Team

Dr. Apathy is an Assistant Professor of Health Policy & Management. His research sits at the intersection of health policy, health services research, and health informatics. He studies the role of health information technology in supporting delivery and payment reform efforts, the impact of regulations on health IT innovation, adoption, and use, and he specializes in using system‑generated log data to deepen understanding of health IT’s impact on care quality. His current research focuses on sources of IT‑based burden and organizational strategies to reduce that burden.

nca@umd.edu

Dr. Baghdadi is an infectious disease physician, hospital epidemiologist, and health services researcher at the University of Maryland Medical Center – Midtown Campus. His clinical interests are infection prevention, antimicrobial stewardship, and early sepsis care. His research interests are diagnostic quality and safety, including diagnostic stewardship and diagnostic error.

jbaghdadi@som.umaryland.edu

Dr. Beckett is a computational ecologist and quantitative biologist whose research focuses on the dynamics and ecology of viruses. In particular, his research into marine microbial ecology, network science, and infectious disease dynamics is driven through the development and use of mathematical models, computational methods, and software development. Dr. Beckett is an advocate for increasing access and transparency in science – both through Open Science practices and science communication.

beckett@umd.edu

Dr. Bergman develops agent-based and mathematical models to investigate tumor-immune dynamics at the cell and tissue scale. His research integrates multiomics data to ground simulations in biological reality, with the goal of informing therapeutic interventions and advancing precision oncology.

My research first explored this question in different biogeographical regions ranging from the Central Andes to the African Great Lakes. During the last few years, I have combined different fields (archaeology, anthropology, and genetics) in order to answer the question: How have evolutionary and demographic factors shaped the present-day genetic diversity of human populations?.

I have explored Native American genetic diversity and identified signals of ancient gene flow across the Andean region, which were associated with cultural interaction between groups from the Highland and Amazonian regions. Currently, I am incorporating several statistical genetic analyses to understand the recent dynamics of Latin American populations. From this point, I believe that by investigating the history of these groups, we can start to understand the architecture of complex phenotypes and work towards eliminating disparities, and also understand the diversity that makes us human.

Michel Boudreaux is an Associate Professor in the Department of Health Policy and Management. He conducts research in interrelated areas of health policy. He is especially interested in public programs for low-income populations and their effects on health and economic well-being.

mhb@umd.edu

Dr. Breman’s work is aimed at improving care for individuals throughout pregnancy, labor, and birth via improved communication and respectful maternal care and by using a lens of reproductive justice as a guide. 

rbreman@umaryland.edu

Jordan Broutman is the Director of Development for the University Corporate Relations (UCR) office. He works on strengthening and expanding campus-wide strategic corporate partnerships and works with colleagues across the University and EIC ecosystem. The UCR office is responsible for expanding corporate gifts and grants that provide critical support to graduate education, faculty research, and priority campus initiatives such as AI and Quantum. The UCR office is based in the Division of University Relations and partners closely with the Research Development office in the Division of Research. 

jbrout@umd.edu

Dr. Brown is a biostatistician and Associate Professor in the Department of Epidemiology and Public Health.  He is also the Director of the Biostatistics Unit in the V.A. Capitol Healthcare Network MIRECC (Mental Illness, Research, Education and Clinical Center).  He collaborates with a wide range of scientists and clinician investigators in medicine, epidemiology, health services, and behavioral interventions research.  

clbrown@som.umaryland.edu

Dr. Chixiang Chen is an Associate Professor in Biostatistics and a NIH-funded principal investigator. Dr. Chen has worked across both theoretical and applied areas of statistics, also has extensive interdisciplinary collaborations including clinical trial design and analysis in neuroscience, Medicare claims data, electronical health records, imaging data analysis, and oncology research. Dr. Chen is devoted to advancing statistical methods in large-scale observational studies and real-world data, encompassing diverse areas including causal inference, data integration, unsupervised clustering, longitudinal data analysis, missing data analysis, and biological age.

