Wenjie Xu - Homepage

 


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.

PhD positions in our group

Our group is interested in hearing from positive PhD candidates who would like to join the team to work on projects related to control, optimization, machine learning, and computation. We have several positions opening for now. Feel free to contact us for potential positions.

Research Interests

My current research interest lies in the integration of optimization, control and learning, with applications to building control and intelligent transportation.

Master/Semester projects

For EPFL students: if you're looking for master/semester projects and would be interested in optimization, probabilistic machine learning, automatic controller tuning or building control, feel free to drop me an e-mail to discuss.

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: 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

    • Homepage: https://JackieXuw.github.io/

    News
    • 02/2024. Paper "Lower Bounds on the Noiseless Worst-Case Complexity of Efficient Global Optimization" accepted to Journal of Optimization Theory and Applications. [arXiv]

    • 12/2023. Paper "Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approach" accepted to Applied Energy. [arXiv]

    • 10/2023. Preprint "Multi-Agent Bayesian Optimization with Coupled Black-Box and Affine Constraints" is available. [arXiv]

    • 10/2023. Preprint "Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approach" is available. [arXiv]

    • 06/2023. Preprint "Bayesian Optimization of Expensive Nested Grey-Box Functions" is available. [arXiv]