Toby Bischoff
Head Of Research at Aeolus Labs
United States
Summary
👤
Senior🎓
Top SchoolToby Bischoff is a research-driven machine learning leader with a decade of experience applying AI to hard physical problems, currently heading research efforts to model and design complex atmospheric and EV systems. He blends academic rigor—a Caltech PhD in atmospheric physics and applied math and Part III from Cambridge—with product-focused impact from roles at Microsoft and Ford, where he shipped scalable forecasting and MLOps solutions and filed multiple patents. Toby has co-founded open-science initiatives and built generative-AI tools for superresolution and simulation, routinely bridging first-principles modeling with modern ML. A pragmatic problem-solver who favors first-principles and leverage, he seeks out under-addressed, high-impact infrastructure work (the “10x data pipeline” problems) and communicates uncertainty candidly to drive decisions. Unusually, his background includes hands-on trades and large-scale event organization in Germany, reflecting a rare combination of physical craftsmanship, operational grit, and academic depth.
10 years of coding experience
8 years of employment as a software developer
Master of Advanced Study (Part III), Applied Mathematics, Theoretical Physics, Master of Advanced Study (Part III), Applied Mathematics, Theoretical Physics at University of CambridgeDoctor of Philosophy (PhD), Atmospheric Physics, Applied Mathematics, Computer Science, Doctor of Philosophy (PhD), Atmospheric Physics, Applied Mathematics, Computer Science at California Institute of Technology
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (64)
soil10
atmosphere10
carbon-emissions10
machine-learning10
climate-science10
earth10
climate-change10
noaa10
earth-science10
fluid-dynamics10
ocean10
julia10
optimization10
gpu9
forecast9
Programming languages (4)
Github contributions (5)
CliMA/OperatorFlux.jl
Jan 2022 - May 2022
Operator layers for Flux.jl that allow for the construction of Neural Operator models by using Flux's API. Useful for discretization-independent spatio-temporal ML models.
Contributions:3 reviews, 40 commits, 27 PRs in 4 months
deep-learningoperatorlayersfluxjulia
bischtob/paleoclimate-precipitation-model
Nov 2016 - Aug 2021
Contributions:9 pushes, 1 branch in 4 years 9 months
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