Jha, a fourth-year graduate student, combines artificial intelligence with statistical neuroscience toward a goal of improving both disciplines. In particular, she studies probabilistic machine learning tools that help scientists contend with the massive data sets produced by increasingly sophisticated neural experiments. These analytic tools help design more efficient experiments and extract richer information from the data those experiments produce. To the extent this research leads to a deeper understanding of the brain, Jha said, those insights could in turn drive key developments in AI.

The Google Ph.D. fellowship program began in 2009 and has since supported nearly 700 graduate students working in computer science and related disciplines. This year’s fellows receive three years of funding as well as mentorship through Google’s network of research scientists. The 2022 cohort includes more than 60 graduate students studying topics across 14 research categories, including computational neural and cognitive sciences.

In 2021, Jha won the department’s Pramod Subramanyan *17 Early Career Graduate Award, and as a first-year graduate student in 2019 she won a Thomas J. Nelson *68 Fellowship from the School of Engineering and Applied Science. She earned her bachelor’s degree from the Indian Institute of Technology-Delhi, where she received a Cargill Global Scholarship. Jha is advised by Jonathan Pillow, professor psychology and neuroscience, an expert in extracting information from complex neural data.