chixiang.chen@som.umaryland.edu

Dr. Jie Chen is Professor and Chair of the Department of Health Policy and Management at the University of Maryland School of Public Health and Director of the UMD Center on Aging. She leads SUNSHINE, an NIH-funded national aging resilience center supported through the NIA DECC P30 program, and has established a robust NIH-funded research program in aging, health systems, and the use of artificial intelligence to strengthen system performance and support aging populations. With more than 200 scholarly publications, Dr. Chen’s work spans health economics, aging health, dementia care, and integrated care systems. Her recent research incorporates artificial intelligence to examine system resilience, support caregivers, improve Medicare and cost outcomes, and strengthen aging and dementia care. Her interdisciplinary, systems-oriented approach advances impactful solutions that support healthy aging and resilient communities.

jichen@umd.edu

Dr. Chen is an MPower Professor of Biostatistics and Bioinformatics. His research focuses on modeling complex structured biomedical data, including spatiotemporal dependence in neuroimaging, linkage disequilibrium in genetics, co-expression graph structures in omics, and group-level graph edge inference. He is also involved in developing machine learning models for individual-level inference, considering complex dependencies between high-throughput features. Dr. Chen has broad experience in collaborative biostatistical research, including clinical trials, environmental health, infectious disease, and cancer research.

A widely recognized oncologist with a specialty in head and neck cancer, Dr. Cullen is a former director of the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center. At the Center, which is ranked as one of the nation’s top cancer programs, Dr. Cullen oversaw a staff of 275 physicians and researchers. Under his leadership, the cancer center expanded its clinical and research programs significantly and was named a National Cancer Institute-designated cancer center in 2008. During his tenure, the Center received more than $61 million in research funding annually and hosted over 230 clinical trials.

Dr. Cullen’s own laboratory examines the mechanisms of chemotherapy resistance in head and neck cancer. Specifically, his group has demonstrated that specific biochemical markers are important predictors of response to the chemotherapy drug cisplatin in head and neck tumors—and that those same markers also predict the disease prognosis. His team was also the first to describe racial survival disparities in head and neck cancer. In 2011, he was appointed by President Obama to a five-year term as a member of the National Cancer Advisory Board, an advisory committee to the National Cancer Institute. He has been chosen to serve as chairman of the Board of the American Cancer Society.

Warren D. D’Souza, PhD, MBA, is Professor and Division Head, Medical Physics in the Department of Radiation Oncology. He joined the faculty as Instructor at the University of Texas M.D. Anderson Cancer Center in 2000. He came to the Department of Radiation Oncology at the University of Maryland School of Medicine in 2002 as Assistant Professor. He was promoted to Associate Professor and appointed as Division Head of Medical Physics in 2008. In 2014, he was promoted to Professor. He is the recipient of several awards, including the Medical Physics Travel Award from the American Association of Physicists in Medicine. He holds six patents from the United States Patent Office. He has been funded as a principal investigator on multiple grants from the National Institutes of Health, National Science Foundation and through various industry sponsored grants. He became a Fellow of the American Association of Physicists in Medicine in 2015.

Dr. Davis is a board-certified family physician with more than 20 years of clinical expertise in the acute and chronic management of adults and children. In addition, she is a widely published, NIH-funded clinical researcher, whose efforts focus on obesity-related maternal and child health outcomes and in comparative effectiveness research in maternal health and tobacco use disorder.

Much of her work has focused on understanding the perinatal determinants of obesity, maternal health inequities and long-term cardiovascular health in women. She has contributed to the field specifically by investigating the perinatal, cultural, and behavioral factors associated with the racial and socioeconomic inequities in obesity among women that have persisted for decades.

Dr. Christopher deFilippi is a Professor of Medicine (Division of Cardiology) and Pathology at the University of Maryland School of Medicine. His career has been distinguished by a sustained focus on the discovery, validation, and clinical application of cardiac biomarkers. He has authored more than 300 peer-reviewed publications and has received funding from the NIH and the in vitro diagnostics (IVD) industry to lead biomarker-based clinical trials across the spectrum of cardiovascular disease.

Over the past 25 years, Dr. deFilippi has collaborated extensively with the IVD industry, contributing to the development of multiple FDA-cleared assays and co-authoring pivotal publications that have shaped biomarker use in clinical practice. He has led the design of numerous diagnostic clinical trials and has served as chairperson for adjudication and endpoint committees supporting FDA registration studies.

To further strengthen his expertise in study design and high-dimensional data analysis, Dr. deFilippi recently completed a Master of Science in Clinical Investigation at Harvard Medical School. His current research integrates discovery-based proteomics to identify circulating protein biomarkers that serve as effect measure modifiers, enhancing precision in treatment response across diverse patient populations.

