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Education
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2024 Ph.D. in Electrical Engineering
California Institute of Technology, California, United States - Advised by Prof. Yisong Yue.
- Thesis Understanding and Improving Reliability of Inference Dynamics in Deep Neural Networks.
- Research Interest: Post-training, Test-time Compute & Reasoning, LLMs, Diffusion Models, Controllable Generation
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2017 B.E. in Opto-electronics Information Science and Engineering
Zhejiang University, Hangzhou, China - Member of Advanced Honors Class of Engineering (ACEE), Chu Kochen Honors College
- Chu Kochen Scholarship (highest honor for Zhejiang University undergrads, 12/5400).
Work Experience
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2024 - now Quantitative Researcher
Citadel Securities, Miami, FL - Designs and implements feature engineering pipelines and deep learning models to identify predictive signals in large-scale, noisy financial time-series data.
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2020 - 2022 Research Intern (part-time)
NVIDIA Research, Santa Clara, CA - Hosted by Zhiding Yu and Weili Nie.
- Invented neural networks with recurrent generative feedback to improve robustness and worked on diffusion models.
Honors and Awards
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2017 - Top 10 Academic Achievements of Zhejiang University
- Chu Kochen Scholarship (highest honor for Zhejiang University undergrads, 12/5400)
Teaching
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2019, 2020, 2021 Teaching Assistant
CS165: Foundations in Machine Learning and Statistical Inference, Caltech -
2018 Teaching Assistant
EE151: Electromagnetic Engineering, Caltech
Professional Services
- Journal Reviewer: JMLR, ARTNT
- Conference Reviewer NeurIPS, ICML, ICLR, WFVML