Ph.D. Candidate · Tsinghua University
Qianyi Chen 陈谦益
Qianyi /tʃjɛn ˈiː/
I develop reliable and practical statistical methods for decision-making in complex systems.
I am a final-year Ph.D. student in Management Science and Engineering at the School of Economics and Management, Tsinghua University, advised by Prof. Bo Li. My research sits at the intersection of causal inference, machine learning, and uncertainty quantification.
- Based in
- Beijing, China
- Research focus
- Causal inference · Uncertainty quantification
Research
My goal is to build effective, scalable, sample-efficient, and easy-to-implement methodology for complex systems.
Causal inference
Experimental design, estimation, and policy learning for settings where complex interactions exist.
Uncertainty quantification
Conformal prediction with substantially improved conditional coverage.
Selected work
Publications & Preprints
Academic community
Service, teaching & experience
Reviewing
NeurIPS (2024–2025), ICLR (2025–2026), ICML (2025–2026), and AISTATS (2024).
Teaching
Teaching Assistant for Probability and Statistics at Tsinghua University, Fall 2022–2025, working with Prof. Bo Li and Prof. Xiaojie Mao.
Industry research
Research intern and algorithm developer at Tencent WeChat (2022–2023).
Machine Learning algorithm engineer intern at ByteDance (2021).
Education
B.Eng. in Industrial Engineering with a minor in Data Science and Engineering, Tsinghua University.
Contact
Interested in research conversations.
cqy22 [at] mails [dot] tsinghua [dot] edu [dot] cn