Alican Bozkurt
Senior AI Scientist at Paige
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolAlican Bozkurt is a Senior AI Scientist at Paige with 12 years of experience applying Bayesian nonparametrics and deep learning to biomedical image analysis. He holds a PhD in Electrical and Computer Engineering and has progressed from doctoral research to industry R&D, including an internship at Uber and multi-year research roles at Paige. Alican contributes to prominent open-source probabilistic programming work—improving robustness and features in pyro, including NaN/Inf handling, locality-sensitive hashing for tracking, and a ZeroInflatedPoisson distribution—which reflects his focus on reliable, production-ready Bayesian tools. He blends theoretical depth with practical engineering, routinely turning advanced inference techniques into robust code and imaging solutions. Based in New York, he is motivated by solving real-world clinical imaging problems where uncertainty-aware models make a measurable impact.
12 years of coding experience
2 years of employment as a software developer
MSc, Electrical & Electronics Engineering, MSc, Electrical & Electronics Engineering at Bilkent UniversityDoctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at Northeastern UniversityIB, Math(HL), Chemistry(HL), Physics(HL), Turkish A1(SL), English A2(SL), Biology(SL), IB, Math(HL), Chemistry(HL), Physics(HL), Turkish A1(SL), English A2(SL), Biology(SL) at TED Ankara College Foundation High School
Stackoverflow
38reputation
3kreached
1answer
1question
Github Skills (13)
pytorch10
machine-learning10
deeplearning-ai10
bayesian10
probabilistic-programming10
deep-learning10
python10
bayesian-inference10
testing8
keras6
command-line-interface6
tensorflow6
python-click6
Programming languages (10)
Github contributions (5)
pyro-ppl/pyro
Jun 2018 - Aug 2018
Deep universal probabilistic programming with Python and PyTorch
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 13 PRs, 50 pushes in 2 months
Contributions summary:Alican primarily contributed to the `pyro-ppl/pyro` repository by refactoring and enhancing existing code related to NaN/Inf handling within the probabilistic modeling framework. Their contributions involved modifying core utility functions and integrating NaN/Inf checks throughout the codebase, specifically in modules related to Bayesian inference, and probabilistic programming. Furthermore, the user added features related to locality-sensitive hashing for approximate occupancy queries within the contrib.tracking module and the implementation of a ZeroInflatedPoisson distribution. These changes suggest a focus on improving the robustness and functionality of the probabilistic programming library.
probabilistic-programmingpythonpytorchmachine-learningbayesian
alicanb/website
Feb 2021 - Mar 2026
🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify
Contributions:9 pushes, 1 branch in 5 years 1 month
hugoeducational-websitenetlifyhugo-themesum
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