Xipeng Shen

Xipeng Shen is a Professor in the Department of Computer Science at North Carolina State University and Director of the High-Performance Intelligent Computing (HiPIC) lab. He joined NC State in 2014 as part of the Chancellor's Faculty Excellence Program after serving as the Adina Allen Term Distinguished Associate Professor at the College of William and Mary.

Shen's research spans programming systems and machine learning, with a focus on enabling extreme-scale, data-intensive, and intelligent computing through innovations in compilers, runtime systems, and ML algorithms. His work has significantly influenced the development of heterogeneous computing and modern AI systems. His research areas include High-Performance Machine Learning & Real-Time AI, Heterogeneous Massively Parallel Computing, and Foundations of Programming Systems & Languages.

His recent publications demonstrate strong trends in optimizing AI deployment across various platforms including mobile devices, serverless environments, and edge computing systems, with particular emphasis on efficiency, power consumption, and real-time performance. His research increasingly integrates compiler techniques with machine learning approaches to solve complex optimization problems.

• ACM Distinguished Member (2018)
• University Faculty Scholar (2017-18)
• ACM Distinguished Speaker (2016-2019)
• IEEE Senior Member (2016)
• IBM CAS Faculty Research Fellow (2010-2016)
• Google Faculty Research Award (2015)
• DOE Early CAREER Award (2011)
• NSF CAREER Award (2010)

Shen has successfully advised 15 PhD students who have gone on to positions at top universities and companies including UC Santa Cruz, UMass Amherst, Google, Meta, and Huawei. His research has been funded by numerous grants from NSF, DOE, and NIH totaling over $4 million. He co-founded CoCoPIE Inc. to commercialize his research on efficient AI deployment and serves as a consultant to major technology companies including Intel, Microsoft, Huawei, Cisco, and Meta.

He leads the PICTure research group and teaches courses including Compiler Construction (CSC412/512), Code Optimization for Scalar and Parallel Programs (CSC766), and Real-time AI and Machine Learning Systems (CSC591/791).