His current research interests include computational intelligence, reinforcement learning, operations research, evolutionary algorithm, hyper-heuristics, modelling, scheduling and optimisation with a special focus on transportation systems and healthcare. He supervised a team of students and software engineers that has successfully tackled a challenging truck dispatching problem in Ningbo-Zhou Port, reduced the operations significantly.

Prof. Ruibin Bai holds BSc and MSc degrees from Northwestern Polytechnic University, China and a PhD from University of Nottingham UK. He joined the University of Nottingham Ningbo China (UNNC) in 2007 after spending 2 years as a postdoctoral research fellow at the University of Nottingham, UK. He is now a professor and Head of the School of Computer Science and an IEEE senior member. He leads the Artificial Intelligence and Optimisation (AIOP) group with more than 20 academics of diverse background from Computer Science, Engineering and Business School. The group promotes collaborations between AI, Engineering and Operations Research communities. He is the Director of the Intelligent Simulation and Digital Port Lab.

I have experience in teaching the following courses at UG level.

• AE1CSA: Computer System Architectures (2007-2013)
• AE1UST: Unix Software and Tools (2007-2008)
• AE1DBS: Database Systems (2007-2015)
• AE1PRG: Programming (2014-2015)
• AE1IMO: Introduction to Modelling and Optimisation (2014-2015)
• AE2OSC: Operating System and Concurrency (2015-2017)
• AE3IDS/J: Individual Dissertation Single/Joint Honours (2014-2017)
• AE2AIM: Artificial Intelligence Methods. (2017-2020)

I am the first supervisor for the following PhD students.

1. Yuchang Zhang: Deep Reinforcement Learning Hyper-heuristics for Port Optimisations, Started in 2016.
2. Chaofan Tu: Deep Reinforcement Learning for Combinatorial Optimisation. Started in 2017.
3. Menglin Cui: Robust and Interpretable medical text mining. Started in 2017.
4. Jiandong Liu: Multi-objective evolutionary algorithm for medical text mining. Started in 2017.
5. Xinan Chen: Data-Driven Genetic Programming Hyper-heuristic. Started in 2019.
6. Jiahuan Jin: Deep Reinforcement Learning in Combinatorial Optimisation. Started in 2019.
7. Shihe Wang: Machine Learning and Applications. Started in 2019.
8. Huayan Zhang: Deep Reinforcement Learning for Combinatorial Optimisation. Started in 2020.
9. Wentao He: Image Understanding and Reasoning. Started in 2020.
10. Chenglin Yao: Face Spoofing and Detection. Started in 2020.
11. Junsong Zhu: Dynamic scheduling in transportation and production. Started in 2021.

I have supervised the following PhD students to completion as the first supervisor.

1. Jianjun Chen: An intelligent container transportation system using novel modelling, metaheuristics and automatic dispatching strategy, Gradated in 2016.
2. Tianxiang Cui: Hybridising Metaheuristics and Exact Methods For Portfolio Optimisation Problem. Graduated in 2016.
3. Ning Xue: Modelling and advanced optimisation methods for the multi-shift full truckload vehicle routing problem, Graduated in January 2017.
4. Xiang Li: Life Cycle Based Decision Support for Sustainable Automotive Engineering and Energy Planning, to Graduated in May 2017.
5. Xia Li: Travel Time Prediction Using Ensemble Learning Algorithms, Graduated in July 2018.
6. Xiaoping Jiang: Stochastic Service Network Design for Transportation Planning of Consolidation Carriers, to finish in May. 2020
7. Shuhui Gong: Spatio-temporal modeling and prediction on travel behaviour analysis. Graduated in 2020.