I am currently pursuing my MSc in Computer Science at University of British Columbia, Vancouver working in the domain of Graph Neural Networks and Molecular Modelling. I am supervised by Jiarui Ding (UBC) and Dominique Beaini (MILA, Valence Labs).
Interests.
- Graph Neural Networks
- Drug Discovery
- Generative Modelling
- ML Engineering
Get in touch.
[CV][Email] [Linkedin] [Twitter] [Github] [Google Scholar]
FAQ
[2023-Current] Research Intern @ Valence Labs (powered by Recursion Pharmaceuticals)
I am working on my master’s thesis in collaboration with Valence labs. The focus of my work is understanding and building machine learning potentials for improved atomistic simulations. I am working on the following projects,
- Role of Structural and Conformational diversity for ML potentials.
- Improving Molecular Conformer Generation with Flow Matching and Pre-trained Potentials [WIP]
[AI4D3, AI4S NeurIPS’23][Arxiv][Poster][Code]
[2020-2022] Associate Machine Learning Scientist @ WadhwaniAI
Worked on various social impact ML projects (AI-based Early Pest Warning System, Cough Against Covid) actively building machine learning and engineering pipelines for rapid experimentation and smooth deployment.
Our work was published at AI for Public Health Workshop, ICLR and Challenges in deploying and monitoring ML systems workshop, NeurIPS 2022.
[Summer-2019] Data Science Intern @ Elucidata (elucidata.io)
Building web-based tools for RNAseq analysis.
[Summer-2018] Research Intern @ National Tsing Hua University, Taiwan
Worked on affinity score prediction using drug docking software, Autodock Vina.
[2022-Current] MSc (Thesis) in Computer Science @ University of British Columbia, Vancouver
[2016-2020] B.Tech in Biochemical Engineering @ Indian Institute of Technology, Delhi
