Meet the 2022 DATA Scholars

Dr. Mohd Anwar joined the National Institute of Biomedical Imaging and Bioengineering in the Division of Health Informatics Technologies. He is an interdisciplinary computer scientist with training in human-centered artificial intelligence (AI). His research employs computational methods for secure and privacy-preserving acquisition of data from cyber and cyber-physical systems as well as for building predictive data analytics models. At NIBIB, he explores how wearable device data from different sources can be aggregated and analyzed to draw meaningful scientific insights, stratify risks, or predict disease or health outcomes. Dr. Anwar is a professor of Computer Science at North Carolina A&T State University.

Dr. Brad Bower joined the National Institute of Biomedical Imaging and Bioengineering to assist with scale up of the NIBIB-funded Medical Imaging Data and Resource Center (MIDRC.org). His work will build on the foundational work of former DATA Scholar Rui Carlos Sa (2020-2022 DATA Scholar cohort). This project includes identifying and advancing opportunities for interoperability between repositories including MIDRC (NIBIB), N3C (NCATS), BioData Catalyst (NHLBI), and All of Us; exploring public-private partnerships in the data ecosystem; and promoting the bench-to-bedside data lifecycle for AI product development to lower the barriers to commercialization of new AI-based products. Dr. Bower has a diverse set of experiences in research, marketing, and leadership roles in medical device companies from preclinical research and development to FDA clearance, product launch, and post-market activities. His prior work includes ophthalmic imaging devices, non-invasive concussion diagnostics, point of care diagnostics, and AI-enabled MRI-based prediction of symptoms associated with autism spectrum disorder in infants.

Dr. Zhaoyi Chen joined the National Cancer Institute (NCI) team working to create Multi-modal Cancer Data Integration Solutions from Cross-atlas Datasets. He will perform integration of large-scale omics and imaging data sets from multiple NIH platforms and develop prototype tools for visualization of cross-atlas data. Before joining NCI, Dr. Chen is a research scientist at the University of Florida, where his research focused on precision medicine and precision public health using large EHR data and causal AI framework.

Dr. Michelle Hribar joined the National Eye Institute (NEI) where she is working under Kerry Goetz in the Office of Data Science and Health Informatics. She is leading a national effort to improve the standardization of ophthalmic data for research, which includes co-chairing the Observational Health and Data Science Informatics (OHDSI) Eye Care and Vision Research workgroup with the goal of adding ophthalmic data to the OMOP common data model. Dr. Hribar originally trained as a computer scientist before retraining as a medical informaticist at Oregon Health & Science University. Before joining NEI, she was an Associate Professor in Ophthalmology at the Casey Eye Institute and in Medical Informatics at Oregon Health & Science University. Her NIH grant funded research has focused exclusively on informatics in ophthalmology, specifically in the reuse of electronic health record data for research both in operations and clinical applications.

Dr. Sharat Israni is a Biomedical Translator within National Center for Advancing Translational Sciences (NCATS). Main scholar project is to lead the ordering and organizing of results to biomedical questions from a set of knowledge graphs, currently focused on drug discovery, to make them maximally relevant to the user. The results come from across many Translator knowledge providers and reasoning engines, and can easily measure in the thousands. Ordering them scientifically (in both senses, data and biomedical) for researcher relevance is a large and complex problem, as the major search companies have shown. Besides NCATS Biomedical Translator, Dr. Sharat is the Chief Technology Officer (CTO) of UCSF’s Bakar Computational Health Sciences Institute, and Director of Research Computation at UC Davis Center for Precision Medicine and Data Sciences

Dr. Chen Liang joined the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). He is mentored by Drs. Robert Star, Chris Ketchum, and Eric Brunskill to develop a cutting-edge framework and standards of a computational data ecosystem for harmonization and migration of large, diverse, and complex datasets for kidney and urologic diseases. At NIDDK, he supports several research consortia and projects employing various biomedical informatics and data science methods. At the time of his appointment as the DATA Scholar, Dr. Liang is an Assistant Professor of biomedical informatics and public health at University of South Carolina, and a Fellow of American Medical Informatics Association (FAMIA). He was trained in data science, biomedical informatics, and artificial intelligence for clinical and translational medicine at the University of Texas School of Biomedical Informatics.

Dr. Sepideh Mazrouee joined the National Institute of Allergy and Infectious Diseases (NIAID) as a DATA Scholar in the Office of Data Science and Emerging Technologies (ODSET). She is a computer scientist, specializing in big data analytics. Her research spans over human and plant DNA sequence analysis, complex transmission networks of various infectious diseases from STIs to COVID-19. She is leading the AI pandemic preparedness project at NIAID. This project involves integration of various data related to pathogens with pandemic potentials in order to assist the efforts of developing medical countermeasures for future pandemics. Besides NIAID, Dr. Mazrouee is a research scientist at the University of California San Diego with research focus on Digital Health AI modeling.

Dr. S. Pyne is a NIH DATA Scholar at NIAMS involved in building an interoperable autoimmunity, inflammation, and Covid-19 data ecosystem. In his research, Dr. Pyne explores and harnesses the Interoperability and Reusability potential of multi-omic datasets on autoimmunity and related diseases generated from different platforms, designs strategies to harmonize heterogeneous data and metadata, and identifies opportunities for their integrative analysis. His project involves data from the Accelerating Medicines Partnership (AMP) programs and the NIH intramural Systemic Autoimmunity Branch (SAB) COVID-19 project. Further, he presents data science strategies and recommendations to senior leadership and advisory committees. Dr. Pyne is also an adjunct professor at the Department of Statistics and Applied Probability, University of California Santa Barbara. Previously, he has served in scientific and leadership positions at premier academic institutions both in the US and internationally.