About

Current Role

I work as a Research Engineer on the Foundational Research Incubation team at Google DeepMind.

Startups

I was the co-founder of Dice Health, a startup that built AI-based tools for solving administrative tasks in veterinary healthcare. I started Dice in late 2023 with my co-founder and friend Abdullah. We were bootstrapped and profitable from Day 1 and grew Dice to a team of 4 over 2 years. We sold Dice to one of our enterprise PMS customers in early 2025.

I am also the creator of Awesome-MLSS, an open-source project I have been running since 2018 that curates summer schools in the field of machine learning. It has grown from a single markdown file on GitHub to a website, newsletter, and a community of over 50K annual visitors and 1000+ subscribers.

Research & Engineering

Before starting Dice, I worked at Meta (Facebook) AI Research with Dr. Ari Morcos on scaling laws, self-supervised computer vision, and foundation models.

Prior to Meta, I was at the Vector Institute, working with Prof Graham Taylor at the Machine Learning Research Group on conditional computation in neural networks, visual reasoning, and dynamic neural networks.

Even further back, I was a research assistant at the Visual Computing Lab at the Indian Institute of Science working with Prof Anirban Chakraborty and Prof Anand Mishra, working on visual question answering, entity re-identification, and object detection.

I also have several years of experience in machine learning and computer vision engineering working with Vector Institute, NEXT-AI Toronto, Layer6 AI Toronto, Shell R&D Center Bangalore, HyperWorks Imaging Bangalore, & Samsung Research Institute Delhi.

Consulting

I work as an independent consultant providing technical expertise to companies on building and scaling data pipelines for training large ML models, large model training and inference optimization, building fine-tuning and evaluation systems for AI solutions, and building production-ready GenAI applications.

In the past, I also served as a technical advisor to Vector Institute and a scientist-in-residence with NEXT Canada where I advised various startups as well as established companies on AI model development, deployment, and strategy.

I have worked with companies ranging from pre-seed startups to Fortune 500, across industries including FinTech, Climate Tech, MedTech, Broadcasting, AI Safety, and Oil & Gas.

See my Contact page for more details on past engagements and to book a consultation.

Education

I did my master's degree in Electrical and Computer Engineering at the University of Guelph, with a specialization in Artificial Intelligence. I wrote my master's thesis on dynamic neural networks and cognitive science. You can read it here: Inductive Biases for Higher-Order Visual Cognition.

I did my bachelor's in Electronics and Communication Engineering from Indian Institute of Technology Dhanbad.

Contact

Book a call with me on my Contact page, or reach out via the links in the sidebar.