anthracis and Entamoeba hystolitica. Since joining the University of Maryland, Dr. Pop has continued to develop novel approaches for genome assembly and analysis, and has developed extensive expertise in the analysis of metagenomic data. His lab has developed a number of widely used open-source software tools, such as the assembly suite AMOS, the NGS aligner Bowtie, the taxonomic classifier Metaphyler, and the metagenomic assembly package MetAMOS. Most recently he co-led the data analysis working group for the Human Microbiome Project and led the sub-group responsible for the assembly of the data generated in this project. In the context of pathogen detection and identification, Dr. Pop was a key member of the team that analyzed the Bacillus anthracis strains used in the biowarfare attack from 2001, helping to develop the diagnostic test that ultimately helped to identify the source of the attack strain.

George C Tseng

Dr. George Tseng, ScD                                                                                         Professor, Biostatistics, Human Genetics, Computational & Systems Biology, University of Pittsburgh

Dr. George Tseng is Professor in the Departments of Biostatistics, Human Genetics, Computational and Systems Biology in the University of Pittsburgh Graduate School of Public Health. He received BS (1997) and MS (1999) in Mathematics from the National Taiwan University, and ScD (2003) in Biostatistics from Harvard School of Public Health under Dr. Wing Hung Wong's lab. He has joined Pitt since 2003 and leads a research lab in Bioinformatics and Statistical Learning. His research interests focus on statistical modeling and applications for genomic and bioinformatic problems to improve precision medicine and human health. Dr. Tseng has published 150+ papers, 5 patents and received multiple awards, including ASA Fellow, Statistician of the Year (ASA Pittsburgh Chapter) and Provost's Award for Excellence in Mentoring (University of Pittsburgh). Collaboration with biological and clinical labs plays an important role where most of his projects and methodological ideas come from. Lab Homepage.

Daniel O. Scharfstein

Dr. Daniel Scharfstein, ScD                                                                                  Professor, Biostatistics, Johns Hopkins University

Dr. Scharfstein’s research is focused on how to draw inferences about treatment effects in the presence of selection bias. Specifically, he is interested in how to report results in randomized trials with informative missing or censored data and in observational studies with non-random treatment assignment. He served on the National Academy panel, which issued the report The Prevention and Treatment of Missing Data in Clinical Trials. He is the principal statistician of the METRC consortium, which is funded by the Department of Defense to conduct multi-center clinical research relevant to the treatment and outcomes of orthopaedic trauma sustained in the military. He have also served as the lead statistician on a number of large evaluation studies including the National Study of the Costs and Outcomes of Trauma (NSCOT), Guided Care for Chronically Ill Older Adults and Healthy Steps for Young Children.

Jie Chen UMD

Dr. Jie Chen, PhD                                                                                                  Associate Professor, Health Policy and Management, UMD

Dr. Jie Chen is an Associate Professor in the Department of Health Services Administration at the School of Public Health, the University of Maryland at College Park. Dr. Chen’s research fields include health care disparities, health care delivery system and policy, behavioral health, aging, and economic evaluation.  Her work uses a multidisciplinary perspective and involves collaboration with clinical leaders, community partners, and organizational decision makers. Her current research focuses on the integration of healthcare organizations, promoting behavioral health of vulnerable populations and mental health among older adults. Dr. Chen is also interested to study the impact of health policy initiatives and changing economic conditions on health care access, utilization, and health disparities. An additional field of her research involves economic evaluation, including cost-effectiveness and cost-benefit analysis of community intervention and state/federal policies. Dr. Chen has more than fifteen years of research experience developing, refining, and applying analytical methods to evaluate the impact of health policy and the health care delivery system on population health outcomes.

Peter Kochunov

Dr. Peter Kochunov, PhD                                                                                     Professor, Psychiatry, UMB

Dr. Kochunov is a board-certified MRI physicist with over two decades of experiences in development of novel data analysis protocols with emphasis on the quantitative, multimodal analyses of genetic factors that are responsible for structural and functional variability. Dr. Kochunov has a background in neuroimaging, electrical engineering, software development and statistics. Dr. Kochunov has participated in development of many popular neuroimaging tools and formats including SOLAR-Eclipse, ENIGMA-Viewer, ENIGMA-DTI and ENIGMA-rsFMRI analyses pipelines, Talairach deamon, BrainMap, Mango and BrainVisa Morphologist, NFITI and others. Dr. Kochunov's research is described in over 150 scientific manuscripts, including some of the first manuscripts on heritability of white matter integrity, gray matter thickness, resting-state connectivity and others.

Shuo Chen

Dr. Shuo Chen, PhD                                                                                              Associate Professor, Epidemiology & Public Health, UMB                                        Director of Biostatistics and Data Science, at Maryland Psychiatric Research Center

Dr. Chen is a biostatistician with a research focus on modeling large biomedical data with complex and organized, yet latent interactive relationship. He develops novel machine learning and Bayesian models for brain connectivity network (neuroimaging), omics, and social network data. Dr. Chen also has extensive experience of biostatistical collaborative research in the areas of clinical trial design and analysis, environmental health, infectious disease, and cancer research.

Sherinne Eid

Ms. Sherrine Eid                                                                                                          Global Head Real-World Evidence and Epidemiology/Biostatistics, SAS Institute Inc. 

Sherrine began her career nearly 20 years ago in Monitoring and Evaluation on global health projects funded by USAID, CDC and GtZ and KfW. Sherrine served as the District Epidemiologist for the City of Alexandria, Virginia where she was responsible for managing outbreak investigations, Syndromic Surveillance Programs and the Epi Response Team in the City of Alexandria and the National Capitol Region.  Following this, she worked as the Network Epidemiologist and Biostatistician for Lehigh Valley Health Network for 10 years and served on the Board of the Allentown Bureau of Health.  Sherrine moved on to Teva Pharmaceuticals where she was an Associate Director Epidemiologist and Biostatistician supporting Global Medical Affairs, Global Scientific Communications and Health Economics and Outcomes Research as well as Pharmacovigilance and Research and Development using RWE.