Faculty and Staff

Vibhuti Gupta, Ph.D.

Assistant Professor of Computer Science and Data Science

Curriculum Vitae

NIH Biosketch

Education

Ph.D., Computer Science, Texas Tech University
M.Tech, Computer Science, SRM University
B.Tech., Computer Science, Bundelkhand Institute of Engineering and Technology


The primary research interests of Vibhuti Gupta, Ph.D. lie at the intersection of machine learning, trustworthy AI and medicine with an emphasis on new methods that lead to the safe, secure, responsible and meaningful adoption of machine learning in health care. Within machine learning, he is particularly interested in analyzing multimodal, and longitudinal time-varying data streams generated from digital health devices (i.e., mHealth apps, wearable devices) and utilizing that information for early diagnosis and prevention of complex human diseases. The overarching goal of his research is to develop the computational methods and tools required to organize, process, and transform health care data into actionable knowledge, along with considerations of explainability, ethics, and fairness.

Dr. Gupta received his Ph.D. from Texas Tech University in 2019 where he worked with Prof. Rattikorn Hewett and his research focused on developing an adaptive and scalable Big stream data pre-processing approach that leverages AI techniques and is adaptable to different data rates and data types.

He joined Meharry as an assistant professor in 2021. He has served as PI in American Cancer Society (ACS) DCRIDG pilot award, NIH AIM-AHEAD, NSF ExpandAI CAP, and Co-I in NSF MRI, RCMI Supplement and NASA MEUREP awards. Dr. Gupta has published more than 30 papers at reputed international journals including Cell, JMIR, IEEE sensors and in top international conferences sponsored by IEEE, and ACM.

Research Interests

Developing scalable preprocessing and large-scale machine learning techniques for big data streams, data mining, natural language processing, information retrieval, application of deep learning in healthcare, distributed computing, and mHealth wearable sensor data analytics.

Research Labs

mHealth Wearables Sensors Lab