In this episode, I converse with Shubhendu Trivedi, who's currently a Machine Learning Researcher at MIT CSAIL, where he works with Prof. Regina Barzilay and Prof. Tommi Jaakkola as part of the MIT Machine Learning for Pharmaceutical Discovery and Synthesis Consortium (MLPDS). Prior to that he was the NSF sponsored Institute Fellow at Brown University's Institute for Computational and Experimental Research in Mathematics and completed a PhD on group covariant neural networks at the Toyota Technological Institute at Chicago and the University of Chicago.

Shubhendu's research particularly focuses on causal learning and representation learning for graph-structured data, with a particular focus on applications to drug discovery. We talk about his fantastic journey in science, being there at the pivotal moment when the deep learning revolution took off, phenomenal mentors who guided him through academia and life, the unique characteristics of research in academia and industry, dealing with issues of bias and ethics in AI systems, his eclectic reading interests and obsession with collecting books, and many more things!!