Fangfang Zhang
Scholar

Fangfang Zhang

Google Scholar ID: ekOoMH0AAAAJ
Lecturer of Artificial Intelligence, Victoria University of Wellington, New Zealand
Evolutionary ComputationGenetic ProgrammingHyper-heuristicsMultitask LearningJob Shop
Citations & Impact
All-time
Citations
2,468
 
H-index
25
 
i10-index
41
 
Publications
20
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • - 2025 SIGEVO Dissertation Award, Honorable Mention: Meng Xu's dissertation “Advancing Genetic Programming for Learning Scheduling Heuristics” ($1,000 USD)
  • - IEEE CIS Outstanding PhD Dissertation Award, 2025: “Genetic Programming Hyper-heuristics for Dynamic Flexible Job Shop Scheduling” ($1,000 USD)
  • - 2023 Humies SILVER Award: “Learning Emergency Medical Dispatch Policies via Genetic Programming”, presented at GECCO 2023 ($2,000 USD)
  • - Best Paper Award: “Grammar-guided Linear Genetic Programming for Dynamic Job Shop Scheduling” at GECCO 2023
  • - New book published: “Genetic Programming for Production Scheduling: An Evolutionary Learning Approach”, Springer
  • - Other awards include Best Presentation Awards, Best Poster Awards, etc.
Research Experience
  • Currently serving as a Lecturer in Artificial Intelligence at Victoria University of Wellington and involved in multiple research projects.
Education
  • B.Sc. from Shenzhen University, 2014; M.Sc. from Shenzhen University, 2017; Ph.D. in Computer Science from Victoria University of Wellington, 2021.
Background
  • Research Interests: 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. Biography: Dr. Fangfang Zhang (Member, IEEE) is a Lecturer in Artificial Intelligence with the Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science, Victoria University of Wellington.
Miscellany
  • Personal motto: For doing research, “Think Big, Start Small, Move Fast!”
Co-authors
0 total
Co-authors: 0 (list not available)