- Best Poster Award Runner-up, our poster “A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling” won the Best Poster Award Runner-up of Australasian Joint Conference on Artificial Intelligence (AJCAI) 2023.
- Best Paper Award, our paper “Grammar-guided Linear Genetic Programming for Dynamic Job Shop Scheduling” won the Best Paper Award of Genetic and Evolutionary Computation Conference (GECCO) 2023.
- 2023 Humies SILVER Award, presented at the Genetic and Evolutionary Computation Conference (GECCO) , “Learning Emergency Medical Dispatch Policies via Genetic Programming”, Humies SILVER Award, 2023.
- 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.
- Best Paper Runner-Up Award, our paper “Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling” won the Best Paper Runner-Up Award of Australasian Joint Conference on Artificial Intelligence (AJCAI) 2018.
• 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 55 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 an Associate Editor of Expert Systems With Applications. She is also a committee member of the IEEE NZ Central Section. She is the Secretary of IEEE New Zealand Central Section, treasurer of Young Professional Affinity Group, and the Secretary of Women-in-Engineering Affinity Group of IEEE NZ Central Section. She was the Chair of the IEEE Student Branch at VUW, the chair of Professional Activities Coordinator. In addition, she is the diversity chair and Post-Doc Member representative of AI Researchers Association.