About me
In 2025 I co-founded an AI company, opening a new chapter in my
career.
Prior to that, I was Senior R&D Director at
Momenta (HKEX: 6880), a leader in autonomous driving,
where I led the AI-Infra team building training accelerators, model
quantization pipelines, and deep learning compilers.
Before Momenta, I was Vice Research Director at
SenseTime Research (HKEX: 0020), leading the
Model-ToolChain team under the supervision of
Prof. Xiaogang Wang
and
Dr. Junjie Yan. Much of our work is open-sourced under the
ModelTC
organization on GitHub, and I write about it on Zhihu at
踢翻炼丹炉.
I first joined SenseTime as a full-time intern for two years in the
Video Intelligence Group under
Dr. Junjie Yan, working on high-performance video analysis systems (face, vehicle,
pedestrian) and porting algorithms to embedded platforms.
During college, I led the BUAA HPC team to first prize at the ASC
Student Supercomputer Challenge 2015, and spent half a year interning
on the Microsoft IoT team in Beijing, working on IoT communication
protocols.
I received my M.S. (2018) and B.S. (2015) in Computer Science from
Beihang University, advised by Prof. Xiaohua Shi. My research covered
JVM memory profiling, the CompCert project, and language models.
Publications
2023
Exploiting Subgraph Similarities for Efficient Auto-tuning of Tensor
Programs
International Conference on Parallel Processing (ICPP), 2023
Mingzhen Li, Hailong Yang, Shanjun Zhang,
Fengwei Yu, Ruihao Gong, Yi Liu, Zhongzhi Luan,
Depei Qian
SysNoise: Exploring and Benchmarking Training-Deployment System
Inconsistency
Conference on Machine Learning and Systems (MLSys), 2023
Yan Wang, Yuhang Li, Ruihao Gong, Aishan Liu, Yanfei Wang, Jian Hu,
Yongqiang Yao, Yunchen Zhang, Tianzi Xiao,
Fengwei Yu, Xianglong Liu
Exploiting Input Tensor Dynamics in Activation Checkpointing for
Efficient Training on GPU
[PDF]
International Parallel & Distributed Processing Symposium (IPDPS), 2023
Jianjin Liao, Mingzhen Li, Hailong Yang, Qingxiao Sun, Biao Sun,
Jiwei Hao, Tianyu Feng, Fengwei Yu, Shengdong Chen,
Ye Tao, Zicheng Zhang, Zhongzhi Luan, Depei Qian
2022
NNLQP: A Multi-Platform Neural Network Latency Query and Prediction
System with an Evolving Database
International Conference on Parallel Processing (ICPP), 2022
Liang Liu, Mingzhu Shen, Ruihao Gong, Fengwei Yu,
Hailong Yang
QDrop: Randomly Dropping Quantization for Extremely Low-bit
Post-Training Quantization
[PDF]
International Conference on Learning Representations (ICLR), 2022
Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu,
Fengwei Yu
Supervision Exists Everywhere: A Data Efficient Contrastive
Language-Image Pre-training Paradigm
[PDF]
International Conference on Learning Representations (ICLR), 2022
Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang,
Jing Shao, Fengwei Yu, Junjie Yan
2021
Once Quantization-Aware Training: High Performance Extremely Low-Bit
Architecture Search
[PDF]
International Conference on Computer Vision (ICCV), 2021
Mingzhu Shen, Feng Liang, Ruihao Gong, Yuhang Li, Chuming Li, Chen
Lin, Fengwei Yu, Junjie Yan, Wanli Ouyang
Differentiable Dynamic Wirings for Neural Networks
[PDF]
International Conference on Computer Vision (ICCV), 2021
Kun Yuan, Quanquan Li, Shaopeng Guo, Dapeng Chen, Aojun Zhou,
Fengwei Yu, Ziwei Liu
MixMix: All You Need for Data-Free Compression Are Feature and Data
Mixing
[PDF]
International Conference on Computer Vision (ICCV), 2021
Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Xin Dong,
Fengwei Yu, Shaoqing Lu, Shi Gu
Incorporating Convolution Designs into Visual Transformers
[PDF]
International Conference on Computer Vision (ICCV), 2021
Kun Yuan, Shaopeng Guo, Ziwei Liu, Aojun Zhou,
Fengwei Yu, Wei Wu
MQBench: Towards Reproducible and Deployable Model Quantization
Benchmark
[PDF]
Conference on Neural Information Processing Systems (NeurIPS), 2021
Yuhang Li, Mingzhu Shen, Jian Ma, Yan Ren, Mingxin Zhao, Qi Zhang,
Ruihao Gong, Fengwei Yu, Junjie Yan
Diversifying Sample Generation for Accurate Data-Free Quantization
[PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Xiangguo Zhang, Haotong Qin, Yifu Ding, Ruihao Gong, Qinghua Yan,
Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong
Liu
BRECQ: Pushing the Limit of Post-Training Quantization by Block
Reconstruction
[PDF]
International Conference on Learning Representations (ICLR), 2021
Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang,
Fengwei Yu, Wei Wang, Shi Gu
2020
Extremely Low-bit Convolution Optimization for Quantized Neural
Network on Modern Computer Architectures
[PDF]
International Conference on Parallel Processing (ICPP), 2020
Qingchang Han, Yongmin Hu, Fengwei Yu, Hailong
Yang, Bing Liu, Peng Hu, Ruihao Gong, Yanfei Wang, Rui Wang, Zhongzhi
Luan, Depei Qian
DMS: Differentiable Dimension Search for Binary Neural Networks
[PDF]
International Conference on Learning Representations (ICLR) NAS Workshop, 2020
Yuhang Li, Ruihao Gong, Fengwei Yu, Xin Dong,
Xianglong Liu
Towards Unified INT8 Training for Convolutional Neural Networks
[PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Feng Zhu, Ruihao Gong, Fengwei Yu, Xianglong Liu,
Yanfei Wang, Zhelong Li, Xiuqi Yang, Junjie Yan
Forward and Backward Information Retention for Accurate Binary
Neural Networks
[PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Haotong Qin, Ruihao Gong, Xianglong Liu, Mingzhu Shen, Ziran Wei,
Fengwei Yu, Jingkuan Song
2019
Differentiable Soft Quantization: Bridging Full-Precision and
Low-Bit Neural Networks
[PDF]
International Conference on Computer Vision (ICCV), 2019
Ruihao Gong, Xianglong Liu, Shenghu Jiang, Tianxiang Li, Peng Hu,
Jiazhen Lin, Fengwei Yu, Junjie Yan
2016
POI: Multiple Object Tracking with High Performance Detection and
Appearance Feature
[PDF]
European Conference on Computer Vision (ECCV) Workshop, 2016
Fengwei Yu, Wenbo Li, Quanquan Li, Yu Liu, Xiaohua
Shi, Junjie Yan
