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Kai YanPh.D. StudentDepartment of Computer ScienceUniversity of Illinois Urbana ChampaignOffice: CSL 130, 1308 W Main St, Urbana, IL 61801, United StatesEmail: kaiyan3 [at] illinois [dot] edu |
"We choose to go to the Moon in this decade and do the other things, not because they're easy, but because they're hard."
-- John F. Kennedy, 1962
Who am I?
Hi there! I am Kai Yan (颜开 in Chinese), a second-year Ph.D. student in the Department of Computer Science at University of Illinois Urbana-Champaign (UIUC), co-advised by Prof. Alexander Schwing and Prof. Yu-Xiong Wang. Prior to that, I get my Bachelor of Science degree in computer science at Peking University with a Summa Cum Laude and a national scholarship. In my high school years, I learned informatics and got a silver award in the National Olympiad of Informatics (NOI 2016).
My research interest is deep learning for better decision making, which is mainly deep reinforcement learning and imitation learning. I have conducted research in the following fields: 1) optimization with prediction, 2) multi-agent reinforcement learning, 3) demonstration-guided reinforcement learning and imitation learning, 4) decision transformer, and 5) Large Language Model (LLM)+MCTS.
You can check my CV, Github and Linkedin here. Don’t forget to check your daily tips at the top of this page!
Publications
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yuxiong Wang. Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models, In ICML, 2024. [PDF][Website]
Kai Yan, Alexander G. Schwing and Yuxiong Wang. Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching. In ICML, 2024. [PDF]
Kai Yan, Alexander G. Schwing and Yuxiong Wang. A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories. In NeurIPS, 2023. [PDF][Website]
Kai Yan, Alexander G. Schwing and Yuxiong Wang. CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations. In NeurIPS, 2022. [PDF][Website]
Kai Yan, Jie Yan, Chuan Luo, Liting Chen, Qingwei Lin and Dongmei Zhang. A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints. In NeurIPS, 2021. [PDF]
Preprints
Kai Yan*, Zhenggang Tang*, Liting Sun, Wei Zhan, Changliu Liu. A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning. arXiv:2108.06589, 2021.[PDF]
Kai Yan*, Yunlong Lu*. Algorithms in Multi-Agent Systems: A Holistic Perspective from Reinforcement Learning and Game Theory. arXiv:2001.06487, 2020. [PDF]
* Equal Contributions.
Working Experiences
I worked in Microsoft Research Asia mentored by Dr. Jie Yan and Chuan Luo from Sept. 2020 to Jun. 2021, and was awarded Stars of Tomorrow.
Teaching Experiences
I was a teaching assistant for Introduction to Computer Systems (Fall 2019) at Peking University, where I led a seminar of 15 people every week, revising and expaning lessons taught in class, grading homeworks, and teaching how to write lecture notes.
Photos with Students and Teacher
Other Experiences
I served for the department of outreach in the EECS Student Union of Peking University in 2017-2018, and as the vice president of the EECS Student Union in the academic year of 2018-2019. We have organized awesome events with hundreds of participants, such as Hackathon and Freshmen Ball.
Photos of Our Hackathon
Hey, you find my easter egg! I am a lover of strategic PC games, such as Frostpunk, Civilization, Stellaris, Hearts of Iron, Victoria and Total Wars. That’s also something where you need to make good decisions :)