LIU Yilu

LIU Yilu

Ph.D. Candidate at CityUHK

Profile

I am currently a final-year Ph.D. student at Department of Computer Science, City University of Hong Kong (CityUHK), where I am very fortunate to be advised by Prof. ZHANG Qingfu.

Before joining CityUHK, I received my B.Eng and M.Eng degrees from School of Artificial Intelligence, Xidian University, in 2020 and 2023, respectively. During this period, I was advised by Prof. LIU Jing and spent seven delightful years in Xi'an and Guangzhou.

My current research interests can be summarized as "Few for Many", i.e., using limited resources to collaboratively addressing a large number of similar demands, mainly including:

  • Multi-Objective Optimization: Find few solutions to optimize many objectives.
  • Computational Social Science: Find few social members to serve many others.
  • Automated Algorithm Design: Design few algorithms to solve many problem instances.

Selected Publications

Journal Article

  1. [TEVC'25] Yilu Liu, Xi Lin, Liang Zhao, and Qingfu Zhang, "Few for many: Towards efficient and flexible many-objective optimization."
    IEEE Transactions on Evolutionary Computation (IF: 15.9, 2026) (Code)
  2. [TEVC'25] Yilu Liu, Xi Lin, and Qingfu Zhang, "Leader-follower disagreement minimization in social networks."
    IEEE Transactions on Evolutionary Computation (IF: 15.9, 2026)
  3. [TEVC'24] Yilu Liu, Qingfu Zhang, and Zhenkun Wang, "Community opinion maximization in social networks."
    IEEE Transactions on Evolutionary Computation (IF: 15.9, 2026)
  4. [INS'23] Yilu Liu, Jing Liu, and Kai Wu, "Cost-effective competition on social networks: A multi-objective optimization perspective."
    Information Sciences (IF: 6.0, 2026)
  5. [SWEVO'22] Yilu Liu, Jing Liu, and Xiangyi Teng, "Single-particle optimization for network embedding preserving both local and global information."
    Swarm and Evolutionary Computation (IF: 9.6, 2026)

Conference Paper

  1. [IJCAI'26] Yilu Liu, Bo Xue, Yiming Yao, and Qingfu Zhang, "Opinion maximization in social networks: An inverse optimization perspective."
    International Joint Conference on Artificial Intelligence (CCF-B, 2026)
  2. [PPSN'24] Yilu Liu, Chengyu Lu, Xi Lin, and Qingfu Zhang, "Many-objective cover problem: Discovering few solutions to cover many objectives."
    International Conference on Parallel Problem Solving from Nature (CCF-B, 2026) (Code)
  3. [AAAI'26] Fei Liu (Co-First), Yilu Liu (Co-First), Qingfu Zhang, Xialiang Tong, and Mingxuan Yuan, "EoH-S: Evolution of heuristic set using LLMs for automated heuristic design."
    Annual AAAI Conference on Artificial Intelligence (CCF-A, 2026) (Code)
  4. [ICLR'25] Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, and Qingfu Zhang, "Few for many: Tchebycheff set scalarization for many-objective optimization."
    International Conference on Learning Representations (CCF-A, 2026) (Code)
  5. [CEC'24] Chengyu Lu, Yilu Liu, and Qingfu Zhang, "MOEA/D-CMA made better with (1+1)-CMA-ES."
    IEEE Congress on Evolutionary Computation (CCF-C, 2026) (Best Student Paper Award)

Selected Awards

Ph.D. Stage

  • Research Tuition Scholarship, City University of Hong Kong, 2026.
    (One of the 15 recipients selected among 355 Ph.D. students in computer science)
  • Research Tuition Scholarship, City University of Hong Kong, 2025.
    (One of the 24 recipients selected among 351 Ph.D. students in computer science)
  • Best Student Paper Award, IEEE Congress on Evolutionary Computation, 2024.
    (The sole one selected among 343 accepted papers)

M.Eng. Stage

  • National Scholarship, Xidian University, 2022. (Top 1%)
  • Social Scholarship, Xidian University, 2022. (Top 1%)

B.Eng. Stage

  • Provincial First Prize, China Undergraduate Mathematical Contest in Modeling, 2018.
  • Outstanding Student, Xidian University, 2018. (Top 5%)

Services

Reviewer

Teaching Assistant

Residence Management