English Version
北卡罗莱纳州立大学Xipeng Shen教授学术报告





Modern Computing and Intelligent Programing Systems


AbstractIn this talk, Dr. Shen will discuss some recent progress in the development of intelligent programming systems, especially in raising program analysis and optimizations to a new level, unleashing the hidden power of compilers, and making applications better harness

the power of modern heterogeneous systems (e.g., GPU). He will demonstrate how the progress helps meet some major challenges in modern computing, including the rapid increase of the volume and variety of data, the rise of deep learning, the shift of computing towards cloud and IoT, and the fast development of heterogeneity in processors and memory.


Bio (报告人简介):

Xipeng Shen is an Associate Professor in the Computer Science Department at North Carolina State University in USA. He has received a number of recognitions, including Early Career Research Award from the US Department of Energy, CAREER Award from US NSF, Google Faculty Research Award, IBM Center for Advanced Studies Faculty Fellow Award, ACM Distinguished Speaker, and so on. His primary research work lies in the field of programming systems and high performance machine learning, featuring an emphasis on inter-disciplinary problems and approaches. His research has produced influential results in multicore and GPU code optimizations, as well as progresses in machine learning, exemplified with a series of new machine learning algorithms (e.g., Yinyang K-Means, Multi-label Scene Classification) published at major ML/AI venues and adopted by Microsoft and other industry companies.

Prior to joining NC State in 2014 as a Chancellor's Faculty Excellence Program cluster hire in Data-Driven Science, Shen was the Adina Allen Term Distinguished Associate Professor in the Computer Science Department at The College of William and Mary. He spent his sabbatical at MIT, Microsoft Research, and Intel Labs between 2012 and 2013. He was an assistant professor at The College of William and Mary from 2006 to 2012. He received his Ph.D. in Computer Science from University of Rochester in 2006.

慎熙鹏是美国北卡州立大学计算机系的副教授。他获得美国能源部Early Career 研究奖,美国自然基金CAREER奖,谷歌教师研究奖,IBM CAS 教师研究奖, 北卡州立大学学者奖。他是ACM杰出演讲者。他的研究主要在编程系统和高性能机器学习领域,特别关注于交叉领域的问题和方法。他的研究在多核和GPU程序优化方面产生了很多影响。同时,他的研究产生了一系列新的高性能机器学习的算法(例如Yinyang K-Means, Multi-label Scene Classification),得到工业界的采纳和应用。

2014年加入北卡州立大学之前,慎教授是美国威廉玛丽学院的一名Adina Allen冠名副教授。他曾是麻省理工和微软研究院的访问科学家,并担任英特尔 实验室和思科的顾问。他于2006年在美国罗切斯特大学获取计算机博士学位,于 2001年在中科院自动化所获取硕士学位,于1998年在北方工业大学获取学士学位。