ARISE Network

Jonathan H. Chen MD, PhD leads a clinical informatics research group to empower individuals with the collective experience of the many, combining human and artificial intelligence to deliver better care than either. Dr. Chen founded a company to translate his Computer Science graduate work into an AI system used by students around the world. His expertise is featured in the popular press with over 100 research publications and awards. Dr. Chen continues to practice medicine for the reward of caring for real people and to inspire his research to discover and distribute the latent knowledge embedded in clinical data.

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Joséphine Cool is an adult hospitalist at Beth Israel Deaconess Medical Center. She is the director of the medical procedure service for the hospital medicine group at BIDMC, as well as the director of Point-of-Care Ultrasound Education and Simulation Education for the internal medicine residency program at BIDMC. She is a graduate of the Rabkin Fellowship in Medical Education at the Shapiro Institute, and she holds an SHM/CHEST certificate in Point-of-Care Ultrasound. She further co-founded the Procedural Research and Innovation for Medical Educators (PRIME) consortium. In addition to her work researching AI, Dr. Cool does research in technological innovations including in procedural innovation and competency and use of point-of-care ultrasound.

Jason A. Freed MD is the deputy section chief of Benign Hematology at Beth Israel Deaconess Medical Center and an assistant professor at Harvard Medical School.  He completed his residency, chief residency, and fellowship at BIDMC before joining the faculty. He has a number of educational leadership roles at BIDMC and HMS including serving as the associate program director for the internal medicine residency, the director of fellowship education for the department of medicine, and course director for hematology in the Harvard-MIT combined MD program. He does research in medical education and clinical hematology and his work has been published in Academic Medicine, the Journal of General Internal Medicine, and JAMA.

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Robert Gallo is a medical informatics research fellow in the Department of Health Policy and the VA Palo Alto Health Care System’s Center for Innovation to Implementation. He obtained his medical degree at Washington University School of Medicine, and subsequently completed his residency training in Internal Medicine at Stanford. Dr. Gallo’s research focuses on inpatient health services delivery, particularly for diabetes and cardiovascular disease. He also has interest in the evaluation and implementation of prediction models.

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Dr. Ethan Goh is an experienced healthcare executive with a background in informatics, digital health transformation, and strategic innovation. Through his role as a Stanford healthcare AI researcher, he has successfully led multi-site, grant-funded evaluation studies on Large Language Models applications within healthcare. Prior to Stanford, he was an Internal Medicine clinician, startup founder and technology consultant, working with partners like Google, OpenAI, Roche, Samsung, IDEO, and the NHS in the development, validation and commercialization of digital health products and AI technology. He holds an MD from Imperial College, London, and a Masters in Clinical Informatics and Management from Stanford University.

Laura Holdsworth PhD is a health services researcher and implementation scientist in the Evaluation Sciences Unit at Stanford. She uses a range of qualitative methods in her work, and is experienced in mixed methods research and evaluation. Her specific research interest is in the intersection of health care service processes and patient experiences, with the goal of improving the implementation and delivery of health services.

Hannah Kerman, MD is a Hospitalist at Beth Israel Deaconess Medical Center (BIDMC) and a lecturer at Harvard Medical School. She attended Brown University for undergraduate and medical school and completed her Internal Medicine Residency at BIDMC. She has participated in the design and implementation of qualitative and quantitative studies of AI in clinical practice.

Dr. Andre Kumar is a clinical associate professor of medicine at Stanford University with experience in clinical trial design, operations, and multi-site leadership. He has expertise in deep learning applications for medical imaging, particularly for clinical ultrasound. As an NIH-funded researcher, Dr. Kumar leads several clinical trials at Stanford University, including the RECOVER study, a $1.15 billion effort to understand the long-term effects of COVID-19 on patients. His work on this study will include large-scale analyses of over one million biosamples.

Julie Lee, MD, is a board-certified internal medicine physician and clinical informaticist at Stanford. She completed her undergraduate studies at Columbia, earned her medical degree at the University at Buffalo, and finished her internal medicine residency at UC Riverside. Dr. Lee focuses on integrating AI into clinical practice to improve patient outcomes, streamline workflows, and ensure health equity. She leverages mixed methods research and design thinking to create innovative, human-centered solutions in healthcare.

