Email：sunjw@ustc.edu.cn
地址：安徽省合肥市高新区中国科大高新园区信智楼A709
主要研究方向：高性能计算，性能评测与建模，并行算法，科学计算
孙经纬，特任副研究员。2020年于中国科学技术大学获得计算机软件与理论博士学位。2020至2022年于中国科学技术大学从事博士后研究工作。2018年3月至9月于瑞士苏黎世联邦理工学院访问学习。2021年12月至2022年3月于微软亚洲研究院访问交流。主要研究方向为高性能计算，并行程序性能建模、预测与优化，并行算法等。主持国家自然科学基金青年项目1项。参与国家自然科学基金面上项目1项、重点项目1项，国家重点研发计划1项，华为、京东、阿里巴巴等企业合作项目5项。
代表性论著：
Yunzhuo Wang, Jianfeng Li, Liangying Zhou, Jingwei Sun*, Guangzhong Sun: Multi-Net strategy: Accelerating physics-informed neural networks for solving partial differential equations. Softw Pract Exper. 2022; 1- 24.
Jingwei Sun, Tao Yan, Hao Sun, Huancheng Lin, Guangzhong Sun: Lossy Compression of Communication Traces Using Recurrent Neural Networks. IEEE Trans. Parallel Distributed Syst. 33(11): 3106-3116 (2022)
Jiaqiang Liu, Jingwei Sun*, Zhongtian Xu, Guangzhong Sun: Latency-aware automatic CNN channel pruning with GPU runtime analysis. BenchCouncil Transactions on Benchmarks, Standards and Evaluations 1 (1), 100009
Jingwei Sun, Guangzhong Sun, Shiyan Zhan, Jiepeng Zhang, Yong Chen: Automated Performance Modeling of HPC Applications Using Machine Learning. IEEE Trans. Computers 69(5): 749-763 (2020)
Jiepeng Zhang, Jingwei Sun, Wenju Zhou, Guangzhong Sun: An Active Learning Method for Empirical Modeling in Performance Tuning. IPDPS 2020: 244-253
Jingwei Sun, Shiyan Zhan, Guangzhong Sun, Yong Chen: Automated Performance Modeling Based on Runtime Feature Detection and Machine Learning. ISPA/IUCC 2017: 744-751
Jingwei Sun, Guangzhong Sun: SPLZ: An efficient algorithm for single source shortest path problem using compression method. GeoInformatica 20(1): 1-18 (2016)
