孙奇（浙江大学博士生导师）

孙奇博士是浙江大学第一类“百人计划”研究员、博士生导师，入选国家级优秀青年人才计划。
2022年获得香港中文大学计算机科学与工程学博士学位，此后于康奈尔大学计算机系统实验室从事博士后研究工作。
主要研究领域为机器学习辅助电子设计自动化（AI for EDA）、深度学习硬件推理加速、设计空间探索等。曾获得EDA国际顶级学术会议ICCAD最佳论文奖、欧洲设计自动化会议DATE最佳论文奖提名与ICCAD学生科研竞赛铜奖等。
研究与成果有：
机器学习辅助电子设计自动化
利用机器学习技术，辅助电子设计自动化完成设计优化、性能建模、预测等任务。相关论文成果如下：
Guojin Chen, Wanli Chen, Qi Sun, Yuzhe Ma, Haoyu Yang, Bei Yu, “DAMO: Deep Agile Mask Optimization for Full Chip Scale”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 9, pp. 3118-3131, Sept. 2022.
Qi Sun, Tinghuan Chen, Siting Liu, Jianli Chen, Hao Yu, Bei Yu, “Correlated Multi-objective Multi-fidelity Optimization for HLS Directives Design”, ACM Transactions on Design Automation of Electronic Systems (TODAES), vol. 27, no. 4, 2022.
Tinghuan Chen, Qi Sun, Canhui Zhan, Changze Liu, Huatao Yu, Bei Yu, “Deep H-GCN: Fast Analog IC Aging-induced Degradation Estimation”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 7, pp. 1990-2003, 2022.
Tinghuan Chen, Qi Sun, Canhui Zhan, Changze Liu, Huatao Yu, Bei Yu, “Analog IC Aging-induced Degradation Estimation via Heterogeneous Graph Convolutional Networks”, IEEE/ACM Asia and South Pacific Design Automation Conference (ASPDAC), Tokyo, Jan. 18–21, 2021.
Chen Bai, Qi Sun, Jianwang Zhai, Yuzhe Ma, Bei Yu, Martin D.F. Wong, “BOOM-Explorer: RISC-V BOOM Microarchitecture Design Space Exploration Framework”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 1–4, 2021.   (William J. McCalla Best Paper Award)
Siting Liu, Qi Sun, Peiyu Liao, Yibo Lin, Bei Yu, “Global Placement with Deep Learning-Enabled Explicit Routability Optimization”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Feb. 01–05, 2021.
Qi Sun, Tinghuan Chen, Siting Liu, Jin Miao, Jianli Chen, Hao Yu, Bei Yu, “Correlated Multi-objective Multi-fidelity Optimization for HLS Directives Design”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Feb. 01–05, 2021. (Best Paper Award Nomination)
深度学习推理加速
涉及硬件友好的模型设计，涵盖不同平台的深度学习推理部署，包括CPU、GPU、FPGA、RISC-V SoC等。
Yuxuan Zhao, Qi Sun#, Zhuolun He, Yang Bai, Bei Yu, “AutoGraph: Optimizing DNN Computation Graph for Parallel GPU Kernel Execution”, AAAI Conference on Artificial Intelligence (AAAI), Feb. 7–14, 2023.
Wenqian Zhao, Yang Bai, Qi Sun, Wenbo Li, Haisheng Zheng, Nianjuan Jiang, Jiangbo Lu, Bei Yu, Martin D.F. Wong, “A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU”, accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).
Qi Sun, Xinyun Zhang, Hao Geng, Yuxuan Zhao, Yang Bai, Haisheng Zheng, Bei Yu, “GTuner: Tuning DNN Computations on GPU via Graph Attention Network”, ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, Jul. 10–14, 2022.
Qi Sun, Chen Bai, Tinghuan Chen, Hao Geng, Xinyun Zhang, Yang Bai, Bei Yu, “Fast and Efficient DNN Deployment via Deep Gaussian Transfer Learning”, IEEE International Conference on Computer Vision (ICCV), Oct. 11-17, 2021.
Wenqian Zhao, Qi Sun, Yang Bai, Haisheng Zheng, Wenbo Li, Bei Yu, Martin D.F. Wong, “A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 1–4, 2021.
Qi Sun, Chen Bai, Hao Geng, Bei Yu, “Deep Neural Network Hardware Deployment Optimization via Advanced Active Learning”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Feb. 01–05, 2021.
Qi Sun, Tinghuan Chen, Jin Miao, Bei Yu, “Power-Driven DNN Dataflow Optimization on FPGA”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Westminster, CO, Nov. 4–7, 2019.

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