We are a research team mainly focus on the Evolutionary Computing, Deep Reinforcement Learning, Black Box Optimization and Meta Black Box Optimization. We belong to the Computational Intelligence Lab, School of Computer Science, South China University of Technology. We are an energetic team including undergraduate students, master students and phd students. The student leader in this team is Zeyuan Ma, a phd student at South China University of Technology. Students in MetaEvo are advised (in part advised) by Prof. Yue-Jiao Gong. This is a pure research-oriented technical team, aiming to develop the new generation of black-box-optimization concepts, algorithms, frameworks and benchmarks. The resulting research domain is commonly named as Meta-Black-Box-Optimization, which generally mitigates the labour-intensive development in traditional black-box optimization algorithms through meta-learning an update rule/algorithmic configuration at the meta level. We believe works done in this team would promote the study edge of both evolutionary computing and optimization.

1. "MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning." Advances in Neural Information Processing Systems 36 (NeurIPS 2023, Oral).
2. "Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning" (ICLR 2024).
3. "Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning" The Genetic and Evolutionary Computation Conference (GECCO 2024).
4. "Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization." IEEE Transactions on Evolutionary Computation (TEVC) (2025).
5. "Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution" IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC) (2024).
6. "ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning" (AAAI 2025, Oral).
7. "Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization" (ICLR 2025).
8. "Meta-Black-Box-Optimization through Offline Q-function Learning" (ICML 2025).
9. "MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization" (NeurIPS 2025).
10. "DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization" (NeurIPS 2025).
11. "Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering" (AAAI 2026).

Feel free to discuss with us!

We are available on E-mail: 1、scut.crazynicolas@gmail.com 2、wukongqwj@gmail.com

We warmly invite you to join our QQ group for further communication (Group Number: 952185139).