Dr. deFilippi rejoined the University of Maryland following his tenure at the Inova Health System, where he established and directed a successful biomarker core laboratory. His return marks a continuation of a long-standing collaboration with Dr. Robert Christenson, with whom he previously worked for more than 15 years in advancing translational biomarker science.

Florence (Flo) Doo, M.D., M.A., CIIP, is an abdominal radiologist, clinical informaticist, and physician innovator.

Dr. Doo is an Assistant Professor and serves as Director of Innovation at the University of Maryland Medical Intelligent Imaging (UM2ii) Center in the Department of Diagnostic Radiology & Nuclear Medicine at the University of Maryland School of Medicine, and also co-leads the AI-enabled Medical Imaging research group in the Applied AI Research Center at the University of Maryland Institute for Health Computing (UM-IHC).

Dr. Doo’s expertise spans clinical radiology, imaging informatics, AI-driven healthcare innovation, and entrepreneurship. She has held local and national leadership positions with prominent medical societies such as the Radiological Society of North America (RSNA), the American College of Radiology (ACR), and the Society for Advanced Body Imaging (SABI). Dr. Doo also serves as the Vice President of Artificial Intelligence in Radiology Education (AIRE) which provides free AI literacy education, and also serves on Board of Governors of the RadDiscord online educational community. She is a recipient of multiple awards, including the RSNA Roentgen Resident/Fellow Research Award, Alpha Omega Alpha (AOA) medical honor society induction, the American Board of Radiology Volunteer Service Award, Outstanding Mentor (for Transformative Impact) at the UMB 48th annual Medical Student Research Day, and recognition as a semifinalist/finalist for Most Influential Radiology Researcher by AuntMinnie.com (“Minnies,” in both 2024 and 2025).

Dr. Doo has authored over 40 peer-reviewed publications*, addressing the intersection of medical imaging, climate impacts on health care delivery, and responsible implementation of AI in clinical practice. Her work is currently funded through several prestigious career development and research grants, including the Association of Academic Radiologists Clinical Effectiveness in Radiology Research Academic Fellowship (AAR CERRAF, a foundation career development award suppoerted by GE Healthcare), the UMMC Innovation Challenge award (for development of a large language model clinical data chatbot), the Mid-Atlantic Center for Cardiometabolic Health (MACCH, a Johns Hopkins NIH MHHD P50 Center) project grant, and the Johns Hopkins – University of Maryland Baltimore ICTR/NIH CTSA K12 mentored career development grant award.

Her research program focuses on translating technologies to improve clinical patient care, with a focus on safe/trustworthy and sustainable applications of AI and informatics tools.

Najib El-Sayed is a professor of cell biology and molecular genetics with an appointment in the University of Maryland Institute for Advanced Computer Studies.

His research uses genomic and bioinformatics tools to study parasitism and host-pathogen interactions, aiming to understand infection and survival mechanisms. Ultimately, he seeks to enhance the diagnosis, prevention and treatment of diseases caused by parasites and bacteria in humans, animals and plants.

Cornelia Fermüller is a research scientist in the UMIACS Computer Vision Laboratory.

Fermüller’s research is in the areas of computer vision and human vision, and she has written more than 35 articles in journals and 100 publications in refereed conferences and books. In her computer vision work, she has developed many computational models and implemented software solutions for applications in visual navigation and image processing. Fermüller’s work on biological vision involves examining the computational constraints, building simulation models, and performing psychophysical experiments to understand the possible computational mechanisms explaining human motion and low-level signal perception.

Many of her studies have been investigating the computational principles underlying multiple view geometry and statistics, and she has discovered a number of basic computational principles in the analysis of visual motion and shape recovery. These include view-invariant texture descriptors, constraints on 3-D motion estimation, 3-D shape and image segmentation, insights on the effects of sensor design on motion estimation, and the findings of statistical bias in low-level processing.

Fermüller has applied these studies in a number of applications, including new imaging sensors for better motion and shape recovery, software for visual motion tasks in navigation and robotics, and various tasks of video computing, such as compression, video manipulation, and image-based rendering.

Her current research interests are centered around developing cognitive robotic systems that integrate, perception with action, reasoning and language. In ongoing projects she develops robots that recognize human manipulation activities and search for an object in a room.

