Augmented Reality
will revolutionize our everyday life

I’m passionate about researching, developing and deploying Computer Vision and Deep Learning algorithms, for making our world better through Self-Driving Vehicles, and Augmented-Reality applications. I received my PhD at Bournemouth University, UK, focused on Augmented Reality research with Computer Vision and Machine Learning. Before this PhD programme, I got my Master's degree from University College London (UCL) with distinction. My research focuses on Augmented Reality in surgical guidance and games with the common theme of applying novel computer vision technologies, e.g. SLAM (Simultaneous Localization And Mapping) and machine learning techniques, e.g. Deep Learning, to tackle the AR tracking, reconstruction and interaction problems.


  • Nov 2018 - present

    Lyft Level 5
    Research Engineer
    Crowd-sourced visual maps building, learned motion planning algorithms for Lyft's Self Driving Vehicles
  • MAY 2018 - NOV 2018

    Blue Vision Labs
    Research Engineer
    Real-time localization system for a city-scale collaborative AR SDK.
  • Oct 2015 - Oct 2018

    Bournemouth University
    Department of Creative Technology
    Ph.D. Candidate in Augemented Reality, Computer Vision
  • FEB 2015 - OCT 2015

    Toshiba Medical Systems Co., Ltd
    Software Engineer
  • NOV 2014 - FEB 2015

    GE Healthcare
    Advanced Application Intern
  • OCT 2013 - OCT 2014

    University College London
    Department of Medical Physics and Biomedical Engineering
    MSc in Medical Image Computing (graduate with Distinction)
  • SEP 2009 - July 2013

    Dalian University of Technology
    Faculty of Electronic Information and Electrical Engineering
    BSc in Biomedical Engineering
  • 20 AUG 1990

    Arrived onto Earth!

Research Projects

Augmented Reality in Minimally Invasive Surgery

Keywords: SLAM|Stereo Matching

[1] L Chen, T Day, W Tang, N John, "Recent Developments and Future Challenges in Medical Mixed Reality", 16th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2017[arXiv]

[2] L Chen, W Tang, N John, "Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery", 11th MICCAI workshop on Augmented Environments for Computer-Assisted Interventions (AECAI), 2017[PDF]

[3] L Chen, W Tang, N Jogn, T Wan, J Zhang, "SLAM-based Dense Surface Reconstruction in Monocular Minimally Invasive Surgery and its Application to Augmented Reality", Computer Methods and Programs in Biomedicine, 158, 135-146, 2018[PDF]

Interactive Material-Aware Augmented Reality Environment

Keywords: Deep Learning|SLAM

[4] L Chen, W Tang, N John, T Wan, J Zhang, "Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction",Computer Graphics Forum \& Eurographics 2020 (Oral Presentation)[arXiv][Video]

[5] L Chen, K Francis, W Tang, "Semantic Augmented Reality Environment with Material-Aware Physical Interactions", 16th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2017[arXiv]

Computer Vision Research

Keywords: CV|Deep Learning

[6] L. Chen, W. Tang, N. W. John, T. R. Wan and J. J. Zhang, "De-smokeGCN: Generative Cooperative Networks for Joint Surgical Smoke Detection and Removal", IEEE Transactions on Medical Imaging, vol. 39, no. 5, pp. 1615-1625[arXiv]

[7] L. Chen, W. Tang, N. W. John, "Self-Supervised Monocular Image Depth Learning and Confidence Estimation", Neurocomputing, 381, 272-281, 2020.[arXiv]

[8] W. Zhang, Y. Zhao, P. Breckon, L. Chen, "Noise robust image edge detection based upon the automatic anisotropic Gaussian kernels", Pattern Recognition, 63, 193-205, 2017.

[9] Q. Gao, T.R. Wan, W. Tang, L. Chen, "A Stable and Accurate Marker-less Augmented Reality Registration Method", In: 2017 International Conference on CYBERWORLDS, 20-22, 2017

[10] Q. Gao, T.R. Wan, W. Tang, L. Chen and K.B Zhang, 2017. "An Improved Augmented Reality Registration Method Based on Visual SLAM", In: Edutainment 2017, 26-27, 2017

Quantitative game-based learning environment

Keywords: VR|Quantitative model

[11] L Chen and W Tang, "MathRun: an adaptive mental arithmetic game using a quantitative performance model." 30th International BCS Human Computer Interaction Conference (BHCI), 2016[PDF][Video]

Skills & Techniques

  • Multi-platform Programming

    I’m passionate about solving real-world problems with coding. I have more than 8 years multi-platform programming experience with C/C++, Python, Matlab and Golang in Windows and Linux.

  • Research

    I love research and always keep up with the latest research trend and paper. I have published 8 papers as the first author during my PhD including some of the most impactful journals and conferences such as IEEE Transactions on Medical Imaging (IF 7.81), Neurocomputing (IF 4.07), and IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Eurographics (EG).

  • Computer Vision

    Computer Vision is one of the most impressive and fascinating technologies that I have learned and worked on. It is the door connecting the machine with our real world. So far, I have worked on many projects using computer vision, such as medical image processing, AR and Self-Driving. I have comprehensive knowledge and experience with computer vision algorithms in feature/object tracking, camera calibration, Structure from Motion (SfM) and Simultaneous Localization and Mapping(SLAM).

  • Deep Learning

    I am keen on deep learning and believe it's the key to many future technologies such as AR and Self-Driving. I have extensive experience using Caffe and Tensorflow for object classification (CNN), semantic segmentation(FCN, CRF-RNN) and reinforcement learning. I have completed and earned certificate of the Deep Learning Specialization coursera online course by Andrew Ng. [Certificate]

Contact Me