Summary
Mehmet Caglar is a data scientist with a PhD in Physics and a decade of experience building end-to-end ML solutions at the intersection of academia and industry, currently working at Meta in Austin. He specializes in anomaly detection for high-dimensional, incomplete time-series, context-aware text classification, noisy-label correction, and model explainability, bringing rigorous statistical and information-theoretic methods to applied problems. Mehmet has led data science teams in financial services and conducted postdoctoral research using machine learning to model microbial behavior, showing an unusual blend of domain-driven research and production impact. He has a track record of independent research (see his Google Scholar) and experience integrating multi-omics and heterogeneous data sources from his academic work. Colleagues know him for turning complex, noisy datasets into interpretable models that inform decisions rather than just improving metrics.
10 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (PhD) Physics, Doctor of Philosophy (PhD) Physics at Texas Tech University
Master of Science (M.S.) Physics, Master of Science (M.S.) Physics at Orta Doğu Teknik Üniversitesi / Middle East Technical University
English, Turkish