Karthik Adapa is a physician-scientist, policy scholar, and international civil servant with over two decades of experience driving healthcare innovation worldwide through digital governance and artificial intelligence. As regional adviser for digital health and AI at the WHO South-East Asia Regional Office, Karthik guides ten countries in designing and adopting medical technology strategies. Under his leadership, his region became the first in the WHO where 80% of countries have successfully launched fully funded digital health roadmaps. Previously, as a member of the Indian Administrative Service, Karthik served as secretary for health and family welfare and secretary for information technology in the Government of Punjab, where he conceived and led India’s first population-scale AI breast cancer screening study. 

With over 100 peer-reviewed publications, Karthik's research covers clinical AI evaluation, explainable machine learning, clinician burnout, and digital health systems. He serves on the editorial boards of npj Digital Medicine and PLOS Digital Health, and is an adjunct professor at the University of North Carolina at Chapel Hill. He is a contributor to WHO normative guidance on AI and digital health, and played a key role in developing India's Strategy for Artificial Intelligence in Health and currently serves on its implementation committee under the Ministry of Health and Family Welfare.

He holds an MBBS, a master's degree in public policy and public health, and a PhD in health informatics and data science from the University of North Carolina at Chapel Hill. He is a Fulbright Scholar and a Chevening Gurukul Fellow at St Cross College, University of Oxford.

As an AsiaGlobal Fellow, Karath’s research will focus on developing rigorous frameworks for evaluating AI and advancing responsible deployment in primary healthcare across low- and middle-income countries in Asia. His work draws on digital public infrastructure models and WHO normative standards to inform governance architectures that are equitable, evidence-based, and context-sensitive.