Austin Mroz
Member Of Technical Staff at CuspAI
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolAustin Mroz is a Schmidt AI in Science Research Fellow at Imperial College London with nine years’ experience at the intersection of experimental chemistry, materials discovery, and scalable AI. Trained as a mechanical engineer turned chemist with a PhD in physical chemistry, he develops data-driven closed-loop optimization algorithms, generative models, and highly efficient computational workflows that can reduce resource needs by up to a million-fold. He has led industry collaborations (BP-ICAM), secured over £60K in research funding, and built open-source tools and database structures to democratize AI-driven materials discovery. Beyond research, Austin co-directs a Women in AI network, teaches Bayesian optimisation to diverse audiences, and manages shared HPC/compute infrastructure—combining hands-on software and simulation engineering with practical lab collaboration to accelerate discovery.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Physical Chemistry, Doctor of Philosophy - PhD, Physical Chemistry at University of OregonMaster of Science - MS, Chemistry, Master of Science - MS, Chemistry at Rose-Hulman Institute of Technology
Github Skills (24)
molecule9
calculation9
chemistry8
electrical-engineering8
prediction-model8
molecular-simulation8
volumes7
power-systems7
renewable-energy7
science7
surface6
cheminformatics6
computational-chemistry6
recovery6
sampling6
Programming languages (3)
Github contributions (5)
ImperialCollegeLondon/webBO
Jun 2024 - Apr 2026
Contributions:1 review, 16 PRs, 20 pushes in 1 year 10 months
austin-mroz/SMORES
Aug 2022 - Mar 2023
Calculation of electric-field-based steric (Sterimol) parameters.
Contributions:1 release, 98 commits, 14 PRs in 7 months
power-systemsparametersrenewable-energychemistryscience
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