She received a doctorate from the Technical University of Vienna, Austria in 1993 and an M.S. from the University of Technology, Graz, Austria in 1989, both in applied mathematics.

Dr. Fertig advances a new predictive medicine paradigm for oncology by converging systems biology with multi-omics technology development. Her computational cancer biology research is inspired by her background as a NASA fellow in weather prediction. She aims to invent computational techniques that blend multi-platform high-throughput with mechanistic mathematical modeling and artificial intelligence methods to forecast the cellular and molecular pathways of tumor progression and therapeutic response over time. Her combined expertise in computational oncology, chaos theory, nonlinear dynamics, and tumor immunotherapy ensures translational relevance and mechanistic validation of computational findings. Dr. Fertig has been a leader in establishing spatial multi-omics technologies, matrix factorization, and transfer learning as current mainstays in bioinformatics. Beyond algorithm development, Dr. Fertig’s transdisciplinary expertise enables her to lead large-scale, team-science projects, adapting cutting-edge molecular profiling technologies to human biospecimen research and clinical trials to uncover new therapeutic interception pathways. Beyond the lab, she is a recognized leader in developing new training paradigms that converge oncologists, pathologists, basic biologists, computational investigators, and engineers to advance the next generation of computationally-driven cancer research.

In December, 2024 Dr. Fertig was named the Director of the Institute for Genome Sciences and the Dean E. Albert Reece Endowed Professor in the School of Medicine at the University of Maryland School of Medicine after a nationwide search; and Associate Cancer Center Director of Quantitative Sciences at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center at the University of Maryland, Baltimore. Prior to joining the faculty of the University of Maryland, she was a Professor of Oncology and Division and Associate Cancer Center Director in Quantitative Sciences and Co-Director of the Convergence Institute at Johns Hopkins University. Prior to entering the field of computational cancer biology, Dr Fertig was a NASA research fellow in numerical weather prediction as a graduate student in Applied Mathematics and Scientific Computation at University of Maryland, College Park. Dr. Fertig’s research is featured in over numerous peer-reviewed publications, open-source software packages, and competitive funding portfolio as PI and co-I. She was elected to the College of Fellows American Institute for Medical and Biomedical Engineering (AIMBE) in 2022, serves on the editorial boards of Genome Medicine, Cell Systems, Clinical Cancer Research, and Cancer Research Communications, and as co-chair of the AACR Data Science Task Force.

My research applies novel informatics and machine learning/AI methods, including natural language processing (NLP) and large language models (LLMs), to large electronic health record and claims data. These projects span multiple clinical domains, from infectious diseases to oncology to maternal-fetal medicine, with a particular interest in improving the screening and diagnosis of antimicrobial resistance gut carriage and early-onset colorectal cancer.

Prior to my doctoral studies, I practiced FDA law in Washington, D.C., and the intersection of law and public health remains an important research interest. With collaborators across the School of Medicine and the School of Law, we have ongoing work focused on the legal regulation and oversight of clinical algorithms and emerging AI technologies.

Rebecca Gourevitch is an Assistant Professor in the Department of Health Policy and Management. She is a health services researcher using quantitative methods to study policies that impact access to affordable, high quality health care in the United States. Her work focuses on how to improve care and social support services for pregnant and postpartum individuals.

I am a Distinguished University Professor and The Michael and Eugenia Brin Endowed E-Nnovate Chair in Mathematics at the Department of Mathematics, University of Maryland, College Park. My research work focuses on using mathematical approaches (modeling, rigorous analysis, and data analytics) to gain insight and provide understanding on the transmission dynamics of emerging and re-emerging infectious diseases of public health significance. Specifically, I design, analyze, parameterize, and simulate novel models for the transmission dynamics and control of emerging and re-emerging infectious diseases. My research also involves the qualitative theory of nonlinear dynamical systems arising in the mathematical modeling of phenomena in population biology (ecology, epidemiology, immunology etc.) and computational mathematics (with emphasis on the design of robust numerical methods that give results that are dynamically-consistent with the governing continuous-time model being discretized). The ultimate objective of my research work, in addition to the development of advanced (and perhaps novel) mathematical theory and methodologies for studying nonlinear dynamical systems arising in population biology, is to contribute to the development of effective public health policy for controlling and mitigating the burden of emerging and re-emerging infectious diseases.

