齐富民

研究方向：高性能计算、软件工程、机器学习

学科类别：计算机科学与技术

简历

2018年于武汉大学计算机学院计算机应用技术专业获得工学博士学位。发表高水平学术论文十余篇，包括CCF A/B/C类期刊或会议，如ICSE、ASE、FSE、IST等论文多篇。长期从事大规模神经网络分布式训练、软件工作量/缺陷预测和网络入侵检测等方面的研究。参与/主持国家重点研发计划，博士后基金等多个项目。     

2018.06 - 2020.05    国家超级计算深圳中心  博士后

参与学术活动情况

1. Local Arrangement Chairs, the 21st International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT’20) and the 11th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP’20), 2020.

2. Committee, International Conference on Advances and Trends in Software Engineering (SOFTENG),2018-2020.

3. Invited Presentation,  Missing data imputation based on low-rank recovery and semi-supervised regression for software effort estimation, International Conference on Software Engineering (ICSE), 2016.

4.Invited Presentation,      Privacy preserving via interval covering based subclass division and manifold learning based bi-directional obfuscation for effort estimation, IEEE/ACM International Conference on Automated Software Engineering (ASE), 2016.