Dr. Laura Biven is the data science technical lead for ODSS. In this role she is responsible for strategic planning, coordination, and oversight in cloud computing, platform interoperability, and bringing together the computer science and biomedical communities. Before joining the NIH, Laura spent 12 years at the Department of Energy, where she led strategic efforts in data management and data science including the development of the department-wide data management plan requirements, a new stewardship model for high-valued public data repositories, and new research avenues to better leverage DOE data and advance AI. Prior to joining DOE, Laura was an AAAS Science and Technology Policy Fellow, serving first in the U.S. Department of Agriculture and then at the Department of State. Laura completed her higher education in the United Kingdom; she holds a MSci in math and physics from the University of Bristol and a Ph.D. in applied mathematics from the University of Warwick.
Dr. Jennifer Couch
Jennifer Couch, Ph.D., is co-chair of the National Cancer Institute’s AI working group which identifies and prioritizes cancer research areas that can most benefit from AI methods. She works with colleagues across the NCI, the NIH, other federal agencies, industry and academia to coordinate efforts and build programs at the intersection of biomedical research and AI, including developing and adapting new methods, creating training opportunities and identifying and addressing ethical issues. She co-leads a series of Innovation Labs that bring together individuals from diverse fields to form new collaborations and launch trans-disicplinary pilot projects to address critical biomedical research questions. Labs this year have focused on the intersection of deep-learning and multi-scale cancer biology, creative methods for data visualization and emergent properties in cancer. Dr. Couch’s branch at the NCI, NIH supports research and development of enabling technologies and methodologies including structural biology and biophysical characterization; bioinformatics, computational biology, mathematical modeling, data science, citizen science and crowdsourcing methods, and systems biology; molecular applications including synthetic biology; and bioengineering and biotechnology including biomimetics. Additionally, she is the NIH Citizen Science and Crowdsourcing Coordinator, exploring the use of and potential for citizen science approaches to biomedical research and provides resources to the research community.
Mr. Glen de Vries
Glen de Vries is the co-CEO and co-founder of Medidata, the leading cloud platform for life sciences R&D. Glen has been driving Medidata's mission since the company’s inception in 1999: Powering smarter treatments and healthier people. In 2019, in one of the largest health care technology acquisitions in history, Medidata became part of Dassault Systèmes. Glen’s publications have appeared in Applied Clinical Trials, Cancer, The Journal of Urology, Molecular Diagnostics, and other journals. He serves as a trustee of Carnegie Mellon University, a HITLAB Fellow, a member of the Healthcare Businesswomen’s Association European Advisory Board, and is the author of The Patient Equation (de Vries & Blachman, 2020).
Dr. Alan Hubbard
Alan Hubbard, Professor of Biostatistics, Univ. of California, Berkeley, is director of the Biomedical Big Data pre-doctoral training program, and one of the co-directors of the Center of Targeted Learning, is head of the computational biology core of the SuperFund Center at UC Berkeley (NIH/EPA), as well a consulting statistician on several federally funded and foundation projects. He has worked as well on projects ranging from molecular biology of aging, epidemiology, and infectious disease modeling, but most all of his work has focused on semi-parametric estimation in high-dimensional data. His current methods-research focuses on precision medicine, variable importance, statistical inference for data-adaptive parameters, and statistical software implementing targeted learning methods. Currently working in several areas of applied research, including early childhood development in developing countries, patient outcomes from acute trauma, environmental genomics and comparative effectiveness research in diabetes care.
Dr. Trey Ideker
UC San Diego, Professor of Medicine
UC San Diego, Adjunct Professor of Bioengineering & Computer Science
Director, Cancer Cell Map Initiative
Director, National Resource for Network Biology
Director, San Diego Center for Systems Biology
Trey Ideker, Ph.D. is a Professor in the Departments of Medicine, Bioengineering and Computer Science at UC San Diego, and Director or co-Director of three NIH-supported research centers: the NCI Cancer Cell Map Initiative, the NIGMS San Diego Center for Systems Biology, and the NIGMS National Resource for Network Biology. Dr. Ideker received Bachelor’s and Master’s degrees from MIT in Electrical Engineering and Computer Science and his Ph.D. from the University of Washington in Molecular Biology under the supervision of Dr. Leroy Hood.
