081104-模式识别与智能系统
081203-计算机应用技术

计算机视觉，深度学习模型优化，智能计算

2013-09--2018-06   中国科学院自动化研究所   工学博士
2009-09--2013-06   山东大学   工学学士

2021-11~2022-05,微软亚洲研究院, “铸星计划”访问学者
2021-04~现在, 中国科学院自动化研究所 模式识别国家重点实验室, 副研究员
2018-07~2021-04,中国科学院自动化研究所 模式识别国家重点实验室, 助理研究员

2024 电子工业出版社2024年度优秀作者奖

2023 入选CCF-百度松果基金学者

2023 入选中科院特聘研究骨干

2022 入选北京科协青年人才托举工程

2022 IEEE国际标准突出贡献奖

2021 入选微软亚洲研究院“铸星计划”

2019 NeurIPS 2019国际神经网络压缩挑战赛MicroNet Challenge冠军

2018 NVIDIA奖学金

   

2024

• Zhengyang Zhuge, JiaxingWang, Yong Li, Yongjun Bao, PeisongWang, Jian Cheng, Patch-Aware Sample Selection for Efficient Masked Image Modeling, AAAI 2024.

• Zhengyang Zhuge, Peisong Wang, Xingting Yao, Jian Cheng. Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration. ICML, 2024. 

• Zeyu Zhu, Peisong Wang, Qinghao Hu, Gang Li, Xiaoyao Liang, Jian Cheng. FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale. ASPLOS, 2024.

2023

• Weihan Chen, Peisong Wang, Jian Cheng. Towards automatic model compression via a unified two-stage framework. Pattern Recognation (PR), 2023.
• Tianqi Chen, Weixiang Xu, Weihan Chen, Peisong Wang, Jian Cheng. Towards Efficient and Accurate Winograd Convolution via Full Quantization. NeurIPS, 2023. 

2022

• Peisong Wang, Weihan Chen, Xiangyu He, Qiang Chen, Qingshan Liu, Jian Cheng. Optimization-based Post-training Quantization with Bit-split and Stitching. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
• Peisong Wang*, Xiangyu He*, Jian Cheng. Towards Accurate Binarized Neural Networks with Sparsity for Mobile Application. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
• Weixiang Xu*, Fanrong Li*, Yingying Jiang, Yong A, Xiangyu He, Peisong Wang, Jian Cheng. Improving Extreme Low-bit Quantization with Soft Threshold. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022.
• Anda Cheng, Peisong Wang, Xi Sheryl Zhang, Jian Cheng. Differentially Private Federated Learning with Local Regularization and Sparsification. CVPR, 2022.
• Weixiang Xu, Xiangyu He, Ke Cheng, Peisong Wang, Jian Cheng. Towards Fully Sparse Training: Information Restoration with Spatial Similarity. AAAI, 2022.
• Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang, Jian Cheng. Dpnas: Neural architecture search      for deep learning with differential privacy. AAAI, 2022.

2021

• Peisong Wang*, Fanrong Li*, Gang Li, Jian Cheng. Extremely Sparse Networks via Binary Augmented Pruning for Fast Image Classification. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
• Weihan Chen, Peisong Wang, Jian Cheng. Towards mixed-precision quantization of neural networks via constrained optimization. ICCV, 2021.