Junfeng Guo is a postdoctoral associate at the University of Maryland Institute for Advanced Computer Studies (UMIACS) working with Heng Huang. He conducts research at the intersection of deep learning, computer vision and privacy and security. Guo’s ongoing work focuses on making AI systems more practically usable through improving their security assurance, privacy preservation and predictability.

Dr. Harris is an infectious disease physician and epidemiologist whose research interests include emerging pathogens, antimicrobial-resistant bacteria, hospital epidemiology/infection control, epidemiologic methods in infectious diseases and medical informatics. He has published over 280 papers. He has current or has had funding from the NIH, CDC and AHRQ to study antibiotic resistance and hospital epidemiology. He is extremely proud of his mentoring track-record.

Dr Amal Isaiah graduated from St. John’s Medical College in Bangalore, India. He was elected a Rhodes Scholar in 2006, following which he completed a DPhil (PhD) in Neurophysiology at Oxford University, England, focusing on developmental plasticity associated with cochlear implantation. Dr Isaiah then completed residency training in Otolaryngology at University of Maryland, and a clinical fellowship in Pediatric Otolaryngology at University of Texas Southwestern Medical Center/Children’s Health Dallas. He is certified by the American Board of Otolaryngology in Otolaryngology-Head and Neck Surgery and Complex Pediatric Otolaryngology. 

Dr Isaiah’s clinical interests include ear, nose and throat disorders in infants and children with focus on sleep disorders, airway-related problems, ear infections and hearing loss. With over 70 peer-reviewed publications, 7 book chapters, 5 patents, and numerous national and international presentations, Dr Isaiah leads a productive research group investigating brain outcomes of pediatric sleep disordered breathing. He is funded by an R01 research grant from the National Institutes of Health/the National Heart Lung Blood Institute. His work in this area has received international attention. 

Joseph JaJa holds a joint appointment in the Department of Electrical and Computer Engineering, and the University of Maryland Institute for Advanced Computer Studies (UMIACS). He received his Ph.D. in Applied Mathematics from Harvard University in 1977. Dr. JaJa has published extensively in a number of areas including parallel and distributed computing, combinatorial optimization, algebraic complexity, VLSI architectures, machince learning, and data science. He has received numerous awards including the IEEE Fellow Award in 1996, the 1997 R&D Award for the development of software for tuning parallel programs, and the ACM Fellow Award in 2000, . He served on several editorial boards, and is currently serving on the advisory boards for several conferences and workshops.

Dr. Keller received his Bachelor of Science degree in Biology from Villanova University, his Master of Science degree in Biomedical Science from Florida Atlantic University, and Doctor of Medicine degree from the University of Miami. He completed residency training at Johns Hopkins Hospital in internal medicine, and then completed a fellowship in Critical Care Medicine at the NIH and fellowships in Pulmonary and Critical Care Medicine and Transplant Pulmonology at Johns Hopkins Hospital. He is actively board certified in Internal Medicine and Pulmonary and Critical Care Medicine.

As an NIH-funded physician-scientist, Dr. Keller’s research work focuses on advanced lung disease and lung transplantation. Dr. Keller values the concept of the bench-to-bedside approach inherent to translational research, applying novel cutting-edge technologies to the clinical realm to advance the field of lung transplantation and critical care medicine. His laboratory focuses on novel methods of evaluating and defining various post-transplant complications. Dr. Keller’s lab employs a multimodality approach that integrates novel molecular assays, advanced bronchoscopic techniques and comprehensive pulmonary function testing techniques to better understand the pathophysiologic mechanisms of post-transplant lung allograft dysfunction. His work has established donor-derived cell free DNA (dd-cfDNA) as a molecular biomarker of allograft injury and has revealed the potential of dd-cfDNA to detect, better quantify and risk stratify various post-transplant complications, including acute cellular and antibody-mediated rejection.

Dr. Keller also values his role as an educator and has a strong passion for teaching the next generation of physicians to become strong clinicians and physician-scientists. He serves as Local Site Director of the Mid-Atlantic Mechanical Ventilation Course, Educational Consortium. He has a passion for medical education and has authored articles on complex topics in mechanical ventilation as well as the impact of dedicated mechanical ventilation courses on trainee competence and retention of knowledge.

