Visiting address
Phone: +852 34422844

Author IDs

Willing to take PhD students: yes


Prof Miu Ling LAM is a media artist and researcher of computational imaging, robotics and interactive media. Her current research focuses on computational photography and display, deep learning-based light field synthesis and near infrared imaging.

Prior to joining CityU, she was a postdoctoral fellow at the University of California Los Angeles, specializing in single-molecule DNA identification and Art-Science integration. Her earlier research includes multi-fingered robotic grasp, computational geometry for wireless sensor network deployment, and obstacle avoidance for redundant manipulators using neural network.

Lam’s research is supported by General Research Fund (GRF), Innovation and Technology Commission of Hong Kong Government (ITF), National Natural Science Foundation of China (NSFC), Croucher Foundation and Hong Kong Jockey Club Charities Trust. She has won various academic and art awards, including CityU Teaching Excellence Award, World Cultural Council's Special Recognition Award, three best paper awards in IEEE international conferences, Croucher Fellowship, CUHK MAE Outstanding Alumni Award, Honorary Mention Award of IFVA-Interactive Media, and Shanghai International Science and Art Exposition Achievement Award.

Lam is a member of CityU Centre for Robotics and Automation, and a fellow of CityU Centre for Applied Computing and Interactive Media. She is the Programme Leader of Bachelor of Arts and Science in New Media in CityU School of Creative Media, and spearheading the education and community programs Jockey Club Project IDEA - Inclusive Digital and Experimental Arts and TEDY - Technologies for the Elderlies and Disabled People by Youths at CityU. She is also appointed as the Art Advisor (Media Arts) at Hong Kong Arts Development Council. She is the chair of SIGGRAPH Asia 2023 Emerging Technologies.

Research Interests/Areas

  • Computational (3D) Display
  • Bioinformatics
  • Computer Vision
  • Human Computer Interaction
  • Light Field Photography
  • Machine Learning
  • Media Arts
  • Robotics
  • Virtual/Augmented/Mixed Reality