2020

• Peisong Wang, Xiangyu He, Qiang Chen, Anda Cheng, Qingshan Liu and Jian Cheng. Unsupervised Network Quantization via Fixed-point Factorization. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020.
• Qiang Chen, Anda Cheng, Xiangyu He, Peisong Wang, Jian Cheng. Spatialflow: Bridging all tasks for panoptic      segmentation. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
• Qiang Chen, Peisong Wang, Anda Cheng, Wanguo Wang, Yifan Zhang, Jian Cheng. Robust one-stage object detection with      location-aware classifiers. Pattern Recognition (PR), 2020.
• Peisong Wang, Qiang Chen, Xiangyu He and Jian Cheng. Towards Accurate Post-training Network Quantization via Bit-Split and Stitching. ICML, 2020.
• Peisong Wang*, Xiangyu He*, Gang Li, Tianli Zhao and Jian Cheng. Sparsity-Inducing Binarized Neural Networks. AAAI, 2020.
• Gang Li, Peisong Wang, Zejian Liu, Cong Leng, Jian Cheng. Hardware acceleration of CNN with one-hot quantization of weights and activations. DATE, 2020.
• Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang, Jian Cheng. Soft Threshold Ternary Networks. IJCAI, 2020.
• Xiangyu He, Zitao Mo, Ke Cheng, Weixiang Xu, Qinghao Hu, Peisong Wang, Qingshan Liu, Jian Cheng. Proxybnn: Learning binarized neural networks via proxy matrices. ECCV, 2020.
• Weihan Chen, Peisong Wang, Jian Cheng. Towards Convolutional Neural Networks Compression via Global&Progressive Product Quantization. BMVC, 2020.

2019

• Xiangyu He, Peisong Wang, Jian Cheng. K-nearest neighbors hashing. CVPR, 2019.
• Xiangyu He, Zitao Mo, Peisong Wang, Yang Liu, Mingyuan Yang, Jian Cheng. Ode-inspired network design for single      image super-resolution. CVPR, 2019.
• Zhe Li, Peisong Wang, Hanqing Lu, Jian Cheng. Reading selectively via Binary Input Gated Recurrent Unit. IJCAI, 2019.

2018及以前

• Peisong Wang, Qinghao Hu, Zhiwei Fang, Chaoyang Zhao and Jian Cheng. DeepSearch: A fast image search framework for mobile devices.  ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2018.
• Jian Cheng, Peisong Wang, Gang Li, Qing-hao Hu, Hanqing Lu. Recent advances in efficient computation of deep      convolutional neural networks. Frontiers of Information Technology & Electronic Engineering (FITEE), 2018.
• Peisong Wang, Qinghao Hu, Yifang Zhang, Chunjie Zhang, Yang Liu and Jian Cheng. Two-Step Quantization for Low-bit Neural Networks. CVPR, 2018.
• Qinghao Hu, Peisong Wang, Jian Cheng. From hashing to cnns: Training binary weight networks via hashing. AAAI, 2018.
• Qinghao Hu, Gang Li, Peisong Wang, Yifan Zhang, Jian Cheng. Training binary weight networks via semi-binary      decomposition. ECCV, 2018.
• Guibo Zhu, Jinqiao Wang, Peisong Wang, Yi Wu, Hanqing Lu. Feature distilled tracking. IEEE transactions on cybernetics, 2017.
• Peisong Wang and Jian Cheng. Fixed-point Factorized Networks. CVPR, 2017.
• Peisong Wang, Qiang Song, Hua Han, Jian Cheng. Sequentially supervised long short-term memory for gesture recognition. Cognitive Computation, 2016.
• Peisong Wang and Jian Cheng. Accelerating Convolutional Neural Networks for Mobile Applications. ACM Multimedia, 2016.

   

（ 1 ） 深度神经网络无监督定点量化方法研究, 负责人, 国家自然科学基金青年基金, 2020-01--2022-12

（ 2 ） 基于目标行为的视频流内容安全分析与智能检索, 课题负责人, 国家自然科学基金重点项目, 2020-01--2023-12

（ 3 ） 进化与推演环境-软硬协同的底层加速库, 子课题负责人, 中科院战略先导A类项目, 2020-07--2025-06

（ 4 ） 面向通用视觉的机器学习理论与方法，子课题负责人，科技创新2030重大项目，2023-01--2025-12

（ 5 ） 面向大模型的异构算力融合的智能编译器研发，课题负责人，江苏省科技重大专项项目，2025-01--2027-12

（ 6 ） 深度学习模型小型化和硬件加速合作项目（四期），负责人，华为合作项目，2022-09--2023-07

（ 7 ） LLM长序列推理加速算法技术合作项目，负责人，华为合作项目，2024-06--2025-05

（ 8 ） 基于自适应低精度和混合精度计算的模型训练加速方法研究，负责人，百度松果基金，2023-11--2024-10