Jesse Michel is a founding research scientist and roboticist with 11 years of experience blending deep theory and practical systems engineering across ML, differentiable programming, and physics-based simulation. He recently finished a PhD at MIT where he extended distribution theory to make physical simulations and rendering differentiable end-to-end, spanning math, semantics, compiler work, and numerical integration. Jesse has a strong industry track record from internships at Google, Microsoft, IBM, ASAPP and clinical and biotech analytics projects, bringing both production engineering and research rigor to product contexts. At Tutor Intelligence he applies that cross-disciplinary expertise to build "robot brains" that tightly couple data, models, and systems. He pairs a pure math and CS background with hands-on experience in compilers, large-model compression, and simulation, which lets him move fluidly between abstract proofs and shipping code. Notably, his work emphasizes formal foundations for practical compute—making theoretically grounded tools that scale to real-world pipelines.
11 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at Massachusetts Institute of Technology
An Elegant Neural Network User Interface to build drag-and-drop neural networks, train in the browser, visualize during training, and export to Python.
Contributions:387 commits, 2 pushes, 1 comment in 2 years
user-interfacepythontensorflowjsbrowserexport
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Jesse Michel - Founding Research Scientist at Tutor Intelligence