Wenjie Xu

Doctoral student in Electrical Engineering
École polytechnique fédérale de Lausanne (EPFL)
[GitHub] [Google Scholar] [ResearchGate] [LinkedIn] [CV]

Biography

I am currently a PhD student in Electrical Engineering in EPFL as part of NCCR automation, working with Prof. Colin Jones. I am also working with Dr. Bratislav Svetozarevic from Empa on building control. I received my MPhil from the Department of Information Engineering, The Chinese University of Hong Kong, where I worked with Prof. Minghua Chen. Prior to that, I received my BEng in Electronic Engineering and (dual) BSc in Math, both from Tsinghua University in 2018.

Research Interests

My current research interest lies in Data/AI-driven control and optimization (particularly LLM-based agentic AI), with applications to sustainable cyber-physical-human systems (CPHS), e.g., buildings.

Collaborations and Consultancy

Academic collaboration: I am generally open to academic collaborations. See my publications for our work. Feel free to contact me if you are interested in some discussions.

Industrial consultancy: I can give consultancy and tutorials on data science and optimization for energy systems (building systems in particular) and logistics systems. Please email me if you are interested.

Services

Reviewer for: IEEE Transactions on Automatic Control, IEEE/ACM Transactions on Networking, IEEE Transactions on Neural Networks and Learning Systems, Optimal Control Applications and Methods.

Reviewer for: NeurIPS, ICML, ICLR, IEEE Conference on Decision and Control, American Control Conference.

Contact

Lab: EPFL STI IGM LA3 ME C2 399 (Bâtiment ME) Station 9 CH - 1015 Lausanne
Email: wenjie.cuhk AT gmail.com, wenjie.xu AT epfl.ch

News

11/2024. Paper "Minimizing Emission for Timely Heavy-Duty Truck Transportation" accepted to the IEEE Transactions on Intelligent Transportation Systems.
09/2024. Paper "Principled Bayesian Optimization in Collaboration with Human Experts" accepted to the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) as a spotlight. [arXiv]
05/2024. Paper "Principled Preferential Bayesian Optimization" accepted to the Forty-first International Conference on Machine Learning (ICML 2024) for oral presentation. [arXiv]