Dr. Milstein is a Professor of Medicine at Stanford and directs the University’s Clinical Excellence Research Center. The Center engages faculty from Health, Computer, and Social Sciences in the discovery and replication of innovative health care delivery methods that safely lower per capita health care spending for excellent care.

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Dr. Andrew Olson is a Professor of Medicine and Pediatrics at the University of Minnesota Medical School, where he practices hospital medicine and pediatrics. He serves as the founding Director of the Division of Hospital Medicine within the Department of Medicine.  Dr. Olson serves as the Director of Medical Education Research and Innovation in the Medical Education Outcomes Center, focusing on linking education with clinical and workforce outcomes.  Dr. Olson’s academic focus is better understanding clinical reasoning, especially diagnostic reasoning. He has published over 100 articles in medical education, diagnostic reasoning, and related areas. His research focuses on the interactions between individuals and the clinical environment and how teams make diagnostic decisions.

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Andrew S. Parsons, MD, MPH, FACP is an associate professor of medicine and practices as an internal medicine hospitalist at the University of Virginia (UVA). As Associate Dean for Clinical Competency for UVA School of Medicine, he oversees the teaching, assessment, and remediation of clinical skills across the four-year medical student curriculum. Within UVA’s Division of Hospital Medicine, he serves as Director of Research and Academic Advancement.  His research is focused on clinical reasoning, specifically management reasoning in education and clinical practice, including the use of AI to improve effectiveness and efficiency. Dr. Parsons leads UVA’s Clinical Reasoning Research Collaborative (CRRC), a physician research group aiming to improve reasoning education and positively impact patient care.

Adam Rodman is a general internis­­­t, medical historian focusing on medical epistemology and the development of diagnostic thought, author, medical educator, and artificial intelligence researcher. He is the Director of AI Programs at the Carl J Shapiro Institute for Education and Research at Beth Israel Deaconess Medical Center and an assistant professor at Harvard Medical School. His research focuses on medical education, clinical reasoning, integration of digital technologies, and human-computer interaction. His research and expertise are often featured in the popular press. His first book is entitled "Short Cuts: Medicine," and he is the host of the American College of Physicians podcast Bedside Rounds.

Eric Strong is an adult hospitalist with Stanford Healthcare, and a Clinical Associate Professor at Stanford School of Medicine. At the medical school, he serves as an associate course director for the school’s 6 semester doctoring course, in which his area of focus has been clinical reasoning and the evidence-based physical exam. He is also part of the school’s Educators-4-CARE learning community in which he has the privilege of being a clinical and professional mentor to five students each year, who he follows for their entire school experience. Prior to becoming a physician, Eric graduated from MIT with a degree in biology, and attended NYU for medical school. He is the founder and content creator for Strong Medicine, an educational YouTube channel which provides free, on-demand videos for healthcare professionals and those in training.

Kameron Collin Black, DO, MPH is a fellow physician in Clinical Informatics at Stanford. He completed his Internal Medicine residency at Oregon Health & Science University. His clinical interests include hospital medicine and geriatric medicine. His research interests are in the implementation of agentic AI in healthcare workflows, mitigation of bias in CDS tools, and data-driven quality improvement.

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Nicholas Marshall, MD, FAAP is a Pediatric Infectious Diseases and Clinical Informatics fellow at Stanford University.  He completed his pediatrics residency and chief residency at Cleveland Clinic, where he also served as a hospitalist and primary care physician.  His research focuses on infectious diseases across care settings, using machine learning and EHR-integrated decision support to advance antibiotic stewardship and diagnostic decision-making.  His work is supported by a grant from the Stanford Maternal and Child Health Research Institute (MCHRI) and by a Patient-Centered Outcomes Research Institute (PCORI)-funded project.

