Kin Wai Lau
Scholar

Kin Wai Lau

Google Scholar ID: inhIzDgAAAAJ
City University of Hong Kong | TCL AI LAB
Image ProcessingVideo ProcessingComputer VisionDeep Learning
Citations & Impact
All-time
Citations
603
 
H-index
7
 
i10-index
5
 
Publications
20
 
Co-authors
13
list available
Resume (English only)
Academic Achievements
  • September 2024, paper titled 'FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning' accepted to ACCV 2024.
  • April 2024, paper titled 'Exploring Federated Self-Supervised Learning for General Purpose Audio Understanding' accepted to ICASSP-2024 workshop on Self-supervision in Audio, Speech and Beyond.
  • February 2024, paper titled 'AudioRepInceptionNeXt: A lightweight single-stream architecture for efficient audio recognition' accepted in NeuroComputing.
  • November 2023, paper titled 'Adaptive uncertainty estimation via high-dimensional testing on latent representations' accepted in NeurIPS 2023.
  • August 2023, paper titled 'Large Separable Kernel Attention: Rethinking the Large Kernel Attention design in CNN' accepted in Expert Systems with Applications.
  • June 2023, solution got first place award in EPIC-Kitchens-100 2023 Challenges on EPIC-SOUNDS Audio-Based Interaction Recognition, CVPR 2023 Workshop.
  • June 2022, paper titled 'What Should Be Equivariant in Self-Supervised Learning' accepted to CVPR Workshops on L3D-IVU.
Research Experience
  • Works at TCL AI Lab on various projects, including audio recognition for smart home robots, anomaly detection for industrial applications, and low-level image enhancement tasks such as super-resolution and diffraction removal for under-display cameras (UDC).
Education
  • Received B.E. degree in Information Engineering from City University of Hong Kong in 2017; Currently pursuing a part-time Ph.D. degree at the Department of Electrical Engineering, City University of Hong Kong, under the guidance of Dr. Lai-Man Po.
Background
  • Research interests include Computer Vision, Audio Processing, Image enhancement, Image and audio representation learning, Federated learning, Self-supervised learning, Reparameterization. Works as a Research Engineer at TCL AI Lab, focusing on Computer Vision, Audio Processing, and Deep Learning.
Miscellany
  • Personal interests and hobbies not mentioned.