Dr. Howie Huang is a Full Professor in Department of Electrical and Computer Engineering and Director of the GraphLab at the George Washington University (GWU). He also holds a courtesy appointment in Department of Computer Science and is an affiliated faculty member in Institute for Data, Democracy & Politics (IDDP) at GWU. Motivated by the needs of big data and cybersecurity applications, he works at the intersection of graph algorithms, computer architecture and systems, with focus on developing high-performance computing and machine learning techniques tailored for large-scale graph datasets. His GraphLab explores novel applications of graph-based knowledge discovery in computer systems, cybersecurity, social networks, biology and health. Over the years his research has been supported by around 20 grants of $8M from the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), and Department of Defense (DoD), as well as leading companies including Raytheon, IBM, NVIDIA and Comcast. He received a PhD in Computer Science from the University of Virginia.

Prof. Huang was a recipient of the prestigious National Science Foundation CAREER Award, NVIDIA Academic Partnership Award, Comcast Technology Research and Development Fund Award, IBM Real Time Innovation Faculty Award, and Outstanding Young Researcher Award of School of Engineering and Applied Science. His work on big graph traversal has ranked highly on both the Graph500 and Green Graph500 benchmarks, which measure the performance and energy efficiency of the most powerful data-intensive supercomputers in the world. His research won the Champion Award at both the 2021 and 2018 Graph Challenge of IEEE High-Performance Extreme Computing (HPEC) conference, a Student Innovation Award at the 2018 Graph Challenge, the Finalist and Honorable Mention awards at the DARPA Graph Challenge 2017, the Best Paper Award Nomination at NVMSA'17, the ACM Undergraduate Student Research Competition Winner at the Supercomputing conference (SC'12), a Best Student Paper Finalist at SC'11, the Best Poster Award at PACT'11, and a High-Performance Storage Challenge Finalist at SC'09. A number of his PhD students have become tenure-track assistant professors at major research universities, including College of William and Mary, Stevens Institute of Technology, and University of North Texas.

Prof. Huang is an Associate Editor for IEEE Transactions on Parallel and Distributed Systems (TPDS) and IEEE Transactions on Cloud Computing (TCC). He was awarded 2020 IEEE TCC Editorial Excellence and Eminence Award, and 2021 IEEE TPDS Awards for Editorial Excellence. He has also served as the General Co-Chair of ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC'17), and in technical program committee of various conferences including AAAI, USENIX ATC, FAST, SC, ICS, IPDPS, HPDC, ISC, ICDCS, DAC, CLOUD, BigData, etc. He was the Associate Chair and Interim Chair in Department of Electrical and Computer Engineering in 2015-2016.

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Recent News

  • Check out our publications and GitHub repository

  • Nov 2023 - The JITSpMM work on just-in-time instruction generation for accelerated sparse matrix-matrix multiplication was accepted by CGO'24

  • Oct 2023 - The EdgeTorrent paper on learning real-time temporal graph representation for intrusion detection was presented at RAID'23

  • Jun 2022 - The Mnemonic paper on parallel subgraph matching was presented at IPDPS'22

  • Jun 2022 - Our Illuminati work on GNN explanation for cybersecurity analysis was presented at EuroS&P'22

  • Mar 2022 - Our Euler paper on detecting network lateral movement was presented at NDSS'22

  • Aug 2021 - Our work on stochastic block partition for graphs has won the Champion award in the annual Graph Challenge at 2021 IEEE High-Performance Extreme Computing (HPEC) conference

  • Apr 2021 - PhD graduate Yuede has accepted a position of tenure-track Assistant Professor in Department of Computer Science and Engineering at the University of North Texas.