Anna Thomas
Director, Machine Learning
Anna Thomas is Director of Machine Learning at FSI, where she leads the development of AI systems for efficiently designing sustainable protein formulations.
“The intersection of AI and sustainable protein design contains both fascinating technical challenges and the potential for significant impact on human and planetary health.”
Biography
Anna Thomas is Director of Machine Learning at FSI and a current PhD candidate in Computer Science at Stanford University. She co-leads a project at FSI, supported by the Bezos Earth Fund’s AI for Climate and Nature Grand Challenge, to develop open-source AI systems for sustainable protein development.
Anna earned her B.S. in Mathematics from Stanford University, with a minor in Computer Science, and holds a Master’s degree in Mathematical Statistics (Part III of the Mathematical Tripos) from the University of Cambridge, where she was a Churchill Scholar. She has also been supported by the Stanford Data Science Scholars Fellowship, NECTAR Fellowship, and NSF Graduate Research Fellowship. Her work has been published in ICML, NeurIPS, and Nature Food.
Areas of Expertise
LLMs and optimization algorithms for accelerating scientific discovery
Formulation design and sensory prediction for sustainable proteins
Speaking Engagements
Stanford Food Systems Symposium (January 2026)
Good Food Institute Science of Alternative Protein Seminar (August 2025)
Pangborn Sensory Science Symposium (August 2025)