About Me
I am currently associate quantum computing researcher at JPMorgan Chase & Co..
Previously I received my Ph.D. in Computer Science from Pennsylvania State University.
- Advisors: Mehrdad Mahdavi, Chunhao Wang
My research focuses on developing both classical and quantum algorithms for large-scale sampling and optimization, with an emphasis on provable performance guarantees.
You can find my CV here.
See also: Google Scholar, Linkedin, Github.
Research Interests
Optimization, Sampling, Theoretical Computer Science, Quantum Computing
Publications and Preprints
- Dylan Herman, Guneykan Ozgul, Anuj Apt, Junhyung Lyle Kim, Anupam Prakash, Jiayu Shen, Shouvanik Chakrabarti. Mechanisms for Quantum Advantage in Global Optimization of Nonconvex Functions, 2025. [preprint Arxiv 2510.03385]
- Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang. Quantum Speedups for Markov Chain Monte Carlo Methods with Application to Optimization, 2025. [preprint Arxiv 2504.03626]
- Shouvanik Chakrabarti, Dylan Herman, Guneykan Ozgul, Shuchen Zhu, Brandon Augustino, Tianyi Hao, Zichang He, Ruslan Shaydulin, Marco Pistoia. Generalized Short Path Algorithms: Towards Super-Quadratic Speedup over Markov Chain Search for Combinatorial Optimization. [TQC 2025]
- Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang. Stochastic quantum sampling for non-logconcave distributions and estimating partition functions. [ICML 2024]
Education
Ph.D. Computer Science and Engineering, Pennsylvania State University, 2021-2025 Dissertation: Quantum Algorithms for Markov Chain Methods In Machine Learning and Optimization (link)
B.S. Computer Engineering / Physics, Boğaziçi University, 2012-2018
Teaching
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CMPSC 448 (Machine Learning and Algorithmic AI), Spring 2023, TA
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CMPSC 497 (Introduction to Quantum Computing), Fall 2022, TA
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CMPSC 448 (Machine Learning and Algorithmic AI), Spring 2022, TA
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CMPSC 497 (Introduction to Quantum Computing), Fall 2021, TA