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.

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.
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.