Shachi Deshpande (शची देशपांडे)

I am a PhD candidate in the Department of Computer Science at Cornell University. I am presently working at Cornell Tech in New York. I am advised by Prof. Volodymyr Kuleshov.

My research focuses on causal machine learning, probabilistic models and uncertainty estimation. During my PhD, I developed novel generative architectures to incorporate rich, unstructured information in modern datasets within the framework of causal inference. I also work on improving the reliability of predictive uncertainties in probabilistic models in the context of causal inference, deep learning and sequential decision-making. I am interested in applications of my research to the identification of causal genetic variants in genome-wide association studies and performing accurate uncertainty quantification of polygenic risk scores in humans.

I graduated with BTech in Computer Science from Indian Institute of Technology, Bombay, where I worked on online query optimization in databases with Prof S. Sudarshan and on empirical evaluation of derivative clouds with Prof Umesh Bellur. I also worked with Prof Bernard Moret as a Summer@EPFL scholar.