Chris Xiaoxuan Lu

Assistant Professor @ School of Informatics, University of Edinburgh

I am an Assistant Professor in the School of Informatics at the University of Edinburgh. My research interests broadly lie in cyber-physical systems (e.g., mobile robots and mixed reality devices) with the goal to drastically improve their reliability, intelligence and security in the wild. These works are motivated by the urgent need of robust localization and spatial perception solutions for mobile robotics and wearables to deal with i. sensing degradation (e.g., bad weather & poor illumination), ii. resource constraints (e.g., payloads, compute & energy budgets) and iii. malicious faults (e.g., adversarial attacks). A representative line of research I have been recently focusing on is 4D Automotive Radar-enabled Mobile Autonomy.

Before coming to Edinburgh, I did both my PhD study and post-doctoral in the Department of Computer Science, University of Oxford. Even earlier, I received my M.Eng degree from Nanyang Technological University (NTU).

I am always looking for students (PhD, Master by Research) to join my group. Drop me an email with your CV if you are interested.

selected publications

  1. T-RO
    Graph-Based Thermal–Inertial SLAM With Probabilistic Neural Networks
    Saputra, Muhamad Risqi U., Lu, Chris Xiaoxuan, Gusmao, Pedro Porto B., Wang, Bing, Markham, Andrew, and Trigoni, Niki
    IEEE Transactions on Robotics 2022
    arXiv Video Code
  2. ICRA’22
    AutoPlace: Robust Place Recognition with Single-chip Automotive Radar
    Cai, Kaiwen, Wang, Bing, and Lu, Chris Xiaoxuan
    In International Conference on Robotics and Automation (ICRA) 2022
    arXiv Video Code Website
  3. ICRA’22
    DC-Loc: Accurate Automotive Radar Based Metric Localization with Explicit Doppler Compensation
    Gao, Pengen, Zhang, Shengkai, Wang, Wei, and Lu, Chris Xiaoxuan
    In International Conference on Robotics and Automation (ICRA) 2022
    arXiv Video Code Website
  4. ICCV’21
    P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
    Wang, Bing, Chen, Changhao, Cui, Zhaopeng, Qin, Jie, Lu, Chris Xiaoxuan, Yu, Zhengdi, Zhao, Peijun, Dong, Zhen, Zhu, Fan, Trigoni, Niki, and Markham, Andrew
    In The IEEE/CVF International Conference on Computer Vision (ICCV) 2021
    arXiv Code
  5. MobiSys’20
    See through smoke: robust indoor mapping with low-cost mmWave radar
    Lu, Chris Xiaoxuan, Rosa, Stefano, Zhao, Peijun, Wang, Bing, Chen, Changhao, Stankovic, John A., Trigoni, Niki, and Markham, Andrew
    In The 18th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys) 2020
    arXiv HTML Video Code
  6. SenSys’20
    milliEgo: single-chip mmWave radar aided egomotion estimation via deep sensor fusion
    Lu, Chris Xiaoxuan, Saputra, Muhamad Risqi U., Zhao, Peijun, Almalioglu, Yasin, Gusmao, Pedro P. B., Chen, Changhao, Sun, Ke, Trigoni, Niki, and Markham, Andrew
    In The 18th ACM Conference on Embedded Networked Sensor Systems (SenSys) 2020
    arXiv HTML Video Code
  7. WWW’20
    Nowhere to Hide: Cross-modal Identity Leakage between Biometrics and Devices
    Lu, Chris Xiaoxuan, Li, Yang, Xiangli, Yuanbo, and Li, Zhengxiong
    In The Web Conference (WWW) 2020
    arXiv HTML Code
  8. MobiCom’18
    Simultaneous Localization and Mapping with Power Network Electromagnetic Field
    Lu, Chris Xiaoxuan, Li, Yang, Zhao, Peijun, Chen, Changhao, Xie, Linhai, Wen, Hongkai, Tan, Rui, and Trigoni, Niki
    In The 24th Annual International Conference on Mobile Computing and Networking (MobiCom) 2018
    Video PDF
  9. AAAI’18
    IONet: Learning to Cure the Curse of Drift in Inertial Odometry
    Chen, Changhao, Lu, Chris Xiaoxuan, Markham, Andrew, and Trigoni, Niki
    In The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) 2018
    arXiv HTML Video