Dr. Kheirbek is a Professor of Medicine and the inaugural Division Head of Gerontology, Geriatrics, and Palliative Medicine at the University of Maryland School of Medicine in Baltimore, Maryland. She is board-certified in Internal Medicine, Geriatric Medicine, and Hospice and Palliative Medicine.

Dr. Kheirbek’s primary focus is on developing and implementing quality improvement programs for older adults with serious and advanced illnesses. Her research portfolio includes numerous large-scale projects with a particular focus on the oldest segment of the global population. Her interest in centenarians originated from caring for a 108-year-old patient and led her to assemble the world’s largest cohort of male centenarians. Through conducting interviews with over 100 centenarians, Dr. Kheirbek gained valuable insights into their exceptional longevity.

In addition to her research work, Dr. Kheirbek plays a vital role in training numerous learners on age-appropriate, person-centered care. She currently serves as the Program Director of the Geriatric Fellowship at UMD, where she fosters empathy, reflection, and professionalism in the practice of medicine. Her dedication to educating future healthcare professionals ensures that they are equipped with the necessary skills to provide compassionate care to older adults.

Dr. Kheirbek is an advocate for social justice. She actively writes and provides expert testimonies, addressing the unique needs of marginalized and medically vulnerable individuals, including elders in the criminal justice system, advocating for compassionate and geriatric release of prisoners. Her work has been featured in several publications, including the Baltimore Sun, New York Times, Washington Post, and US World and News Report.

I am a PhD student at the University of Maryland, College Park, and a Graduate Research Assistant at the University of Maryland Institute for Health Computing (UM-IHC), advised by Dr. Heng Huang. My research is primarily focused on the intersection of machine learning, computer vision, and medical imaging, with the goal of enabling opportunistic screening and early-stage disease detection in everyday clinical practice. I am currently interested in multi-modal models that integrate imaging, clinical, and multi-omics data for clinical decision-making, as well as trustworthy and explainable AI systems that adapt to distribution shifts over time, align with nuanced human feedback, and mitigate algorithmic bias. In my free time, I enjoy hiking, gardening, and reading about history, biogeography, and urban planning.

Dr. Li joined the University of Maryland, College Park as a tenure-track Assistant Professor in Aug. 2023. During the deferral time before joining, he was a research associate at Qualcomm AI Research.

Dr. Li received his Ph.D. in 2022 from the Department of Electrical and Computer Engineering (ECE) at Duke University. Li has also earned a Ph.D. in Computer Science from the University of Arkansas. He has an MS in Management of Innovation and Venture Capital from Peking University, and a BS in Computer Science from Henan University in China.

His research interests lie in the intersection of machine learning and edge computing, with a focus on building large-scale networked and trustworthy intelligent systems to solve practical problems in a collaborative, scalable, secure, and ubiquitous manner. Dr. Li has been recognized with a variety of awards, including the IEEE TCCPS Outstanding Ph.D. Dissertation Award, ACM KDD Best Student Paper Award in 2020, and the 2022-2023 Duke ECE Department Outstanding Dissertation Award.

Anup Mahurkar is the Executive Director of Software Engineering & Information Technology at IGS. Anup has extensive experience in the fields of genomics and health sciences and has worked as a researcher, engineer, and manager for the past 16 years overseeing the work of scientists, managers, engineers, and IT professionals in research environments. At IGS, Anup is responsible for development of software tools and analysis systems for genome sequencing, assembly, annotation, and gene expression. Anup is also responsible for the development of the IT infrastructure necessary to support the high-throughput sequence generation and analysis. His areas of expertise include bioinformatics tool development, large scalable analysis systems, database design, and high throughput computing architecture and application development. Prior to joining IGS in July 2007, Anup was the Director of Software Engineering at TIGR/JCVI.

Anup has directed a number of open-source projects at IGS and TIGR/JCVI that include PANDA (protein and nucleotide data archive), Workflow, Manatee, Pathema, Gemina, and BRC Central. PANDA is a system built to perform taxonomy based protein clustering used extensively at TIGR/JCVI and IGS to improve microbial and eukaryotic annotation. Workflow is a pipeline execution and management system central to the development of analysis pipelines in use at JCVI, Camera (UCSD), and IGS. This tool has also been deployed at other bioinformatics research institutions worldwide. Some applications have been used extensively in high profile scientific research including the analysis of the Sargasso Sea metagenomic data at TIGR/JCVI. His contributions to web projects such as Pathema and BRC Central include the design and development of a 3-tier architecture that has allowed these tools to be made portable to many different database systems including Sybase, MySQL, and PostgreSQL. He has extensive experience in assembly and closure and helped build TIGR’s sequence editing tool Cloe, automated closure tool, AutoCloser, and assembler pipeline CARun. In addition, Anup built TIGR’s second-generation laboratory information management system (LIMS), Tracker, and was instrumental in the acquisition and deployment of a LIMS system at IGS.