Dr. Ideker’s research is led by the vision that given the right experimentation and analysis, it will be possible to automatically assemble maps of pathways just as we now assemble maps of genomes. During graduate work, he developed a general iterative framework for how biological systems can be systematically perturbed, interrogated and modeled. This framework laid the foundation for many studies in the discipline of Systems Biology. He demonstrated that biological networks could be integrated with gene expression to systematically map pathways and aligned, like sequences, to reveal conserved and divergent functions. He showed that the best biomarkers of disease are typically not single proteins but aggregates of proteins in networks.
Dr. Ideker has founded influential bioinformatic tools including Cytoscape, a popular network analysis platform which has been cited >12,000 times. Ideker serves on the Editorial Boards for Cell, Cell Reports, Nature Scientific Data, EMBO Molecular Systems Biology, and PLoS Computational Biology and is a Fellow of AAAS and AIMBE.
He was named one of the Top 10 Innovators of 2006 by Technology Review magazine and was the recipient of the 2009 Overton Prize from the International Society for Computational Biology. His work has been featured in news outlets such as The Scientist, San Diego Union-Tribune, Forbes magazine, NPR, and The New York Times.
Dr. Shravan Kethireddy
Dr. Shravan K. Kethireddy is a board certified physician in Infectious Diseases, Critical Care Medicine and Clinical Informatics. He received his medical degree from the Sri Ramachandra Medical College in India and completed residency in internal medicine at Hennepin County Medical Center. Following residency, he completed fellowships in Infectious Diseases at the University of Wisconsin, Madison and Critical Care Medicine at the University of Manitoba. His current research interests intersect the fields of sepsis/septic shock, causality and complex systems. He was previously associate program director of the clinical informatics fellowship and associated chief data officer both at Geisinger Medical Center, system director for critical care at Northeast Georgia Health System and currently associate staff in the Respiratory Institute at Cleveland Clinic.
Dr. Patrick Loehrer
Patrick Loehrer, Sr., M.D. is the Joseph W. and Jackie J. Cusick Professor in Oncology and Distinguished Professor of Indiana University. He is also the Director of the IUSCCC Center for Global Oncology and Health Equities. He has been an active clinical researcher and specialist in the treatment of a variety of cancers including testis, bladder, colon, pancreas and, most notably, thymic malignancies. His research on the drug, ifosfamide, led to its approval by the FDA. His research related to thymic cancers has been recognized with the Exceptional Service Award of the Foundation for Thymic Research.
Dr. Loehrer received his undergraduate degree in Mechanical Engineering from Purdue University and his medical degree from Rush Medical College. He completed his internship and residency at Rush Presbyterian St. Luke's Medical Center and a fellowship in Medical Oncology at Indiana University. In 1983, he joined the faculty of the Indiana University School of Medicine. Dr. Loehrer is director emeritus of the Indiana University Melvin and Bren Simon Comprehensive Cancer Center, an NCI-designated Cancer Center and led the efforts to achieve comprehensive status in 2019.
Dr. Loehrer was the founding chair of the Hoosier Oncology Group (now Hoosier Cancer Research Network) for two decades, which has enrolled over 5,000 patients and conducted trials in 20 countries around the world. Dr. Loehrer has served on the boards of the ECOG Foundation, the American Society of Clinical Oncology, and the American Board of Internal Medicine. He serves on the Advisory Committee for the Indiana University Center for Global Health. Dr. Loehrer is also the founding director of the Academic Model for Providing Access to Healthcare (AMPATH)-Oncology Program for over the past decade, which now sees over 8,000 cancer patients a year and screens over 1,500 women for cervical and breast cancers a month in western Kenya.
Dr. Loehrer has received numerous awards including the Special Recognition Award and the inaugural, Allen S. Lichter Visionary Leader Award from the American Society of Clinical Oncology. From Purdue University, he has received the Outstanding Mechanical Engineering Award and the Distinguished Engineering Alumni Award in 2015. He is the recipient of the President’s Medal for Excellence and the Bicentennial Medal from Indiana University. He has served on the Board of Directors for the American Board of Internal Medicine, American Society of Clinical Oncology and the American Association of Cancer Institutes. He is currently the Chair of the NCI Clinical Trials Advisory Committee. In 2004, he was inducted into the Alpha Omega Alpha Honor Medical Society.
