Tolga Dinçer is a Systems and Security Operations Engineer with a PhD in Physics and a decade of experience building scalable, secure compute platforms and ML pipelines. Based in New York, he combines academic rigor from astrophysics research with practical infrastructure engineering—designing bare-metal Kubernetes clusters with MAAS/Juju, integrating Slurm, and delivering resilient JupyterHub and on-premise GPU services. He has implemented end-to-end ML solutions (PyTorch, MLflow, LangChain RAG) for real-world workflows, including a seal-counting app and Whisper-based transcription running on university supercomputers. His background in astronomy and data science shows up in careful signal-processing, experiment tracking, and reproducible pipelines for high-throughput science. Colleagues appreciate that he translates messy documentation and heterogeneous systems into usable, automated services that improve transparency and user productivity.
10 years of coding experience
7 years of employment as a software developer
Master of Science - MS Astronomy, Master of Science - MS Astronomy at Istanbul University
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at Sabanci University
DataJoint Element for behavioral analysis with Facemap
Contributions:23 reviews, 96 commits, 12 PRs in 7 months
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