Bradley Maron is the Co-Executive Director of the University of Maryland Institute for Health Computing (UM-IHC) and is the Senior Associate Dean for Precision Medicine at the University of Maryland School of Medicine. He is the incoming Editor-in-Chief of the American Heart Association flagship journal Circulation.

Dr. Maron is a recognized physician-scientist in the rapidly growing fields of precision medicine, network medicine, and computational data analysis. Currently, he is engaged as the Co-Principal Investigator in an ongoing study entitled, “Network Medicine and Systems Pharmacology to Advance Precision Medicine in Combined Pulmonary Hypertension,” and a second, as the Principal Investigator, entitled, “Personalized protein-protein interactomes and precision medicine in pulmonary arterial hypertension.” He is also the co-author of more than 230 scientific works including manuscripts published in flagship journals for the American Heart Association, American Thoracic Society and the Nature family discussing how multi-omics technologies can contribute to precision medicine. Dr. Maron is also the co-inventor of several patents or pending patents and is funded by the National Institutes of Health and other organizations.

Under his directorship, the UM-IHC conducts research in AI and applies this powerful technology to bio-monitoring wearable, sensor data, clinical, and many other datasets to revolutionize medicine. The research involves exploring and analyzing the data using various learning models to find hidden patterns and relationships to tackle health related problems. Research is also underway using AI, machine learning and network medicine to identify novel therapeutic targets as well as biomarkers that can be advanced into the Learning Health System. The Institute also leverages immense computational power to analyze and interpret very large amounts of biological data, such as gene sequences, transcriptomics, structural genomics, and more. These analyses can be linked to clinical data and used to anticipate disease, develop improved diagnostic and prognostic tools, and identify novel drug targets as well as disease biomarkers. UM-IHC researchers are also using data science and the Electronic Health Record to improve the way clinical research is performed aiming to generate clinical research data that reflects the communities at-hand, disrupts workflow, and increases the chances of successful findings at lower cost and greater efficiency.

Rozalina G. McCoy, M.D., M.S., is an endocrinologist, internist, and health services researcher. She is Associate Professor of Medicine, Associate Division Chief for Clinical Research in the Division of Endocrinology, Diabetes and Nutrition, and Director of Precision Medicine and Population Health at the University of Maryland Institute for Health Computing.

rozalina.mccoy@som.umaryland.edu

Thu Nguyen, ScD, MSPH is an associate professor of epidemiology and biostatistics at the University of Maryland School of Public Health. She is a social epidemiologist whose research focuses on the impact of modifiable social factors on minority health and health disparities. A primary line of focus of her research is investigating the influence of racism and discrimination in creating and perpetuating health equities.

Lisa L. Pineles, MA, is Program Director at UM‑IHC, supporting collaborative research and program management in epidemiology, artificial intelligence, infection prevention, antimicrobial resistance, and diagnostic stewardship. She contributes expertise in study design to advance patient outcomes and health system impact.

Dr. Danielle Powell is a dual-trained Audiologist and Epidemiologist. She received her AuD from the University of North Carolina-Chapel Hill and practiced in the greater Washington D.C. area for a number of years before pursuing a PhD in Epidemiology from the Johns Hopkins Bloomberg School of Public Health with a focus on epidemiology of aging. She has completed a post-doctoral fellowship in health services and outcomes research in the Department of Health Policy and Management at Johns Hopkins as a Health Services and Outcomes Research T32 fellow. Her research is at the intersection of hearing and hearing care, gerontology, epidemiology and public health, dementia, caregiving, health services and health systems-level care, consumer oriented health information technology, and implementation sciences or translation of research to clinical care. Her current work is funded through the Alzheimer’s Association exploring innovative ways to support care partners of older adults with hearing loss and dementia. 

