“Can you find a list of people who are currently employed and working in machine learning/reinforcement learning in new york city who completed their physics phd in 2025 from an American University”
As of 2026-09-27, this sourced shortlist covers 7 publicly verifiable matches — each with a physics (or explicit physics-subfield, e.g. Applied Physics) PhD completed in 2025 at a U.S. university and a currently active ML, AI, deep-learning, or quantum-ML role at an NYC-based employer. It is not a full enumeration of everyone qualifying: public-profile discoverability limits coverage, and no candidate's public evidence specifically emphasized reinforcement learning, so this is an ML/AI set. Evidence spans 7 unique source URLs on 3 independent hosts; no URL backs more than one person.
Physics PhD, University of Chicago, completed 2025 (PhD student 2020 - 2025)
Senior Research Associate at JPMorgan Chase, New York, NY, start date Jul 2025
Researching spectral matrix-aware optimizers (machine-learning optimizers) and developing quantum optimization methods, including approaches demonstrated on trapped-ion hardware
Physics PhD, The University of Texas at Austin, completed 2025 (August 2019 – August 2025)
Flatiron Research Fellow at Simons Foundation (Flatiron Institute), New York City Metropolitan Area, August 2025 – Present
Machine learning in the current Flatiron research fellow role: designing, testing, and implementing models to interpret complex datasets through first-principles approaches, machine learning, and interpretable statistical techniques, alongside Bayesian methods for black-hole research
Physics PhD, New York University, completed May 2025 (PhD researcher September 2019 – May 2025)
Data Scientist at Citi, New York, New York, United States, starting January 2025 – Present
Leads acquisition response models (machine learning models) for Citi's proprietary credit cards (US) in the current Data Scientist role
Physics PhD, University of California, Berkeley, completed December 2025 (January 2020 – December 2025)
Data Scientist at Bank of America, New York, NY, start date May 2026
Building production ML systems on the Data & AI team, including designing a retrieval (RAG) system that adapts its response based on the similarity-score distribution and mapping a large production ML codebase
Ph.D. (Applied Physics), Harvard School of Engineering and Applied Sciences, completed 2025-01-14 (2019-09-01 to 2025-01-14)
Flatiron Institute, Flatiron Research Fellow (Center for Computational Mathematics), 2025-01-17 to present, New York, New York, US
Current research work involves deep learning and neural networks: AlphaFold as a prior — experimental structure determination conditioned on a pretrained neural network (Nature Methods, 2026-04), and SFCalculator: connecting deep generative models and crystallography
Physics PhD, Northeastern University, completed 2025 (2018 – 2025)
Postdoctoral Research Scientist at Columbia University, New York, New York, United States, March 2025 – Present
Developed and applied computational image analysis and machine learning tools to quantitatively analyze high-throughput drug testing experiments
Doctor of Philosophy - PhD Physics, University of Florida, 2021 – 2025
Founding Research Scientist at FlowSense AI, November 2025 – Present, New York, New York, United States
Developed scalable, accurate, and explainable computational models integrating theory with real-world mobility networks, and utilized graphically structured data to develop advanced geometric deep learning, sequence modeling, and network simulation methods for traffic analysis tools
| Person | 2025 PhD | Current NYC role | ML work | Source |
|---|---|---|---|---|
| Anuj Apte | Physics PhD, University of Chicago, completed 2025 (PhD student 2020 - 2025) | Senior Research Associate at JPMorgan Chase, New York, NY, start date Jul 2025 | Researching spectral matrix-aware optimizers (machine-learning optimizers) and developing quantum optimization methods, including approaches demonstrated on trapped-ion hardware | alphaxiv.org |
| Asad Hussain | Physics PhD, The University of Texas at Austin, completed 2025 (August 2019 – August 2025) | Flatiron Research Fellow at Simons Foundation (Flatiron Institute), New York City Metropolitan Area, August 2025 – Present | Machine learning in the current Flatiron research fellow role: designing, testing, and implementing models to interpret complex datasets through first-principles approaches, machine learning, and interpretable statistical techniques, alongside Bayesian methods for black-hole research | linkedin.com |
| Jatin Abacousnac | Physics PhD, New York University, completed May 2025 (PhD researcher September 2019 – May 2025) | Data Scientist at Citi, New York, New York, United States, starting January 2025 – Present | Leads acquisition response models (machine learning models) for Citi's proprietary credit cards (US) in the current Data Scientist role | linkedin.com |
| Krish Desai | Physics PhD, University of California, Berkeley, completed December 2025 (January 2020 – December 2025) | Data Scientist at Bank of America, New York, NY, start date May 2026 | Building production ML systems on the Data & AI team, including designing a retrieval (RAG) system that adapts its response based on the similarity-score distribution and mapping a large production ML codebase | linkedin.com |
| Minhuan Li | Ph.D. (Applied Physics), Harvard School of Engineering and Applied Sciences, completed 2025-01-14 (2019-09-01 to 2025-01-14) | Flatiron Institute, Flatiron Research Fellow (Center for Computational Mathematics), 2025-01-17 to present, New York, New York, US | Current research work involves deep learning and neural networks: AlphaFold as a prior — experimental structure determination conditioned on a pretrained neural network (Nature Methods, 2026-04), and SFCalculator: connecting deep generative models and crystallography | prereview.org |
| Rebecca Harman | Physics PhD, Northeastern University, completed 2025 (2018 – 2025) | Postdoctoral Research Scientist at Columbia University, New York, New York, United States, March 2025 – Present | Developed and applied computational image analysis and machine learning tools to quantitatively analyze high-throughput drug testing experiments | linkedin.com |
| Roy Thomas Forestano | Doctor of Philosophy - PhD Physics, University of Florida, 2021 – 2025 | Founding Research Scientist at FlowSense AI, November 2025 – Present, New York, New York, United States | Developed scalable, accurate, and explainable computational models integrating theory with real-world mobility networks, and utilized graphically structured data to develop advanced geometric deep learning, sequence modeling, and network simulation methods for traffic analysis tools | linkedin.com |
Sourced shortlist of 7 people, one row each, compiled as of 2026-09-27; evidence is largely self-reported public-profile material (LinkedIn, alphaXiv, PREreview — 3 independent hosts, one unique URL per row). Inclusion required a physics or physics-subfield PhD completed in 2025 at a U.S. university, a currently active role ("Present" or clearly current status) in New York City, and ML/AI/deep-learning work tied to that role. Applied Physics counts as a physics subfield. No RL-specific specialists were found; the set is described as ML/AI. Not an exhaustive enumeration — public discoverability limits coverage.