- 2022 SIGEVO Dissertation Award, Honorable Mention: “Genetic Programming Hyper-heuristics for Dynamic Flexible Job Shop Scheduling”
- Our new book published: “Genetic Programming for Production Scheduling: An Evolutionary Learning Approach”, Springer (XXXIII+338 pages, the first book on hyper-heuristic for production scheduling)
- [Best Paper Award] Our paper “An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling” won the Best Paper Award of European Conference on Genetic Programming (EuroGP) 2022.
• Job shop scheduling, hyper-heuristic learning / optimisation
• Artificial intelligence, machine learning
• Evolutionary computation, particularly genetic programming
• Transfer learning, multitask optimisation, multi-objective optimisation
• Feature selection, surrogate, genetic operators
Fangfang Zhang (Member, IEEE) received the B.Sc. and M.Sc. degrees from Shenzhen University, Shenzhen, China, in 2014 and 2017, respectively, and the Doctor of Philosophy in Computer Science from Victoria University of Wellington, Wellington, New Zealand, in 2021. She is currently a postdoctoral research fellow in computer science with the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. She has over 40 publications. Her current research interests include evolutionary computation, hyper-heuristic learning / optimisation, job shop scheduling, and multitask learning. Dr. Zhang is a member of the IEEE Computational Intelligence Society and Association for Computing Machinery, and has been severing as reviewers for top international journals such as the IEEE Transactions on Evolutionary Computation and the IEEE Transactions on Cybernetics, and conferences including the Genetic and Evolutionary Computation Conference and the IEEE Congress on Evolutionary Computation. She is also a committee member of the IEEE NZ Central Section. She is the Chair of the IEEE Student Branch at VUW, the chair of Professional Activities Coordinator, the treasurer of Young Professional Affinity Group, and a member of Women-in-Engineering Affinity Group of IEEE NZ Central Section. In addition, she is a member of AI Researchers Association.