Since September 2025, I have been a Visiting Professor at Bloomberg AI in Finance, where I am collaborating on a research initiative that applies machine learning and agent-based modeling to advance the study of fixed-income markets. I am an Assistant Professor in the Department of Applied Mathematics and Statistics and an Affiliated Faculty in the Institute for Advanced Computational Science, at Stony Brook University. My research is on statistical learning and machine learning methods with applications in engineering, medicine, and finance.
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I co-organize two webinars in the department see the Webinars & Workshops tab above.
More details on my work can be found under Publications tab and Research & Students tab above.
If you want to stay up to date with the most recent news from the department, follow our LinkedIn Page
Prospective Students: I am seeking Ph.D. students with a strong foundation in mathematics, statistics, physics, and/or computer science. Prior experience or training in finance is not required. Prospective students may apply to the Ph.D. program in Applied Mathematics & Statistics at Stony Brook University and reference my name in their application. Please reachout to me via email to discuss potential funding opportunties and support.
Application Instructions: Email Subject: Use "PhD Application-Semester-Year" (e.g., "PhD Application-Fall-2025"). Email Content: Include your CV and all academic transcripts. Your CV should clearly indicate your GPA and relevant academic achievements.
Important Notes: All emails will be reviewed; however, responses to individual inquiries may not be guaranteed. Please refrain from sending multiple inquiries, as this will not expedite the process.
For Current Stony Brook Students: Email your CV to arrange an in-person meeting.
Preferred Qualifications: M.S. degree in Applied Mathematics, Statistics, Operations Research, Quantitative Finance, Computer Science, or Physics. Success in competitive environments such as Kaggle competitions, hackathons, or mathematics and programming contests. Relevant experience in trading and investment activities. Previous internships at recognized institutions, with clear descriptions of responsibilities and specific achievements.
Self-Funded Interns & Visiting Scholars: Applications from self-funded interns and visiting students or scholars interested in collaborative research are welcome.
News & Updates
News & Updates
see my recent LinkedIn activity for most recent news
https://www.linkedin.com/in/pawelpolaknyc/recent-activity/all/
General Updates (2023-2025)
Highlights:
Since September 2025, I have been a Visiting Professor at Bloomberg AI in Finance, where I am collaborating on a research initiative that applies machine learning and agent-based modeling to advance the study of fixed-income markets
Research Excellence: CVPR 2024 (Top 1 Computer Science Conference) Highlight Paper (Top ~2.8% of total submissions), three NeurIPS Workshops (Top 1 Machine Learning Conference) Papers (2024 Machine Learning in Optimization, 2023 Physics, 2023 Medicine).
Top 10 US Quant & Finance Professors 2023 by Rebellion Research (https://www.rebellionresearch.com/top-10-2023-us-quant-finance-professors)
Research Supported by Prestigious Grants: Department of the Air Force, Department of Energy, Bloomberg, and various quantitative hedge funds.
Invited Presentations: Stanford University, George Mason University, SQA Annual Conference (x2), Fidelity Investment Boston, Bloomberg Quant Seminar NYC, Thalesian Seminar Fordham University, QWAFAxNEW Society of Quantitative Finance NYC.
Workshops Organized:
Alphathon 2024 & 2025: Collaboration with CEWIT and SQA, sponsors: AllianceBernstein, Point72/Cubist, Principal, Optimal Portfolio Strategies.
Recent Trends in Quantitative Finance Workshops: Third, Second (Stony Brook University), First (with University of Florida).
ADDRESS
ADDRESS
Department of Applied Mathematics and Statistics
Stony Brook University
Stony Brook, NY 11794
CONTACT INFO
CONTACT INFO
Email: pawel.polak@stonybrook.edu
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