缪峥 讲师（高校）

缪峥，杭州电子科技大学网络空间安全学院讲师，本硕毕业于南京大学，博士毕业于美国克莱姆森大学。研究领域为高性能计算、分布式与并行计算、异构计算等。读博期间曾在美国阿贡国家实验室和美国太平洋西北国家实验室实习工作一年。近5年在相关领域发表CCF B类及以上高水平论文10余篇，担任SC，ICPP等领域内国际顶级会议审稿人及会议委员。

美国克莱姆森大学，计算机科学， 博士        2017.1 - 2022.5

南京大学，计算机科学与技术，  硕士        2013.9 - 2016.7

南京大学，计算机科学与技术，  本科        2009.9 - 2013.7

2022-09 至 今, 杭州电子科技大学, 网络空间安全学院, 讲师

2020-02 至 2020-08, 美国西北太平洋国家实验室, Department of High Performance Computing, 研究实习员

2018-05 至 2018-08, 美国阿贡国家实验室, Department of Mathematics and Computer Science, 研究实习员

计算机组成原理

云计算技术

主持浙江大华技术股份有限公司横向项目：多模态融合及聚类关键技术研究

[1]     Zheng Miao, Jon C. Calhoun, Rong Ge, Jiajia Li, Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition[J]. ACM Transactions on Parallel Computing, 2023, 10(2): 10.

[2]     Zheng Miao, Jiajia Li, Jon C. Calhoun, Rong Ge, BALA-CPD: BALanced and Asynchronous Distributed Tensor Decomposition[C]. IEEE International Conference on Cluster Computing (CLUSTER), 2022: 440-450. (CCF B类会议)

[3]     Zheng Miao, Jon C. Calhoun, Rong Ge. Relaxed Replication for Energy Efficient and Resilient GPU Computing[C]. IEEE/ACM 11th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS), 2021: 41-50. (CCF A类会议workshop)

[4]     Zheng Miao, Jon C. Calhoun, Rong Ge, Jiajia Li. Sparsity-Aware Distributed Tensor Decomposition, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), Research Poster, 2020. (CCF A类会议)

[5]     Zheng Miao, Jon C. Calhoun, Rong Ge. A Framework for Resilient and Energy-efficient Computing for GPU-accelerated Systems. The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), Research Poster, 2019. (CCF A类会议)

[6]     Zheng Miao, Jon C. Calhoun, Rong Ge. Energy Analysis and Optimization for Resilient Scalable Linear Systems[C]. IEEE International Conference on Cluster Computing (CLUSTER), 2018: 24-34. (CCF B类会议)

[7]     Hui Song, Zheng Miao, Ali Babalhavaeji, Saman Mehrnia, Mahdi Jalili, Xinghuo Yu. Clustering-based Multitasking Deep Neural Network for Solar Photovoltaics Power Generation Prediction[C]. International Joint Conference on Neural Networks, accept, 2024: 1-8. (CCF C类会议)