Vishnu Ravi, MD is an internal medicine physician, software engineer, and clinical informaticist who serves as Technology Architect for Stanford Medicine Catalyst and Lead Architect for Digital Health at Stanford's Mussallem Center for Biodesign. He has designed and implemented many AI-driven healthcare innovations including platforms for Parkinson's care, cardiovascular disease management, and precision pharmacogenomics. He co-founded Stanford Spezi, an open-source framework used globally for building standards-based digital health solutions. Alongside his technology work, he teaches CS342 Building for Digital Health at Stanford and maintains an active clinical practice providing primary care.

Samantha Wang MD is a Clinical Assistant Professor in the Division of Hospital Medicine. She is the Director of Faculty Development for the Division of Hospital Medicine, and Associate Course Director for the Practice of Medicine course required for all MD students transitioning to clerkships. She also leads strategic implementation of AI-enhanced QI initiatives in her role as Associate Clinical Director to the Serious Illness Care Program at Stanford. Her expertise lies in the overlap of medical education and DEI work, where she has developed and disseminated innovative curricula nationally and internationally. Her interests within AI include the societal and ethical implications of AI implementation and the need for governance and education to mitigate bias, harm, and disparities.

Yingjie is a senior biostatistician and the assistant director of the learning health systems program at Quantitative Sciences Unit, Stanford University of Medicine. She specialized in the integration of real-world evidence in clinical and public health research. Her expertise is in designing, implementing, and disseminating clinical research using diverse real-world databases, such as Electronic Health Records (EHRs), claims data, and registry databases. Yingjie’s proficiency extends to pragmatic trials, including evaluating innovative intervention (e.g. best practice alert, AI-driven tools, etc) in the health systems to improve patient’s care.Yingjie's work in these areas encompasses study design, data management, statistical analysis planning, and the submission of regulatory statistical documents to government agencies.

David Wu MD, PhD is a resident physician in dermatology at Harvard. Dr. Wu completed his MD, PhD training at the University of California, San Francisco (UCSF), where his research focused on genomic data science, CRISPR technology, and omics-based precision medicine. His current work aims to integrate clinical informatics and medical artificial intelligence to unlock insights from electronic health records, explore physician-AI collaboration, and advance the safety and alignment of medical AI. 

Fateme Nateghi Haredasht, PhD is a postdoctoral researcher at Stanford University in the Center for Biomedical Informatics Research. Dr. Nateghi completed her PhD in Biomedical Sciences at KU Leuven in Belgium, where her research focused on machine learning for time-to-event prediction and clinical decision support. Her current work centers on applying large language models and retrieval-augmented generation to electronic health records to enhance specialty care access, improve treatment prediction, and develop trustworthy, explainable AI systems for clinical use.

David JH Wu, MD is a resident physician in Radiation Oncology at Stanford. He completed his medical training at the University of Minnesota. His previous research work has focused on clinical applications of large language models and imaging applications of deep learning models. He was previously the host of the Medicine and Machine Learning (MaML) Podcast. Fun fact: He is one of many David Wu’s in medicine and befriended the other David Wu of ARISE while working in a neuroscience lab at UCSF.

Spencer Dorn MD MPH MHA is a gastroenterologist, physician leader, clinical administrator, informatics physician, academic, and advisor. Committed to the greater good, he writes here to connect the dots, spark thoughtful conversations, and learn from and connect with others who share a passion for improving healthcare. Sitting at the intersection of clinical practice, operations, and technology, he enjoys explaining how healthcare works and imagining how it can work better. He is fascinated by how artificial intelligence and other digital technologies are reshaping medicine and is particularly interested in redesigning specialty care. Spencer aims to integrate mind and body in both clinical practice and life. Outside of work, he enjoys spending time with family and friends, music, sports, reading, and swimming—most of all in the ocean.

Saloni Maharaj, MD is a Clinical Assistant Professor of Medicine at Stanford University and an academic hospitalist specializing in perioperative medicine and medical education. Outside of her clinical role, her research centers on the role of artificial intelligence in augmenting physician clinical decision-making, with particular emphasis on promoting the safe, effective, and clinically appropriate integration of these tools into real-world medical practice.

Jessica Tran, MD is a Clinical Assistant Professor of Medicine and hospitalist at Stanford University. She is actively engaged in clinical care, quality improvement, and research with a focus on the safe and effective integration of artificial intelligence into medical practice.