Prof. Shiqi(Shawn) Ou, a Tenured Professor and Doctoral Supervisor at the School of Future Technology, South China University of Technology (SCUT), is also a dual-appointed Research Fellow at the Pazhou Lab (Guangdong Laboratory of Artificial Intelligence and Digital Economy). He has been recognized in the Stanford University list of the World’s Top 2% Scientists. During his tenure at the U.S. Department of Energy’s Oak Ridge National Laboratory, he led or participated in numerous energy system modeling studies for the U.S. DOE and Department of Transportation. Currently, he serves on the editorial boards of Transportation Research Part D: Transport and Environment (CAS Tier 1 SCI) and Transportation Research Record (TRR), as a youth editorial board member for Communications in Transportation Research (COMMTR, CAS Tier 1 SCI), and as an Associate Editor for the SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy (EI indexed). He has published over 50 SCI papers as first or corresponding author in prestigious journals such as Nature Energy and Nature Communications.
His research focuses on dynamic modeling and intelligent optimization of road, waterborne, and air transportation energy systems to support overall economy-wise carbon net zero strategy. The research centers on the coupling of alternative fuels vehicles including PEVs, connected and autonomous vehicles, energy storage, and the power energy market. It employs advanced methodologies such as transportation big data mining and analysis, AI, operations research, and multi-threaded parallel computing.
The team develops multi-powertrain system simulation and optimization models reflecting real-world conditions and vehicle driver travel behaviors. These models integrate mathematical modeling and AI algorithms to quantify transportation market energy demand, life-cycle energy consumption, and carbon emissions under various vehicle powertrain technologies and energy policies. This research aims to optimize vehicle energy efficiency, planning of recharging/refueling infrastructure, and total cost of ownership (TCO), while assessing life-cycle carbon emissions and resource allocation for different vehicle powertrain technologies. It also forecasts transportation demand and energy evolution, ultimately supporting and advancing national decarbonization goals in the transportation sector.
TRANS Lab recruits PhD and Master students annually, welcoming applicants from diverse STEM backgrounds, particularly those with expertise in computer science, engineering in transportation, electric or mechanical engineering. The team also actively seeks assistant professors, postdoctoral researchers, and research assistants to join its efforts.
Contact：
- Email： sou [at] scut [dot] edu [dot] cn，translab_scut [at] hotmail [dot] com
- Address： School of Future Technology, South China University of Technology
TRANS Lab is recruiting Ph.D. students for the class of 2026
Candidates are expected to meet the following three criteria:
1.Applicants should hold or be pursuing a Master’s degree in Engineering. Priority will be given to those with research experience in AI algorithm applications, embedded hardware, Large Language Models (LLMs), Natural Language Processing (NLP), or multi-agent systems, particularly within the fields of Computer Science, Transportation, Energy, or Mechanical Engineering;
2.Candidates should have published two or more academic papers as a primary author in top-tier conferences or journals, and possess solid programming skills alongside strong English proficiency. Preference will be given to those with significant contributions to open-source communities like GitHub (e.g., leading high-impact projects related to LLMs);
3.Applicants must demonstrate a passion for scientific research, a rigorous scholarly spirit, ambition, and a strong sense of responsibility. We value candidates who are outgoing, enthusiastic, and possess excellent teamwork skills.
Interested individuals should send a comprehensive CV (including academic, professional, and research experience, honors and awards, publications, and GitHub project links) to the head of the research group: Shiqi(Shawn) Ou, sou [AT] scut [DOT] edu [DOT] cn