CTDS Core Faculty and PIs
Robert L. Grossman
Robert L. Grossman, Ph.D., is the Frederick H. Rawson Distinguished Service Professor in Medicine and Computer Science and the Jim and Karen Frank Director of the Center for Translational Data Science at the University of Chicago. He joined the faculty in 2010 and has served as the chief research informatics officer of the Biological Sciences Division since 2011. He is also the Chief of the Section of Biomedical Data Science in the Department of Medicine.
He is the principal investigator for the National Cancer Institute Genomic Data Commons (GDC), a platform for the cancer research community that manages, analyzes, integrates, and shares large-scale genomic datasets in support of precision medicine. The GDC was used by more than 100,000 researchers in the past year. He has also built data commons to support research in other areas, including cardiovascular diseases, infectious diseases, gastrointestinal diseases, and the environment. His research interests include data science, machine learning, and deep learning.
He earned his Ph.D. in applied mathematics at Princeton University and an AB in mathematics from Harvard University.
Phil Schumm
L. Philip Schumm, M.A., is the Director of Biostatistics and Statistical Computing in the Center for Translational Data Science. Prior to this he was the Director of the Research Computing Group and Assistant Director of the Biostistics Laboratory in the Department of Public Health Sciences, where he had been since 1996.
He is the Co-PI for the HEAL Data Platform, a Gen3 data mesh providing access to data from studies funded by NIH's Helping to End Addiction Long-term (HEAL) Initiative. He also co-leads the Data and Analytics Support Core (DASC) within NIDA's Justice Community Opioid Innovation Network's (JCOIN) Methodology and Advanced Analytics Resource Center (MAARC), for which he has built a Gen3 data commons. He has built data commons and analytic platforms for several other NIH-funded research consortia and groups, including a platform at the University of Chicago for secure management and analysis of Medicare and Medicaid data from CMS. He is a co-investigator and principal biostatistician for the NIA-funded National Social Life, Health and Aging Project (NSHAP). His current methodological work focuses on the measurement and modeling of social networks, cognitive and sensory function, and physical activity, all of which are critical to understanding differences in health trajectories at older ages.
He earned his M.A. in statistics from the University of Chicago, and joined the Center in 2023.
Aarti Venkat
Aarti Venkat, Ph.D. is the Director of Clinical Informatics in the Center for Translational Data Science and Assistant Professor of Medicine at the University of Chicago.
Her research is broadly focused on oncology, specifically i) developing bioinformatics and machine learning methods for multimodal cancer data and ii) building data meshes, systems that researchers can use to perform federated search and learning. She is Co-PI for the Biomedical Research Hub, a leading example of a data mesh for biomedical research.
She earned her Ph.D. in Human Genetics at the University of Chicago, M.S. in Bioinformatics at the University of Illinois Urbana-Champaign, M.S. in Biochemistry at Seth G.S. Medical College, and B.S. in Life Sciences at St. Xavier’s College. She joined the Center and University in 2022.
Zhenyu Zhang
Zhenyu Zhang, Ph.D. is the Director of Bioinformatics in the Center for Translational Data Science at the University of Chicago.
He is a Co-PI and key contributor to the design and development of the National Cancer Institute Genomic Data Commons, a unified repository and cancer knowledge base that enables data sharing across cancer genomic studies in support of precision medicine. His research interests include multi-omics data analysis, statistical modeling and method development, and machine learning.
He earned his Ph.D. in Molecular Biology and MS in Statistics at the University of Texas at Austin. He joined the University in 2010 and has been affiliated with the Center since 2013.
CTDS Affiliated Faculty
Maryellen L. Giger
Maryellen L. Giger, Ph.D. is the A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, and the College at the University of Chicago. She is also the Vice-Chair of Radiology (Basic Science Research) and the immediate past Director of the CAMPEP-accredited Graduate Programs in Medical Physics/ Chair of the Committee on Medical Physics at the University.
She is the PI for the NIBIB Medical Imaging and Data Resource Center (MIDRC), which is based upon a Gen3 data commons.
For over 30 years, she has conducted research on computer-aided diagnosis, including computer vision, machine learning, and deep learning, in the areas of breast cancer, lung cancer, prostate cancer, lupus, and bone diseases.
She is a former president of the American Association of Physicists in Medicine and a former president of the SPIE (the International Society of Optics and Photonics) and was the inaugural Editor-in-Chief of the SPIE Journal of Medical Imaging.
She is a member of the National Academy of Engineering (NAE) and was awarded the William D. Coolidge Gold Medal from the American Association of Physicists in Medicine, the highest award given by the AAPM. She is a Fellow of AAPM, AIMBE, SPIE, SBMR, IEEE, and IAMBE. In 2013, Giger was named by the International Congress on Medical Physics (ICMP) as one of the 50 medical physicists with the most impact on the field in the last 50 years.
She has more than 200 peer-reviewed publications (over 300 publications), has more than 30 patents, and has mentored over 100 graduate students, residents, medical students, and undergraduate students.
Aly A. Khan
Aly A. Khan, Ph.D. is a research faculty member in the Department of Pathology at the University of Chicago. His lab focuses on developing novel computational methods to better understand how immune cells interact with each other, the surrounding tissue and organ systems, and the microbiome. Prior to joining the University of Chicago in 2019, Dr. Khan was a member of the research faculty at the Toyota Technological Institute in Chicago, where he led an independent research program in computational immunology. In addition to his academic work, he has worked on computational biology in industry, including at Merck, Genentech, and Tempus Labs. He received his Ph.D. in Computational Biology jointly from Cornell University and Memorial Sloan Kettering Cancer Center.
Alexander Pearson
Alexander Pearson, MD, Ph.D. is Assistant Professor of Medicine in the Sections of Hematology/Oncology and Computational Biomedicine and Biomedical Data Science at University of Chicago, and co-director of the head/neck cancer program at the University of Chicago Comprehensive Cancer Center.
He runs a laboratory that has a combined focus on integrating cancer biology techniques into mathematical modeling frameworks as well as developing machine learning-based cancer biomarkers. His goal as a practicing physician is to maintain a cutting-edge, data-driven, research-intensive clinical practice with clinical trial protocols evaluating scientific questions across the full natural history of solid tumors. He is a highly collaborative computational oncology researcher, and his research partners include multiple branches of the National Institutes of Health, the US Department of Energy, and multiple research foundations.
He earned his MD and Ph.D. in Statistics from the University of Rochester as part of the Medical Scientist Training Program. He completed an internship, Internal Medicine Residency, and Hematology/Oncology Fellowship at the University of Michigan Physician Scientist Training Program. He joined the University in 2017 and has been affiliated with the Center since 2020.
Samuel Volchenboum
Sam Volchenboum, MD, Ph.D., MS, is an expert in pediatric cancers and blood disorders. He has a special interest in treating children with neuroblastoma, a tumor of the sympathetic nervous system.
In addition to caring for patients, Dr. Volchenboum studies ways to harness information technology to enable research and foster innovation using large data sets. He directs the development of the International Neuroblastoma Risk Group Database project, which connects international patient data with external information such as genomic data and tissue availability. The center he runs provides computational support for the Biological Sciences Division at the University of Chicago, including high-performance computing, applications development, bioinformatics, and access to the clinical research data warehouse.
