About the Ross Lab
The Ross lab is bridging the chasm between the science of personalized medicine and its use with cutting-edge analytics and implementation science. With a focus on cardiovascular and metabolic diseases, we aim to utilize big data from multiple sources (electronic health records, biobanks and sensors) and multidisciplinary efforts to detect disease early and improve health outcomes.
Elsie Gyang Ross, MD
Assistant Professor of Surgery
Dr. Ross is a vascular surgeon and research scientist. She graduated from Stanford University School of Medicine in 2011 and completed her vascular surgery 0+5 residency at Stanford University School of Medicine in 2018. During her residency, she completed a two-year post-doctoral fellowship in biomedical informatics. Her current research focuses on using machine learning and electronic health records for early disease identification, precision medicine, and evaluating opportunities to engage in patient education beyond the clinic.
Shaunak Adkar, MD, PhD
Vascular Surgery Resident
Dr. Adkar is a vascular surgery resident. He graduated from UC Berkeley with a BS in Molecular and Cell Biology before completing an M.D./Ph.D. program at the Duke University School of Medicine.
Saeed Amal, PhD
Visiting Postdoctoral Scholar
Dr. Saeed Amal received his PhD and MSc degree in Computer Science from the University of Haifa and BSc degree in Computer Science from Technion. He has vast leadership experience in applied research from the tech industry and is a former VP of R&D oata medical startup in the cardiology field. His research interests are Deep Learning (DL) for Natural Language Processing (NLP) and Recommender Systems for the health care domain
Vascular Surgery Resident
Vivian completed her undergraduate degree in Biology at Stanford. She attended the Columbia University College of Physicians & Surgeons in New York for medical school and returned to Stanford for her Integrated Vascular Surgery residency. As part of her program, Vivian has completed 3 years of clinical training and is now taking a two year fellowship to pursue her interest in academic surgery.
Vivian’s research leverages epidemiological and machine learning methods to evaluate surgical diagnostics and decision-making tools, with the goal of reducing unnecessary testing and streamlining the pathway from diagnosis to intervention. Previously, she has used national databases to delineate gender differences in outcomes of aortic surgery and the effect of systemic anticoagulation on patients with traumatic aortic injury. She is particularly interested in using the electronic medical record as a source of clinical data and a platform for clinical decision-making support. She will be pursuing a Masters in Biomedical Informatics at Stanford from 2020-2022 to refine her computational techniques.
Tofunmi Omiye is an MS student in Health Policy at Stanford University. He received his medical degree from the University of Ibadan, Nigeria, where he was a Federal Government scholar.
Tofunmi is a Research assistant in the Ross Lab in the vascular surgery division at Stanford, and he works on using machine learning to improve overall healthcare outcomes. He is also interested in predictive analytics, particularly for cerebrovascular diseases. He is keenly interested in developing solutions at the nexus of health, technology, and policy. In his spare time, he enjoys traveling, studying the financial markets, and Afrobeats music.
Postdoctoral Research Scholar