About me

I am currently a PhD Candidate in the Department of Information Engineering at The Chinese University of Hong Kong, where I am fortunate to be advised by Prof. Raymond Yeung. I received my Bachelor’s degree in Electrical Engineering with First Class Honors from The University of Sydney in 2020. During my undergraduate studies, I was fortunate to work with Prof. Philip Leong on perturbation-based neural network on-chip training.

I have been a reviewer for NeurIPS, CVPR, ECCV, ACM MM, and AAAI. My research focuses on learning and modeling complex systems with AI. I am particularly interested in finding the underlying representation of data and solving real-world problems with interdisciplinary knowledge.


  • I will graduate in late 2024 and am looking for postdoc positions!

  • [July 16, 2024] The structured BATS code paper is accepted by IEEE Transactions on Communications (TCOM)

  • [Sep 22, 2023] The Mind-Video paper was accepted by NeurIPS2023 for Oral Presentation!

  • [Aug, 2023] MinD-Vis project was also covered by The Telegraph, Reuters and South China Morning Post

  • [May, 2023] MinD-Vis project was featured by NBC News [Youtube,Website]

Publications (* indicates equation contributions)

Towards High-Performance Network Coding: Parallel Construction With Subfield Generators
Jiaxin Qing, Philip H.W. Leong and Raymond W. Yeung
under review, 2024

A scalable and high-performant BATS code accelerator based on FPGA with an optimized finite field multiplier.

Dependence Analysis and Structured Construction for Batched Sparse Code
Jiaxin Qing, Xiaohong Cai, Yijun Fan, Mingyang Zhu and Raymond W. Yeung
IEEE Transactions on Communications (TCOM), 2024

First step towards hardware-friendly Batched Sparse Codes (BATS).

Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity
Zijiao Chen*, Jiaxin Qing*, Juan Helen Zhou
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 (Oral)

flow chart

We decoded photo-realistic video stimuli from fMRI brain signals.
[paper, website, code]

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding
Zijiao Chen*, Jiaxin Qing*, Tiange Xiang, Wan Lin Yue, Juan Helen Zhou
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

flow chart

We decoded photo-realistic visual stimuli from fMRI brain signals.
[paper, website, code]

Performance Analysis and Optimal Design of BATS Code: A Hardware Perspective
Jiaxin Qing, Philip HW Leong, and Raymond W. Yeung
IEEE Transactions on Vehicular Technology (TVT), 2023

Design space analysis of BATS code for FPGA implementation.

Packet size optimization for batched network coding
Hoover HF Yin, Harry WH Wong, Mehrdad Tahernia, Jiaxin Qing
IEEE International Symposium on Information Theory (ISIT), 2022

Optimizing the packet size for batched network coding.

Enhancing the decoding rates of BATS codes by learning with guided information
Jiaxin Qing, Hoover HF Yin, and Raymond W. Yeung
IEEE International Symposium on Information Theory (ISIT), 2022

Explored the graphical structure of Batched Sparse Codes (BATS) with reinforcement learning.