Doruk Gökmen

Postdoctoral Researcher at NSF-Simons National Institute for Theory and Mathematics in Biology

Switzerland
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Summary

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Doruk Gökmen is a postdoctoral researcher based in Switzerland with eight years of interdisciplinary experience at the intersection of statistical physics, machine learning, and soft-matter/biological physics. He developed a renormalisation group algorithm grounded in lossy compression theory during his doctoral work at ETH Zürich, blending information theory with practical computational methods. Currently affiliated with the University of Chicago and a fellow at the NSF-Simons NITMB, he investigates how emergent, low-dimensional languages capture collective behaviors distinct from microscopic descriptions. His background spans theory, hands-on quantum and photonics experiments, and teaching, giving him a rare combination of mathematical rigor and experimental intuition. Known for framing complex phenomena in terms of concise emergent concepts, he often brings ideas from machine learning to bear on fundamental physics problems.
code8 years of coding experience
job5 years of employment as a software developer
bookMEB Bilim ve Sanat Merkezi
bookBachelor of Science (BSc) Physics, Bachelor of Science (BSc) Physics at Bilkent University
bookDoctor of Sciences (Dr. sc. nat.) Theoretical and Mathematical Physics, Doctor of Sciences (Dr. sc. nat.) Theoretical and Mathematical Physics at ETH Zürich
languagesJapanese, German, Latin
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Github Skills (21)

gnn9
autoencoder9
manifold8
optimizers8
machine-learning6
python6
tensorflow5
deep-learning5
graph5
spin4
mechanics4
ising-model4
statistical-mechanics4
monte-carlo4
matlab3

Programming languages (3)

Jupyter NotebookPythonMatlab

Github contributions (5)

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dgoekmen/dgoekmen.github.io

Aug 2018 - Mar 2019

Contributions:5 PRs, 73 pushes, 10 branches in 6 months
Illustrating various topics in classical and quantum statistical mechanics through Monte Carlo simulations.
Contributions:4 PRs, 89 pushes, 5 branches in 6 months
quantum-mechanicsquantum-computingstatisticalsimulationsmonte-carlo
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