Sergei Kliavinek
Doctoral Student at Caltech
Pasadena, California, United States
Summary
👤
Senior🎓
Top SchoolSergei Kliavinek is a doctoral student in materials science at Caltech with nine years of experience applying computational methods to complex materials problems. His background spans MD simulations of metallic glass transitions, high-performance computing internships, and computational science research at EPFL, blending deep physics intuition with strong numerical and coding skills. He specializes in modeling electronic and atomic-scale phenomena, bringing practical experience from national supercomputing centers and interdisciplinary academic labs. Based in Pasadena, Sergei combines rigorous training from MIPT and EPFL with a knack for translating theoretical models into scalable simulations—often optimizing code to run efficiently on modern HPC architectures.
9 years of coding experience
California Institute of TechnologyMaster of Science - MS, Computational Science and Engineering, 5.4/6, Master of Science - MS, Computational Science and Engineering, 5.4/6 at Ecole polytechnique fédérale de LausanneHonors Bachelor, Applied Mathematics and Physics, 3.85/4, Honors Bachelor, Applied Mathematics and Physics, 3.85/4 at Московский Физико-Технический Институт (Государственный Университет) (МФТИ)High School Diploma, High School Diploma at Saint Petersburg Lyceum 239
Russian, English
Github Skills (45)
data-analysis10
benchmark10
continuous-integration10
python10
data-science10
scikit10
statistics10
machine-learning10
benchmarking10
performance-testing10
regression10
regression-testing10
scikit-learn10
portable9
hdf9
Programming languages (5)
Github contributions (5)
hurricane642/reframe
Jul 2021 - Sep 2021
A powerful Python framework for writing and running portable regression tests and benchmarks for HPC systems.
Contributions:6 PRs, 103 pushes, 16 branches in 2 months
regressionpythonbenchmarkingbenchmarkbenchmarks
hurricane642/scikit-learn
Apr 2021 - Jun 2021
scikit-learn: machine learning in Python
Contributions:3 reviews, 1 PR, 16 pushes in 1 month
pythondata-sciencelearn-machine-learningsklearnmachine-learning
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