Dr. Eneida A. Mendonca
Dr. Mihai Pop
Dr. Pop is a Professor in the Department of Computer Science and the Center for Bioinformatics and Computational Biology at the University of Maryland, College Park, and he serves as the Director of the University of Maryland Institute for Advanced Computer Studies (UMIACS). He received his Ph.D. in Computer Science at Johns Hopkins University in 2000, and has joined the University of Maryland in 2005. Dr. Pop's current research interests include metagenomic assembly and analysis algorithms with a specific interest in characterizing variation within natural communities. His lab has developed a number of widely used open-source software tools for genome and metagenome analysis. Dr. Pop is actively involved in teaching at the undergraduate and graduate levels and is strongly interested in the development of educational resources for introductory computer science and bioinformatics. He is also actively involved in diversity and inclusion efforts within the university and the broader computer science and computational biology communities.
Dr. John Quackenbush
John Quackenbush is Professor of Computational Biology and Bioinformatics and Chair of the Department of Biostatistics at the Harvard TH Chan School of Public Health and Professor at the Dana-Farber Cancer Institute. John’s PhD was in Theoretical Physics, but in 1992 he received a fellowship to work on the Human Genome Project. This led him through the Salk Institute, Stanford University, and The Institute for Genomic Research (TIGR), before moving to Harvard in 2005. John’s research uses massive data to probe how many small effects combine to influence our health and risk of disease. He has published more than 300 scientific papers that have collectively been cited over 78,000 times and among his honors is recognition in 2013 as a White House Open Science Champion of Change. In 2012, he founded Genospace, a precision medicine software company providing data platforms to hospitals, diagnostic testing labs, and other groups. In 2017, Genospace was purchased by the Hospital Corporation of America. He serves on numerous advisory boards, including those of Merck KGaA, Caris Life Sciences, and RenalytixAI.
Cynthia Rudin is a professor of computer science, electrical and computer engineering, and statistical science at Duke University, and directs the Prediction Analysis Lab, whose main focus is in interpretable machine learning. She is also an associate director of the Statistical and Applied Mathematical Sciences Institute (SAMSI). Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a PhD from Princeton University. She is a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the "Top 40 Under 40" by Poets and Quants in 2015, and was named by Businessinsider.com as one of the 12 most impressive professors at MIT in 2015. She is a fellow of the American Statistical Association and a fellow of the Institute of Mathematical Statistics.
Pratik Shah is a Principal Investigator and Principal Research Scientist at The MIT Media Lab and leads the Health 0.0 research lab. His research creates novel intersections between engineering, medical imaging, machine learning, and medicine to improve health and diagnose and cure diseases.
Research topics: 1) medical imaging technologies using unorthodox artificial intelligence for early disease diagnoses; 2) novel ethical and explainable artificial intelligence based digital medicines and treatments, and 3) point-of-care medical technologies for real-world data and evidence generation to improve public health. Pratik’s graduate and postdoctoral research has contributed to the discovery of a vaccine component to prevent pneumococcal (Streptococcus pneumoniae) diseases; the identification of new pathways, technologies, and metabolites as antimicrobials to target gastrointestinal infections; and a non-profit organization to deploy a low-cost water quality test for the developing world. Past acknowledgments include the American Society for Microbiology’s Raymond W. Sarber National Award, a Harvard Medical School and Massachusetts General Hospitals ECOR Fund for Medical Discovery postdoctoral fellowship, coverage by leading national and international news media outlets. Pratik has been an invited discussion leader at Gordon Research Seminars; a speaker at American Association for the Advancement of Sciences, Cold Spring Harbor Laboratories, Gordon Research Conferences, The National Academies of Sciences, Engineering and Medicine, TED and IEEE bioengineering conferences; and a peer reviewer for leading scientific publications and funding agencies. Pratik has BS, MS, and Ph.D. degrees in biological sciences and completed fellowship training at Massachusetts General Hospital, the Broad Institute of MIT and Harvard, and Harvard Medical School.
Dr. Paul Sheehan
Dr. Paul Sheehan joined DARPA as a program manager in the Biological Technologies Office in July 2017. Dr. Sheehan will focus on new nanoscale methods for biological sensing that could be coupled with advanced engineering and electronics. His interests involve the bi-directional conversion between electronic and biochemical signals, the study of how nanostructures interact with cells and biomolecules, and new approaches for the rapid development and manufacture of bioassays.
