Nigam H. Shah, MBBS, Ph.D Closed Now

Dr. Nigam Shah is an internationally recognized leader in biomedical informatics, health data science, and artificial intelligence in healthcare. He currently serves as the Chief Data Scientist for Stanford Health Care and is a Professor of Medicine (Biomedical Informatics) at Stanford University School of Medicine. His work bridges cutting-edge AI and machine learning methods with real-world clinical data to transform patient care, improve outcomes, and optimize health systems.

Dr. Shah’s research focuses on large-scale health data analysis, natural language processing (NLP) of clinical records, and predictive modeling for clinical decision support. He has developed innovative approaches that leverage electronic health record (EHR) data to detect adverse drug events, improve diagnostic accuracy, and personalize treatment strategies.

One of his major contributions is the development of data science platforms that enable rapid-learning health systems—healthcare environments that continuously analyze patient outcomes and feed that knowledge back into practice. His work has helped establish AI-driven frameworks for evidence generation, enabling clinicians and researchers to make decisions supported by real-world evidence rather than relying solely on clinical trials.

Dr. Shah has published extensively in high-impact journals such as JAMA, Nature Medicine, and The Lancet Digital Health. His thought leadership in responsible AI in healthcare has influenced policy discussions globally, ensuring that machine learning applications remain transparent, equitable, and clinically relevant.

He has received recognition for his contributions, including election to the American Society for Clinical Investigation (ASCI) and multiple awards for innovation in biomedical informatics. Beyond academia, Dr. Shah frequently collaborates with technology companies and health systems to accelerate the safe and effective adoption of AI in clinical practice.