I am a Ph.D. candidate in the Department of Management Science and Engineering at the Stanford University. Before joining Stanford, I was a Ph.D. student in the Department of Finance and Risk Engineering at the New York University from Sep 2024 - Aug 2025 and in the Epstein Department of Industrial and Systems Engineering at the University of Southern California from Aug 2021 - Aug 2024. I am fortunate to be co-advised by Prof. Renyuan Xu (Stanford) and Prof. Meisam Razaviyayn (USC). I obtained my B.S. in Mathematics from The Chinese University of Hong Kong, Shenzhen, where I was advised by Prof. Zizhuo Wang. Please find my CV here.
I am on the 2026-27 academic job market.
News
- 11/26: At the INFORMS Annual Meeting in San Francisco, I will co-chair the session Transport-based Generative AI (SB49, Nov 1), present Diffusion Models for Adaptive Sequential Data Generation in the Finance Section Best Student Paper finalist session (MA47, Nov 2), and present my research on generative diffusion models for decision-making in the Job Market Showcase (TB28, Nov 3).
- 10/26: Our paper Diffusion Models for Dynamic Volatility Surface Generation and Data-Driven Hedging is accepted by ICAIF 2026 (7th ACM International Conference on AI in Finance), Milan, Nov 14 - 17.
- 09/26: Our paper Diffusion Models for Adaptive Sequential Data Generation is selected as a finalist for the 2026 INFORMS Finance Section Best Student Paper Award.
- 09/26: Our preprint Diffusion Models for Dynamic Volatility Surface Generation and Data-Driven Hedging is available online; Code is released.
- 06/26: Our preprint Diffusion Models for Adaptive Sequential Data Generation is available online; Code is released.
- 06/26: I presented our work Diffusion Models for Adaptive Sequential Data Generation at SIAM Conference on Optimization (OP26) in Edinburgh, Jun 2 - 5.
- 05/26: I passed the PhD Area Qualification Exam at Stanford and advanced to PhD candidacy. 🎉
- 03/26: I presented our work Stochastic control for fine-tuning diffusion models at INFORMS Optimization Society Conference in Atlanta, Mar 20 - 22.
- 03/26: I presented our work Diffusion Models for Adaptive Sequential Data Generation at AFTLab PhD Student Workshop at Stanford, Mar 16.
- 12/25: I presented workshop posters Diffusion Models for Adapted Sequential Data Generation and Inexact Moreau Envelope Augmented Lagrangian Method for Nonconvex Robust Constrained Optimization at NeurIPS workshop 2025, Dec 6 - 7.
- 12/25: I co-organized a workshop on Generative AI in Finance at NeurIPS 2025 in San Diego, Dec 6.
- 10/25: I gave a talk on Diffusion Models for Adapted Sequential Data Generation at INFORMS Annual Meeting in Atlanta.
- 09/25: Our paper Inexact Moreau Envelope Augmented Lagrangian Method for Nonconvex Robust Constrained Optimization is accepted by NeurIPS 2025 Workshop on Constrained Optimization for Machine Learning.
- 09/25: Our paper Diffusion Models for Adapted Sequential Data Generation is accepted by NeurIPS 2025 Workshop MLxOR.
- 08/2025: The code for our paper Stochastic Control for Fine-tuning Diffusion Models is available online.
- 08/2025: We are co-organizing a workshop on Generative AI in Finance at NeurIPS 2025 in San Diego (Dec 6-7, 2025).
- 07/2025: I gave talks on Stochastic control for fine-tuning diffusion models at INFORMS Applied Probability Society Conference, International Conference on Machine Learning and International Conference on Continuous Optimization.
- 05/2025: Our paper Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity and Convergence is accepted by ICML 2025 for poster presentation.
- 04/2025: Our paper Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators is accepted by SIAM Journal on Control and Optimization.
- 12/2024: Our preprint Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity and Convergence is available online.
- 10/2024: I gave a talk titled Fine-tuning diffusion models: A stochastic control perspective at INFORMS Annual 2024, Seattle.
- 10/2024: I presented a poster at the Yale Sampling Conference, New Haven.
- 08/2024: I joined NYU Tandon and started a new journey here!
- 05/2024: I started my Research Scientist Intern at Meta, Sunnyvale.
- 05/2024: I presented a poster titled Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization at ICLR 2024, Vienna.
- 03/2024: I co-chaired a session with Meisam Razaviyayn and gave a talk titled Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization at INFORMS Optimization Society Conference.
- 01/2024: Our preprint Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization is available online.
- 01/2024: Our paper Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization is accepted by ICLR 2024 for poster presentation.
- 12/2023: I presented a poster titled Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization at NeurIPS 2023 Workshop on Diffusion Models.
- 10/2023: Our paper Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization is accepted by NeurIPS 2023 Workshop on Diffusion Models.
- 10/2023: I gave a talk titled Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization at INFORMS Annual 2023.
- 09/2023: Our paper Optimal Switching Policy for Batch Servers is available online.
- 09/2023: Our paper Optimal Switching Policy for Batch Servers is accepted by Operations Research Letters.
- 03/2023: Our paper Policy gradient converges to the globally optimal policy for nearly linear-quadratic regulators is submitted to SIAM Control and Optimization.
- 12/2022: Poster at NeurIPS 2022 Workshop OPT 2022.
- 10/2022: I gave a talk at INFORMS Annual Meeting 2022.