I am currently a Masters Student and Research Scholar at École Polytechnique Fédérale de Lausanne (EPFL), working at the intersection of graph machine learning and generative models, with Prof. Maria Brbic. Before this, I had the privilege of spending two exciting years as a Predoctoral Research Fellow at Microsoft Research India (MSR), where I was under the guidance of Arun Iyer and Sundarajan Sellamanickam. During my time at MSR, my research was centered around the integration of machine learning and graph-related problems, including supervised and unsupervised representation learning on graphs, spectral graph theory, and multi-behavior recommendation systems. I also had the opportunity to intern at Mila - Quebec AI Institute, where I contributed to the development of GFlowNets for the discovery of new drugs and vaccines. My work has been presented in papers at conferences such as NeurIPS, ICML, KDD, ECML PKDD and others. My primary interest lies in developing algorithmic and theoretical tools to enhance our understanding of machine learning and make it more robust and practical, especially in the context of graph data.
In the past, I have worked on various topics at different institutions, including Freie Universität Berlin, Indian Institute of Science (IISc), S20.AI, and as a Google Summer of Code Student Developer. I completed my undergraduate studies at the Indian Institute of Technology (IIT) Bhubaneswar in 2021.
When not staring at code, you can find me either on a basketball court, going for a run, playing the piano, or enjoying hikes. Feel free to reach out if you'd like to discuss any of the above. I'm open to all kinds of potential collaborations and conversations, be it discussions on representation learning theory to why I believe Jordan is the GOAT :).
