Volodymyr Kuleshov

Assistant Professor
Computer Science

Biography

My research focuses on machine learning and its applications in science, health, and sustainability. It involves two high-level directions:

• Core research in machine learning, specifically: generative models, probabilistic methods, approximate inference, decision-making under uncertainty. ICML18 ICML19 NeurIPS22 ICLR23
• The development of machine learning techniques that support new technologies that improve human and environmental health. Previous projects focused on genome sequencing, machine reading, and reducing food waste. Nature Biotech. 14 Nature Biotech. 16 Nature Comm. 19 Nature Medicine 19

I am also involved in commercializing my research. I co-founded Afresh, a startup that uses AI to significantly drive down food waste—a major environmental problem. Afresh is now deployed in about 10% of US supermarkets. My earlier work on genome sequencing was commercialized by the Stanford spin-off Moleculo, and became part of Illumina’s genome phasing service.

I obtained my PhD from Stanford, where I was the recipient of the Arthur Samuel Best Thesis Award. I worked with Stefano Ermon, Serafim Batzoglou, Michael Snyder, Christopher Re, and Percy Liang.