We are the LAMDA-BBO (Black-Box Optimization) group, led by Professor Chao Qian. Our group is a part of LAMDA Group @ Nanjing University, which is led by Professor Zhi-Hua Zhou.
Our research focuses on advancing the theories, algorithms, and applications of black-box optimization. Our key areas of interest include, but are not limited to:
- Theoretical analysis of evolutionary algorithms
- Designing safe evolutionary algorithms, i.e., evolutionary algorithms with provable approximation guarantee
- Designing efficient black-box optimization algorithms, e.g., Bayesian optimization, evolutionary strategies, evolutionary gradient optimization, and cooperative coevolution
- Learning to optimize, e.g., learning to configure, generate and select black-box optimzition algorithms, offline optimization, and neural combinatorial optimization
- Evolutionary learning, particularly evolutionary reinforcement learning, deep learning, and ensemble learning
- Applications to solve complex real-world optimziation problems in industry (e.g., electronic design automation) and science (e.g., geoscience)
