Key Publications (*=Corresponding Author, ABC=Equal Contribution, see my scholor page for more)
Zhan JJ, Ma Z, et al. Learning Where, What and How to Transfer: A Multi-Role Reinforcement Learning Approach for Evolutionary Multitasking. IEEE TEVC, 2026. [paper, code]
Wang C, Ma S, Ma Z, et al. Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model. ICML, 2026. [paper, code]
Wang C, Gong Y J, Cao Z and Ma Z*. Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering. AAAI, 2026. [paper, code]
Qiu W J, Guo H S, Ma Z, Zhang J and Gong Y J. 自动黑箱优化算法设计：进展与挑战. 计算机学报, 2026. [paper]
Ma Z, Huang W, Song G H, et al. Evolutionary System 2 Reasoning: An Empirical Proof. AAAI, 2026. [paper, code]
Ma Z, Gong Y J, Guo H, et al. LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation. IEEE TEVC, 2026. [paper, code]
Ma Z, Gong Y J, Guo H, et al. MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization. NeurIPS, 2025. [paper, code]
Guo H, Ma Z, Ma Y, et al. DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization. NeurIPS, 2025. [paper, code]
Ma Z, Guo H, Gong Y J, et al. Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization. IEEE TEVC, 2025. [paper, code]
Ma Z, Cao Z, Jiang Z, et al. Meta-Black-Box-Optimization Through Offline Q-function Learning. ICML, 2025. [paper, code]
Ma Z, Chen J, Guo H, et al. Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization. ICLR, 2025. [paper, code]
Guo H, Ma Z, Chen J, et al. ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning. AAAI, 2025. [paper, code]
Ma Z, Chen J, Guo H, et al. Auto-Configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning. ACM GECCO, 2024. [paper, code]
Guo H, Ma Y, Ma Z, et al. Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution. IEEE TSMC, 2024. [paper, code]
Chen J, Ma Z, Guo H, et al. SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning. ICLR, 2024. [paper, code]
Ma Z, Guo H, Chen J, et al. Metabox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning. NeurIPS, 2023. [paper, code]
Invited Talks
NICE Student Seminar(2025-06-02), NeurELA and Q-Mamba.
AITIME AAAI 2025 Pre-Talk, ConfigX.
AITIME ICLR 2024 Pre-Talk, SYMBOL.
AITIME NeurIPS 2023 Pre-Talk, MetaBox.
Services
Journal of Intelligent and Sustainable Systems (JISS), Associate Editor (2025-present)
NeurIPS Reviewers (2024, 2025, 2026*)
AAAI Reviewers (2025, 2026)
ICML Reviewers (2025, 2026)
ICLR Reviewers (2025,2026)
IJCAI Reviewers (2026)
IEEE TCDS Reviewers (2024-present)
IEEE TEVC Reviewers (2024-present)
IEEE TETCI Reviewers (2025-present)
IEEE TII Reviewers (2026-present)
Elsevier SWEVO Reviewers (2026-present)