Junzhou Huang

Jenkins Garrett Professor, University of Texas at Arlington

Dr. Junzhou Huang is the Jenkins Garrett Professor in the Computer Science and Engineering department at the University of Texas at Arlington. He is an AIMBE Fellow. His major research interests include machine learning, computer vision, medical image analysis and bioinformatics. Specifically, he focuses on developing efficient machine learning algorithms with nice theoretical guarantees to solve practical problems involved large scale graph data. The significance of his research work is demonstrated by 90+ high-impact journal publications (including Nature Machine Intelligence, Nature Communications, IEEE T. Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research, Medical Image Analysis, bioinformatics, etc.), 100+ highly selective refereed conference publications (such as ICML, NeurIPS, CVPR, ICCV, AAAI, MICCAI, etc.), with a total of 19,000+ citations and H-index 70. His research has been recognized by several awards including the NSF CAREER Award 2016, Google TensorFlow Model Garden Award 2021, UT Rising STARs Award 2022, four Best Paper Awards (MICCAI'10, FIMH'11, STMI'12 and MICCAI'15) as well as two Best Paper Nominations (MICCAI'11 and MICCAI'14). His research projects are supported by both federal/state agencies (NSF/NIH/CPRIT) and industry (Google, Amazon, IBM, Samsung, XtaiPi and Nokia). His recent work on protein folding won the 6th place in the 3D Structure Prediction Challenge (AlphaFold from DeepMind won the 1st place) and the 1st place in the Contact and Distance Prediction Challenge at CASP14, December 2020. 


  • Sparse Learning
  • Deep Graph Learning
  • Trustworthy Learning
  • Robust Learning