Joining us with a rich background spanning AI, Responsible Data Science, global partnerships, and learning & computational social sciences, Dr. Krishna Chaitanya Rao brings a unique perspective to the Translational Data Analytics Institute (TDAI). As a Program Director, he will lead interdisciplinary research aligned with TDAI’s strategic focus areas and oversee the Master of Translational Data Analytics (MTDA) program, supporting student success through experiential learning, applied research, and workforce alignment.

Prior to joining Ohio State, Krishna led Responsible and Trustworthy AI initiatives at Vanguard, where he worked on embedding fairness, explainability, and governance frameworks into enterprise AI systems. At the University of Massachusetts Amherst, he focused on global partnerships, including international engagement to support educational research and workforce development, while designing and scaling experiential learning programs. Earlier, with the Government of Telangana, Krishna contributed to strengthening the innovation ecosystem, supporting startups, social innovation, and statewide digital education strategies. He is also the co-founder of an EdTech startup that focuses on expanding access to STEM and data-driven learning.

Krishna has co-authored the Springer Nature book Privacy in the Age of Innovation, holds international patents, and has judged over 25 global hackathons. He has reviewed 150+ papers for leading organizations and currently serves on various research / advisory boards and he is also recognized as a Top 1% Mentor by ADPList, early this year, he received the AIEA Harold Josephson Professional Promise Award for international education leadership. His expertise has earned him invitations to speak at global forums where he advocates for inclusive and ethical AI to broaden participation in STEM fields. Krishna holds a Ph.D. in Learning Sciences and Technology, with his dissertation exploring how informal learning environments such as computing-focused hackathons enhance self-efficacy, computational thinking, and innovation in STEM.