Welcome to my website~ My name is Shengkun Tang. You can call me Bryson for short.
Currently, I am a research intern in Alibaba Qwen Team. Besides, I am a PhD student of Machine Learning in MBZUAI, under the supervision of Prof. Zhiqiang Shen.
During my gap year, I had a wonderful time as an research assistant in DASLab in ISTA , working with Prof. Dan Alistarh.
Besides, I had close collaboration with Prof. Dongkuan Xu (NCSU) and Dr. Yaqing Wang (Google DeepMind), working on efficent multi-modal models.
I finished B.E. in Remote Sensing at Wuhan University , under the supervision of Prof. Jian Yao and Prof. Xin Su.
05/2023: Invited to give a talk at
将门创投 on June 8, 2023. Welcome!
02/2023: My first paper on
accelerating inference of vision language model
was accepted by CVPR 2023. Super excited :). Thank all co-authors' support.
09/2022: I joined Intelligent Automotive Group(IAG) at SenseTime as a system developer.
I will build system for various perception modules of self-driving.
Research
My research focuses on building efficient,
reliable, and
deployableAI systems. I am interested in improving the full pipeline of modern foundation models, from architecture design and training to inference, data, and evaluation.
Specifically, my research spans four directions:
Inference Efficiency. I develop methods that reduce the computational and memory cost of large models during deployment, including structured pruning , quantization, adaptive computation, and token pruning.
Training Efficiency. I study resource-efficient training methods that improve model capability under limited computational budgets, including efficient optimization, data-efficient learning, and scalable training strategies.
Novel Model Architectures. I design compact and scalable model architectures for efficient intelligence, including work such as SlimQwen and other architecture-level innovations.
Data-Centric AI and Trustworthy Evaluation. I also study data quality, efficient data usage, benchmarks, and trustworthy evaluation.
I am always open to research collaborations. Please feel free to contact me if you are interested in efficient AI systems, foundation models, or related topics.
MosaicDiff: Training-free Structural Pruning for Diffusion Model Acceleration Reflecting Pretraining Dynamics Bowei Guo, Shengkun Tang, Cong Zeng, Zhiqiang Shen [ICCV 2025] International Conference on Computer Vision, ICCV 2025 Paper
Do Large Language Models Perceive Orderly Number Concepts as Human? Xuanjie Liu, Cong Zeng, Shengkun Tang, Ziyu Wang, Gus Xia [Re-Align Workshop, ICLR 2025] 2nd Workshop on Representational Alignment, ICLR 2025 Paper
DDR-Net: Learning Multi-Stage Multi-View Stereo With Dynamic Depth Range Puyuan Yi*, Shengkun Tang*, Jian Yao Preprint, 2021 arXiv / code
Scale-robust deep-supervision network for mapping building footprints from high-resolution remote sensing images Haonan Guo, Xin Su, Shengkun Tang, Bo Du, Liangpei Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 PDF
Industrial Experience
Qwen Team, Alibaba, 06/2025 - Now
Research Intern
Mentor: Bo Zheng and Dayiheng Liu
SenseTime, Engineering & Intelligent Automotive Group (IAG), 06/2021 - 10/2021 & 05/2022 - 07/2023
Vision Algorithm Intern; System Developer
Project: SenseRobot Chess Robotic, working with Ruodai Li
Project: Large-Scale Self-Driving System Development