Prior to his arrival at DARPA, Dr. Sheehan directed the Surface Nanoscience and Sensor Technology Section at the U.S. Naval Research Laboratory. His highly interdisciplinary team comprised biochemists, chemists, engineers, and physicists who studied nanometer scale phenomena at surfaces, as well as bioelectronics for sensing and biotic/abiotic interfaces. The team focused on discovering and developing new materials that could advance electronics and biosensing.
Dr. Sheehan was a University Fellow at the University of North Carolina where he earned a Bachelor of Science degree in Chemistry-based Materials Science. After receiving his Doctor of Philosophy degree in Chemical Physics from Harvard University, he served as a National Research Council Postdoctoral Fellow at the Naval Research Laboratory. He is a fellow of the AVS.
Dr. Eric Stahlberg
Director, Biomedical Informatics and Data Science
Frederick National Laboratory for Cancer Research
Stahlberg is director of Biomedical Informatics and Data Science at the Frederick National Laboratory for Cancer Research (FNLCR). He has been instrumental in establishing the FNLCR high performance computing initiative and in assembling scientific teams across multiple, complex organizations to advance predictive oncology.
Stahlberg joined the Frederick National Laboratory in 2011 to form and direct the National Cancer Institute’s (NCI) Center for Cancer Research Bioinformatics Core, which helped build intramural research collaborations between the national laboratory and NCI.
Since then, Stahlberg has played a leadership role in many key partnerships, including the strategic interagency collaboration between the NCI and the Department of Energy (DOE), created in 2016 to simultaneously accelerate advances in precision oncology and scientific computing. Programs include the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), ATOM and CANDLE. Stahlberg spearheads the Laboratory’s contributions to the NCI-DOE Collaboration programs and directs FNLCR activities to expand engagement with the broader cancer research community, including interdisciplinary projects to advance development of a cancer patient digital twin and creation of innovative approaches for radiation oncology.
He helped launch and support the Frontiers of Predictive Oncology and Computing meetings and is a founding co-organizer of the annual Computational Approaches for Cancer Workshop (CAFCW), held at the international Supercomputing conference since 2015.
Stahlberg holds a Ph.D. in computational chemistry from The Ohio State University. In 2017, he was recognized as one of FCW‘s Federal 100.
Dr. Wendy Woodward
Professor University of Texas MD Anderson Cancer Center
Dr. Woodward is a Professor and the Section Chief of Clinical Breast Radiation in the Department of Radiation Oncology at the University of Texas MD Anderson Cancer Center (MDACC). She is a physician-scientist specializing in clinical breast radiation oncology with a lab focused on breast cancer stem cell biology and radiobiology. Dr. Woodward is the Deputy Director of the MDACC Inflammatory Breast Cancer Clinic and Research Program and is dedicated to advancing the radiation treatment and biologic understanding of inflammatory breast cancer through laboratory, translational, and clinical research. Nationally, she serves as a translational science liaison for the breast working group in NRG Oncology devoted to designing translational endpoints for multi-institutional trials in breast radiation therapy. Finally, Dr. Woodward has a strong interest in education and mentoring trainees in both clinical and translational breast cancer research and has received awards for post-doctoral and Resident mentoring.
Dr. Bin Yu
Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair in the departments of statistics and EECS at UC Berkeley. She leads the Yu Group which consists of 15-20 students and postdocs from Statistics and EECS. She was formally trained as a statistician, but her research extends beyond the realm of statistics. Together with her group, her work has leveraged new computational developments to solve important scientific problems by combining novel statistical machine learning approaches with the domain expertise of her many collaborators in neuroscience, genomics and precisio medicine. She and her team develop relevant theory to understand random forests and deep learning for insight into and guidance for practice.
She is a member of the U.S. National Academy of Sciences and of the American Academy of Arts and Sciences. She is Past President of the Institute of Mathematical Statistics (IMS), Guggenheim Fellow, Tukey Memorial Lecturer of the Bernoulli Society, Rietz Lecturer of IMS, and a COPSS E. L. Scott prize winner.
She is serving on the editorial board of Proceedings of National Academy of Sciences (PNAS) and the scientific advisory committee of the UK Turing Institute for Data Science and AI.