About me

I am a Staff Machine Learning Researcher at SandboxAQ. My team's focus is on developing causal foundation models for efficient drug discovery. I have developed novel probabilistic graph algorithms to assist with biomarker discovery and designing cargo for mRNA-based cancer vaccines.

I worked as a Scientist at Microsoft Research (2021-2024). I have been a core contributor to MSR's Project Science Engine. My work was on advancing Generative AI, Graph Neural Networks for Genomics and designing efficient Large Language Models for enterprise using high performance computing techniques.

I was fortunate to be the first PhD in Machine Learning graduate from Georgia Tech (2016-2020). My advisors were Prof. Srinivas Aluru and Prof. Le Song.  My thesis was titled "On using inductive biases for designing deep learning architectures".

In the past, I have been a scientist at Xerox Research (2014-2016). I developed methods to solve the class imbalance problem in ML and designed AI devices for ICU patient monitoring.

My undergrad degree was in Electronics & ECE from Indian Institute of Technology Kharagpur (2009-2014). I enjoy swimming and racquet sports like squash, tennis & badminton.

Email: contact [at] harshshrivastava [dot] com