Hello, I am Fei Liu, a Postdoc researcher in Department of Physics, UZH & Department of Mathematics, ETH Zurich, working with Prof. Nicola Serra and Prof. Alessio Figalli.

I was a Postdoc Fellow in Prof. Qingfu Zhang’s Group, Department of Computer Science, City University of Hong Kong.

I completed my PhD degree at CityU supervised by Prof. Qingfu Zhang, my master’s and bachelor’s degrees at Northwestern Polytechnical University supervised by Prof. Zhonghua Han.

I am currently interested in automatic algorithm design, artificial intelligence, optimization algorithm and their applications on real-world problems.

You can found my CV in this link
For more information, you can visit my Google Scholar , ResearchGate, and Github

🔥 News

2026.02: 🎉🎉 We won the Champion of the CVRPLib BKS Competition using Automated Algorithm Design!
2026.02: 🎉🎉 We won the Champion of the GECCO Competition on LLM for Evolutionary Algorithm Design!
2026.01: 🎉🎉 Our Survey Paper “A Systematic Survey on Large Language Models for Algorithm Design” has been accepted by ACM Computing Surveys !
2025.10: 🎉🎉 I had the opportunity to Give a keynote talk on IJCCI 2025 !
2025.06: 🎉🎉 We had the opportunity to present a Tutorial on Automated Algorithm Design with Large Language Models at CEC 2025! The tutorial slides are available here.!
2025.03: 🎉🎉 We had the opportunity to present a Tutorial on Algorithm Design with Large Language Models at EMO 2025! The tutorial slides are available here.!
2025.01: 🎉🎉 Platform LLM4AD has received IEEE FLAME Second Prize (Only One)!
2024.12: 🎉🎉 Paper “LLM4AD: A Platform for Algorithm Design with Large Language Model” is online !
2024.10: 🎉🎉 Survey Paper “A Systematic Survey on Large Language Models for Algorithm Design” is online !
2024.09: 🎉🎉 “Evolve Cost-aware Acquisition Functions Using Large Language Models” has been nominated as PPSN 2024 Best Paper Candidate!
2024.08: 🎉🎉 IEEE HK CI Postgraduate Student Research Paper Competition CHAMPION!
2024.05: 🎉🎉 “Evolution of Heuristics: Towards Efficient Automatic Algorithm Design using Large Language Model” has been accepted at ICML 2024 (Oral) 1.5% accept rate.

📝 Publications

ICML 2024

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design using Large Language Model

Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang

Visit Google Scholar for full paper list.

💻 Projects

🎖 Honors and Awards

2025.09: Champion, GECCO LLM for Evolutionary Algorithm Design Competition
2025.01: IEEE FLAME Competition 2024 Second Price (only one)
2024.08: Champion, IEEE HK CI Postgraduate Student Research Paper Competition 2024 CHAMPION
2021.03 Gold Award, EMO 2021 HUAWEI Logistic Competition
2020.03 Outstanding master’s thesis, CSAA

💼 Experience

2026.02 - now, Postdoc, UZH & ETH Zurich
2025.02 - 2026.01, Postdoc, City University of Hong Kong

📖 Educations

2020.09 - 2025.02, PhD, City University of Hong Kong
2017.09 - 2020.06, Master, Northwestern Polytechnical University
2013.09 - 2017.07, Undergraduate, Northwestern Polytechnical University

🎤 Talks

2025.10, Conference Keynote: “Automated Algorithm Design with Large Language Model”, IJCCI.
2025.06, IEEE Webinar: Large Language Model for Algorithm Design Video and Slides
2025.05, 基于大模型的自动算法设计 Automated Algorithm Design with Large Language Model, NICE Seminal, 视频Video (Chinese)

📚 Tutorials and Workshops

2026.08, LLMs for Optimization: From Automated Modeling to Algorithmic Discovery, IJCAI Tutorial 2026
2026.08, LEAD: The First International Workshop on Learning-assisted Algorithm Design, IJCAI Workshop 2026
2025.06, Tutorial on Automated Algorithm Design with Large Language Models, CEC 2025. The tutorial slides are available here
2025.03, Tutorial on Algorithm Design with Large Language Models, EMO 2025!

📝 Paper List

Visit Google Scholar for full paper list.

Selected Papers

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Xi Lin, Zhe Zhao, Xialiang Tong, Kun Mao, Zhichao Lu, Zhenkun Wang, Mingxuan Yuan, and Qingfu Zhang. “A systematic survey on large language models for algorithm design.” ACM Computing Surveys, 2026
Fei Liu, Yilu Liu*, Qingfu Zhang, Xialiang Tong, and Mingxuan Yuan. “EoH-S: Evolu- tion of heuristic set using LLMs for automated heuristic design” AAAI, 2026 (Oral)
Shunyu Yao*, Fei Liu*, Xi Lin, Zhichao Lu, Zhenkun Wang, and Qingfu Zhang. Multi-objective Evolution of Heuristic Using Large Language Model. AAAI, 2025 (Oral)
Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, and Qingfu Zhang. Evolution of heuristics: towards efficient automatic algorithm design using large language model. ICML, 2024 (Oral Top 1.5%)
Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, and Mingxuan Yuan. Prompt learning for generalized vehicle routing. IJCAI, 2024
Fei Liu, Xi Lin, Qingfu Zhang, Xialiang Tong, and Mingxuan Yuan. Multi-task learning for routing problem with cross-problem zero-shot generalization. SIGKDD, 2024
Fei Liu, Qingfu Zhang, Qingling Zhu, Xialiang Tong, and Mingxuan Yuan. Machine learning assisted multiobjective evolutionary algorithm for routing and packing. IEEE Transactions on Evolutionary Computation, 2024
Yu Zhang, Kefeng Zheng, Fei Liu#, Qingfu Zhang, and Zhenkun Wang. AutoTurb: Using Large Language Models for Automatic Algebraic Model Discovery of Turbulence Closure. Physics of Fluid 2025.