Dr. Ratzki-Leewing is an Assistant Professor at the University of Maryland Institute for Health Computing and the Division of Gerontology, Department of Epidemiology and Public Health, and the Clinical and Translational Research Informatics Center (CTRIC) at the University of Maryland School of Medicine, Baltimore. She is also an Adjunct Professor in the Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University (Canada).

Her work focuses on leveraging and spotlighting person-reported data and measures to capture the real-world burden of iatrogenic hypoglycemia (low blood sugar caused by certain diabetes treatments) in diverse adult populations with diabetes. To this end, Dr. Ratzki-Leewing has led multiple interdisciplinary projects spanning more than 10 countries. Her scientific contributions have been published in top-tier medical journals and incorporated into several diabetes clinical practice guidelines, including the American Diabetes Association (ADA) Standards of Care.

She has delivered >100 research presentations across North America, Europe, and Asia—including more than 15 invited conference symposia—and co-developed over 10 continuing medical education programs. Dr. Ratzki-Leewing is a lead author of the forthcoming ADA textbook on diabetes-related hypoglycemia, an invited member of the ADA Conference Planning Hypoglycemia Sub-committee, a fellow of the ADA Women’s Interprofessional Network Group, and the Deputy Chair of the International Hypoglycaemia Study Group (IHSG).

In 2023, she was named a ‘Rising Star’ by the International Diabetes Center (Minnesota, USA).

Dr. Roger received her medical degree in 1986 from Sorbonne University in Paris, France and her Master in Public Health (Epidemiology) at the University of Minnesota in 1996. After training in cardiology at Mayo Clinic, in Rochester Minnesota, she joined the faculty in 1992 and became Professor in Medicine (2002) and Epidemiology (2006). At Mayo Clinic, Dr. Roger served in various leadership positions including Chair of the Department of Health Sciences Research and member of the Mayo Clinic Board of Governors and Board of Trustees.

Dr. Roger served on the NHLBI Advisory Council and the NHLBI Board of Scientific Counselors. She chaired the Epidemiology Council of the American Heart Association 2018-2020 and was recognized as the American Heart Association Distinguished Investigator in 2019.

The unifying theme of Dr. Roger’s work is the epidemiology of heart diseases and their occurrence and outcomes in populations. As a physician scientist, Dr. Roger has deployed, directly and through collaborations, multidisciplinary methods including epidemiology, outcomes, and population surveillance, and the use of electronic health records in population research.

I am a physician specializing in infectious diseases, and serve as co-director of the Research Initiative in Infectious Disease and Substance Use. My research and clinical care focus on the intersection of substance use disorder and infectious diseases, a focus on gender and sexual minorities, and incarcerated populations. I practice in community based sites in Washington, DC and Baltimore.

Dr. Slejko’s research is focused on innovative approaches for decision-analytic modeling for economic and health outcomes assessments. She has applied these methods to modeling medication adherence and translating pharmacometric findings to cost-effectiveness analyses. She holds a BA in Molecular, Cellular and Developmental Biology from the University of Colorado Boulder. Her PhD training at the University of Colorado School of Pharmacy Center for Pharmaceutical Outcomes Research was focused on pharmacoeconomics. Her postdoctoral training was completed at the Pharmaceutical Outcomes Research and Policy Program in the University of Washington School of Pharmacy. Prior to her PhD training, she had a seven-year career in drug discovery at Array BioPharma. Dr. Slejko is very active in the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and maintains close connections with industry and academic partners. Her research focuses on assessing economic and comparative value of medications and health care. Current efforts include informing decision-analytic models with real-world evidence on effectiveness, in particular patients’ adherence to medications as a determinant of value, how adherence affects economic evaluations and how predicting and improving adherence may increase value. As co-director of the School of Pharmacy’s Patient-Driven Values in Healthcare Evaluation (PAVE) Center, she leads research on incorporating patient-driven value elements into cost-effectiveness analyses and other components of value assessments.

Dr. Pratyush Tiwary and his research group conduct interdisciplinary theoretical and computational research to model and predict thermodynamics, dynamics, and their interplay in complex real‑world systems relevant to pharmaceutical, chemical, and materials sciences. A common theme across these systems is the prevalence of hard‑to‑model rare events. To address these challenges, Dr. Tiwary’s group develops and applies theoretical and computational tools grounded in equilibrium and non‑equilibrium statistical mechanics, applied mathematics, and recent advances in machine learning and artificial intelligence.

ptiwary@umd.edu