Ingmar Schuster
CEO And Cofounder at Provolut
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolIngmar Schuster is a machine learning-driven founder and CEO with 14 years of experience translating advanced statistical research into high-impact products. After a PhD and postdoctoral work on sampling, MCMC and RKHS estimators, he led applied ML teams at Zalando building time-series, RL and anomaly-detection solutions and then cofounded Provolut to apply those methods to protein engineering. At Provolut he built, on a shoestring, one of the first ML-first enzyme design apps that cuts R&D experiments roughly 16× while improving performance across food, biotech and medical applications. He combines deep technical expertise in Bayesian and kernel methods with practical product sense and operational leadership, plus hands-on experience deploying ML in logistics and pandemic response. Based in Berlin, he’s equally at home discussing model inference details or client-facing strategy, and brings an unusual mix of linguistics, engineering and psychology-informed communication to cross-disciplinary teams.
13 years of coding experience
7 years of employment as a software developer
Engineer’s Degree, Computer Science, A, Engineer’s Degree, Computer Science, A at University of TübingenDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Leipzig University
English, French, German, Italian, Chinese
Github Skills (98)
probabilistic-programming10
python10
mcmc10
gpu10
bayesian-inference10
jax10
probability10
distributions10
gaussian-processes10
automatic-differentiation10
bayesian10
composable10
jit10
autodiff10
pytorch10
Programming languages (4)
Github contributions (5)
ingmarschuster/Rpository
Jun 2012 - Jan 2014
Contributions:26 commits in 1 year 7 months
journalrepositoriesrstatscran
zalandoresearch/JaxRK
Feb 2020 - Jun 2021
RKHS feature vectors, operators, and statistical models using JAX for automatic differentiation
Contributions:2 releases, 118 commits, 6 PRs in 1 year 4 months
automatic-differentiationdifferentiationvectorsstatisticalmachine-learning
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