Education

Ph.D at Yale University, 2026, Advisor: Dr. Hongyu Zhao; Committee: Dr. Rex Ying; Dr. Yuval Kluger
M.S. at Yale University, 2025
B.S. with highest honor at University of Illinois at Urbana-Champaign (UIUC), 2022
B.E. with outstanding student at Zhejiang University (ZJU), 2022

Research experience

September 2022 - Now: Research assistant at Yale
- Participating in the research group focusing on AI, Comp Bio, and Drug Discovery.
- Advisor: Zhao Hongyu
- Co-authors: Zhang Le, Strittmatter Stephen, Ying Rex, Luo Xiao, Sun Yizhou, Huang Kexin, Xu Hua, Zheng Wenjin, Zou James, Mahmood Faisal, Jin Wengong, Zitnik Marinka, Pinello Luca, Chen Qingyu.
September 2021 - August 2022: ECE 397 (Individual Research) at UIUC
- Participating in Open Problems in scRNA-seq competition: https://openproblems.bio.
- Advisor: Shomorony Ilan
- Teammates: Greenberg Grant
March 2021 - September 2022: Visiting student at Yale University
- Trying to utilize GAN to reduce batch effect in scRNA-seq data.
- Trying to utilize auto-encoder model to mutually predict gene expression data and protein data.
- Advisor: Zhao Hongyu
- Teammates: Wang Yuge
March 2020 - August 2021: SRTP at Zhejiang University
- National project
- Progress of Minimally Invasive Surgical Robots
- Professor: Yang Liangjing
- Teammates: Chang Junyu, Wang Chongyu
July 2019 - August 2019: HKU summer school
- MATH1641: Mathematical Laboratory and Modeling
- Instructor: WONG Chi Wing & LAW, Ka Ho
- Got A score and scholarship

May - August 2025: Research Internship
- Broad Institute
- Mentor: Jin Wengong.
May - August 2024: Research Internship
- Genentech
- Machine Learning Department
- Mentor: Graham Heimberg, Regev Aviv.
May - June 2022: Research Internship
- Biomap
- Computational biology research institute supported by Baidu
- Bioinformatics scientist
March - September 2020: Research Internship
- DiDi
- AI Labs
- Mentor: Zhang Lingyu
- topic: Research in solutions for manpower scheduling problem, combining with machine learning theory.

January - May 2024: Teaching Assistant in Biomedical NLP
- Yale University
- Mentor: Xu Hua, Chen Qingyu
- topic: Organize discussion sections related to biomedical NLP and grade students’ homework and exams.
Septermber - December 2024: Teaching Assistant in Linear Models
- Yale University
- Mentor: Ma Zongming
- topic: Organize discussion sections related to linear models and grade students’ homework and exams.
February - May 2022: Teaching Assistant in Differential Equations (Plus)
- Zhejiang University
- Mentor: Honold Thomas
- topic: Organize discussion sections related to calculus and grade students’ homework and exams.
Septermber - December 2021: Teaching Assistant in Digital Signal Processing Lab
- University of Illinois at Urbana-Champaign
- Mentor: Corey Ethan Snyder
- topic: Grade students’ lab reports.
Septermber - December 2020: Teaching Assistant in Calculus I
- Zhejiang University
- Mentor: Zhou Cui
- topic: Organize discussion sections related to calculus and grade students’ homework, quizes, and midterms.

UIUC:
- Core course: Introduction to Computer Science, Introduction to Computing.
- Core course: Computer Systems & Programming, Digital Systems Laboratory, Computer System Engineering, Discrete Mathematics, Data Structure, Analog Signal Processing, Digital Signal Processing, Data Science and Application, Introduction to Algorithms and Computing Model, Multimedia Signal Processing.
- Core course: Statistical Learning (with Graduate Students), Introduction to Bioinformatics (with Graduate Students), Bioinformatics and Statistical Tools (with Graduate Students), Database Systems (with Graduate Students), Biosensors (with Graduate Students).
- Math course: Calculus, Real Variables, Abstract Linear Algebra (with Graduate Students), Differential Equations (Plus), Probability Theory and Statistics, Biostatistics.
- Optional course: Microeconomics, Rhetoric and Composition.
Yale:
- Core course: Intermediate Machine Learning, Statistical Inference, Linear Models, Foundation of Epidemiology, High-Dimensional Phenomena in Statistics and Learning, Trustworthy Deep Learning, Longitudinal and Multilevel Data Analysis, Theory of Survival Analysis, Theory of Generalized Linear Models, AI and Foundation Models, Statistical Methods for Causal Inference, Immunology, Cancer, Core Topics in Bioinformatics.