Philipp Spitzer
Research Lab Lead Applied AI In Services KSRI WIN at Karlsruher Institut für Technologie (KIT)
Karlsruhe, Baden-Württemberg, Germany
Summary
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Senior🎓
Top SchoolPhilipp Spitzer is an applied AI and data science leader with nine years of experience translating machine learning research into industrial impact across automotive and manufacturing domains. Currently Research Lab Lead Applied AI in Services at KSRI/WIN while also serving as Senior Data Scientist at Trelleborg, he blends academic rigor from his KIT PhD work with hands-on product-focused ML solutions. His background includes forecasting and reinforcement learning prototypes for Daimler, production-optimization projects, and applied analytics at Fujitsu, evidencing strength in time series, predictive maintenance, and human–machine collaboration. Known for bridging research and deployment, he routinely moves models from prototypes to business value in cross-disciplinary teams. Based in Karlsruhe, he brings a systems-level view of industrial engineering informed by international research experience and practical internships.
9 years of coding experience
5 years of employment as a software developer
Research Internship, Environmental Science, Research Internship, Environmental Science at University of North Carolina at CharlotteMaster of Science (M.Sc.), Industrial Engineering, Master of Science (M.Sc.), Industrial Engineering at Karlsruhe Institute of Technology (KIT)Industrial Engineering, Industrial Engineering at California State University-Long Beach
German, English
Github Skills (111)
package-management10
python10
stochastic10
connectivity10
multi-objective-optimization10
covariance10
snappy10
cpp10
adaptation10
computation10
cpp-library10
conan10
slicer10
connections10
gcode10
Programming languages (6)
Github contributions (5)
phbasler/libcmaes
Sep 2020 - Dec 2024
libcmaes is a multithreaded C++11 library with Python bindings for high performance blackbox stochastic optimization using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy
Contributions:11 PRs, 91 pushes, 15 branches in 4 years 3 months
evolutionpythonstrategymatrixcma-es
phbasler/BSMPT
Mar 2018 - Jan 2023
BSMPT - Beyond the Standard Model Phase Transitions : A C++ package for the computation of the EWPT in BSM models
Contributions:15 releases, 179 reviews, 603 commits in 4 years 11 months
computationcppbsmtransitionsbeyond-the-standard-model
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