Welcome

I am a full stack ML engineer, builder, and open-source developer.

Currently, I am a software engineer, Infrastructure Lead, and the Technical Lead of the Core Engineering team at OpenEvidence, a healthcare technology startup developing conversational AI for physicians and healthcare professionals to enhance clinical decision-making at the point of care. OpenEvidence uses large language models (LLMs) as part of a larger AI system that can understand and synthesize the world's published biomedical research.

I received my PhD in Computer Science in 2021 at MIT in the Department of Electrical Engineering and Computer Science, where I was advised by Dr. Kalyan Veeramachaneni in the Data To AI group in the Laboratory for Information and Decision Systems.

My research has focused on machine learning, human-computer interaction, and software engineering. How can we create systems that enable people to do machine learning and data science more easily and effectively? How can we make machine learning and data science more collaborative in nature? Can we automate mundane or error-prone tasks in machine learning and data science? How can we make these areas more accessible to other domain experts? How can we expose data science and machine learning to the open-source development paradigm?

I've helped build and deploy ML models at small and large companies and have consulted on ML for clients in the finance industry and in academia. Check out my resume or my full CV.

Talk to me about software engineering, ML, and research... as well as cycling, chess, crosswords, BBQ, running, basketball, tennis, fantasy sports, cooking, house plants, books, trains, and politics...

You can also read my blog for various musings about the above.

Everything on this site reflects my personal views only.