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). Representative lines of research I have been recently focusing on are 4D Automotive Radar-enabled Mobile Autonomy and Sense Augmentation for First Responders.

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).

news

Oct 1, 2022 Our embedded AI enabled firefighting helmet was covered by more than 20 top-tier hits across broadcast TV, radio, international newswires, including: BBC News, BBC Good Morning Scotland, Reuters, STV, Planet Radio, Sky News, Evening Standard Tech & Science Daily, Yahoo!, Scottish Daily Express, The Independent, Scottish Field, Scottish Daily Mail, Italy 24 News, Irish News, Engineering & Technology, Digit News, UoE News (FrontPage).

selected publications

  1. CVPR’23
    Hidden Gems: 4D Radar Scene Flow Learning Using Cross-Modal Supervision
    Ding, Fangqiang, Palffy, Andras, Gavrila, Dariu M., and Lu, Chris Xiaoxuan
    In IEEE Conference on Computer Vision and Pattern Recognition 2023
    Selected as CVPR’23 Highlight (top 2.5% out of 9155 submissions)
    arXiv Video Code Website
  2. 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
  3. SenSys’22
    Telesonar: Robocall Alarm System by Detecting Echo Channel and Breath Timing
    Yan, Zhenyu, Tan, Rui, Song, Qun, and Lu, Chris Xiaoxuan
    In ACM Conference on Embedded Networked Sensor Systems (SenSys) 2022
    PDF
  4. 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
  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. 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
  8. 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