个人信息

太阳成集团tyc9728准聘教授，同时担任麻省理工学院访问学者（2026–至今），MIT-Novo Nordisk Fellow，由 Anantha Chandrakasan 教授（MIT 教务长）和 Angela Belcher教授（MIT 生物工程系主任，美国三院院士） 联合指导。

研究聚焦于高效AI算法与硬件协同设计，涵盖模型量化、剪枝、视觉Transformer及大语言模型加速，并完成了28nm CMOS AI加速器芯片的流片验证，研究成果发表于NeurIPS、HPCA、DAC、ICCAD等国际顶级会议。

同时，致力于医学AI的应用研究，曾与Dana-Farber癌症研究所、宾夕法尼亚大学合作，建立无标记成像的癌症突变检测平台，以及与约翰霍普金斯医院合作的高光谱卵巢癌检测系统"OVASEEK"。

每年招收：硕士生2~3名，博士生1名。

科研方向

AI 芯片与加速器、AI 高效算法、智能医疗设备与生物发现

代表性学术成果

1. [TCAD] Peiyan Dong, Jinming Zhuang, Zhuoping Yang, Shixin Ji, Dongkuan Xu, Yanyu Li, Heng Huang, Jingtong Hu, Alex K. Jones, Yiyu Shi, Yanzhi Wang, Peipei Zhou, “EQ-ViT: Algorithm-Hardware Co-Design for End-to-End Acceleration of Real-Time Vision Transformer Inference on Versal ACAP”, in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2024，IF=2.7).

2. [23’HPCA] Peiyan Dong, Mengshu Sun, Alec Lu, Yanyue Xie, Zhenglun Kong, Xin Meng, Xue Lin, Zhenman Fang, Yanzhi Wang, “HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers”, in the 2023 IEEE International Symposium on High Performance Computer Architecture.

3. [22’DAC] Peiyan Dong, Yanyue Xie, Hongjia Li, Olivia Chen, Mengshu Sun, Nobuyuki Yoshikawa and Yanzhi Wang, “TAAS: A Timing-Aware Analytical Strategy for AQFP-Capable Placement Automation”, in the Proceedings of the 59th Annual Design Automation Conference.

4. [20’DAC] Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, Dingwen Tao, “Rtmobile: Beyond real-time mobile acceleration of rnns for speech recognition”, in the Proceedings of the 57th Annual Design Automation Conference.

5. [23’NeurIPS] Peiyan Dong, Zhenglun Kong, Xin Meng, Pinrui Yu, Yanyue Xie, Yifan Gong, Geng Yuan, Fei Sun, Hao Tang, Yanzhi Wang, “HotBEV: Hardware-oriented Transformer-based Multi-view 3D Detector for BEV Perception”, in the Proceedings of the 37th Conference on Neural Information Processing Systems.

6. [23’NeurIPS] Peiyan Dong, Lei Lu, Chao Wu, Cheng Lyu, Geng Yuan, Hao Tang, Yanzhi Wang, “PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile”, in the Proceedings of the 37th Conference on Neural Information Processing Systems.

7. [23’ICML] Peiyan Dong, Zhenglun Kong, Xin Meng, Peng Zhang, Hao Tang, Yanzhi Wang, Chih-Hsien Chou, “SpeedDETR: Speed-aware Transformers for End-to-end Object Detection”, in the Proceedings of the 2023 Fortieth International Conference on Machine Learning.

8. [IJCV] Zhenglun Kong, Dongkuan Xu, Zhengang Li, Peiyan Dong, Hao Tang, Yanzhi Wang, Subhabrata Mukherjee, “AutoViT: Achieving Real-Time Vision Transformers on Mobile via Latency-aware Coarse-to-Fine Search”, in the International Journal of Computer Vision (2025，IF=15.5).

9. [25’ICCAD] Xuan Shen, Peiyan Dong, Zhenglun Kong, Yifan Gong, Changdi Yang, Zhaoyang Han, Yanyue Xie, Lei Lu, Cheng Lyu, Chao Wu, Yanzhi Wang, Pu Zhao, “Squat: Quant Small Language Models on the Edge”, in Proceeding of the 2025 IEEE/ACM International Conference On Computer Aided Design (ICCAD) .

10. Xuan Shen*, Peiyan Dong*, Lei Lu, Zhenglun Kong, Zhengang Li, Ming Lin, Chao Wu, Yanzhi Wang, “Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge”, in the Proceedings of the 2024 AAAI Conference on Artificial Intelligence (Oral), 共同一作.

11. [24’DATE] Yanyue Xie*, Peiyan Dong*, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen and Yanzhi Wang, “SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits”, in the Proceedings of the 2024 Design, Automation & Test in Europe Conference. 共同一作.

12. [23’MICRO] Zhengang Li, Geng Yuan, Yanyue Xie, Peiyan Dong, Xulong Tang, Nobuyuki Yoshikawa, Devesh Tiwari, Yanzhi Wang, Olivia Chen, “SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices”, in the Proceeding of 56th IEEE/ACM International Symposium on Microarchitecture.

13. [20’ICS] Runbin Shi*, Peiyan Dong*, Tong Geng, Yuhao Ding, Xiaolong Ma, Martin Herbordt, Ang Li, Yanzhi Wang,“CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks”, in the Proceeding of the 2020 International Conference on Supercomputing. 共同一作.

14. [23’ICCAD] Changdi Yang*, Yi Sheng*, Peiyan Dong*, Zhenglun Kong, Yanyu Li, Pinrui Yu, Lei Yang, Xue Lin, “Fast and Fair Medical AI on the Edge through Neural Architecture Search for Hybrid Vision Models”, in the Proceedings of the 2023 IEEE/ACM International Conference on Computer Aided Design. 共同一作.

15. [TPAMI] Wei Niu, Zhengang Li, Xiaolong Ma, Peiyan Dong, Gang Zhou, Xuehai Qian, Xue Lin, Yanzhi Wang, Bin Ren, “GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity”, in the IEEE Transactions on Pattern Analysis and Machine Intelligence (2023，IF=23.6).

16. [23’DAC] Zhengang Li*, Yanyue Xie*, Peiyan Dong*, Olivia Chen, Yanzhi Wang, “Invited: Algorithm- Software-Hardware Co-Design for Deep Learning Acceleration”, in the Proceedings of the 60th Annual Design Automation Conference. 共同一作.

17. [23’DAC] Changdi Yang*, Yi Sheng*, Peiyan Dong*, Zhenglun Kong, Yanyu Li, Pinrui Yu, Lei Yang, Xue Lin, “Fast Fair Medical Applications? Hybrid Vision Models Achieve the Fairness on the Edge: Late Breaking Results

承担科研情况

国家自然科学基金青年科学基金项目

所获奖励

MIT-Novo Nordisk Fellow（麻省理工学院）

EECS Rising Star Award（北美范围）

Koch Institute Imaging Award（麻省理工学院）

社会兼职

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