Kuber Shahi

Hey, thanks for stopping by!

I work across the full ML stack, from building distributed data pipelines to training and deploying language and vision models, turning messy real-world problems into production-ready ML systems.

Currently, I’m a Graduate Researcher at UCSD’s Biomedical Image Analysis Group, where I investigate uncertainty quantification for medical image registration, while broadening my ML expertise at UC San Diego through coursework spanning Statistical NLP, Computer Vision, AI Agents, and ML Systems. My work is driven by my research interests in LLM-based reasoning, agentic AI, medical image analysis, and NLP, and I enjoy working on problems that require both creativity and technical depth, especially where real-world impact is involved.

Last summer, I was a Machine Learning Intern at Melio, a blood diagnostics biotech startup, where I got to work at the intersection of MLOps and healthcare, rebuilding fragmented research workflows into a robust, production-grade ML training infrastructure for blood diagnostic time series classification. Before that, I spent two years as a Data Scientist at Vayana Network, India’s largest trade credit and supply chain financing fintech, where I built large-scale data infrastructure to streamline invoice processing, developed graph-based tools to uncover customer networks driving business growth, and led an NLP-based entity resolution system to deduplicate and enrich company records, improving data quality at scale.

My ML foundations go back to undergrad at Ashoka University, where I graduated with honors in CS with a minor in Physics, and did early research in privacy-preserving ML and adversarial attacks with Professors Mahavir Jhawar and Debayan Gupta.

Outside of work and research, I’m a big Chelsea FC fan and follow football closely, alongside cricket and Formula 1 occasionally. I also enjoy science fiction, mystery, and thriller films, and like to swim and hike in my free time.