Dr Zekun Guo

Dr Zekun Guo

Lecturer in Electrical Engineering, Postgraduate Research Director for DAIM

Faculty and Department

  • Faculty of Science and Engineering
  • Data Science AI and Modelling Centre (DAIM)

Qualifications

  • BEng (Shandong University)
  • MRes (University of Edinburgh)
  • PhD / DPhil (Brunel University London)

Summary

Dr. Zekun Guo, is a Lecturer and Postgraduate Research Director at the Centre of Excellence for Data Science, Artificial Intelligence, and Modelling (DAIM) at the University of Hull. He earned his PhD in Electronic and Electrical Engineering from Brunel University of London in September 2023. He began his PhD at Cranfield University on November 1, 2019, and transferred to Brunel University on August 1, 2021. Dr. Guo holds an MSc by Research in Energy Systems (2019) from the University of Edinburgh and a B.Eng in Energy and Environmental System Engineering (2018) from Shandong University.

At DAIM, Dr. Guo leads the Large Language Model (LLM) Agent Research Team, pioneering the development of LLM-based multi-agent systems. His work focuses on creating innovative vertical AI Agent applications in biology, healthcare, engineering, and business, with an emphasis on enhancing the safety, efficiency, and problem-solving capabilities of multi-agent frameworks.

Dr. Guo is leading the design and delivery of the MSc AI for Engineering variant programme. As part of this programme, he developed its core module, AI-Driven Optimization and Control, integrating cutting-edge AI technologies into engineering practices to address industrial challenges.

Teaching MSc Data Science and Artificial Intelligence:

- Module - Applied Artificial Intelligence, 2024

- Module - MSc Research Project, 2024

Leading in Development of MSc Artificial Intelligence for Engineering Variant programme

- Module - Artificial Intelligence Driven Optimisation and Control, 2025

Recent outputs

View more outputs

Journal Article

Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach

Ren, X., Lai, C. S., Guo, Z., & Taylor, G. (2024). Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/TCE.2024.3482101

A Carbon Emission Allowance Bargaining Model For Energy Transactions Among Prosumers

Xiang, Y., Qing, G., Fang, M., Li, Z., Yao, H., Liu, J., Guo, Z., Liu, J., & Zeng, P. (2024). A Carbon Emission Allowance Bargaining Model For Energy Transactions Among Prosumers. IEEE Transactions on Power Systems, https://doi.org/10.1109/TPWRS.2024.3388251

Multi-Objective Optimization for Solar-Hydrogen-Battery-Integrated Electric Vehicle Charging Stations with Energy Exchange

Duan, L., Guo, Z., Taylor, G., & Lai, C. S. (2023). Multi-Objective Optimization for Solar-Hydrogen-Battery-Integrated Electric Vehicle Charging Stations with Energy Exchange. Electronics, 12(19), Article 4149. https://doi.org/10.3390/electronics12194149

Infrastructure planning for airport microgrid integrated with electric aircraft and parking lot electric vehicles

Guo, Z., Li, B., Taylor, G., & Zhang, X. (2023). Infrastructure planning for airport microgrid integrated with electric aircraft and parking lot electric vehicles. eTransportation, 17, Article 100257. https://doi.org/10.1016/j.etran.2023.100257

Techno-economic assessment of wireless charging systems for airport electric shuttle buses

Guo, Z., Lai, C. S., Luk, P., & Zhang, X. (2023). Techno-economic assessment of wireless charging systems for airport electric shuttle buses. Journal of Energy Storage, 64, Article 107123. https://doi.org/10.1016/j.est.2023.107123

Research interests

Automatic Eco-Driving

Transportation Electrification

Power System Stability and Resilience

Artificial Intelligence Applications in Electrical Engineering

Artificial Intelligence Driven Control for Offshore Renewable Energy

Large Language Model Multi Agent System

Committee/Steering group role

Supergen Offshore Renewable Energy ECR Rep

2024

In 2024, Dr. Guo took on the role of Supergen ORE ECR Committee Communication Officer. This role spotlights Early Career Researcher work, seek collaborative research opportunities via LinkedIn and other media, and engage ECRs in Supergen ORE Hub events, in collaboration with the Supergen ORE Hub team.

Membership/Fellowship of professional body

IEEE Member

2023

Affiliate of Royal Aeronautical Society

2023

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