Prof. Mohammed J Zaki, Rensselaer Polytechnic Institute (RPI), Troy, New York gave a talk on Graph Transformers to the Max on 24 June at institute’s KRB Auditorium.
Graph Transformers (GTs) are powerful models for graph learning. In this talk Prof Zaki presented his recent work on improving graph transformers along several directions. Building upon his work on Edge-Augmented Graph Transformer (EGT), he proposed the Triplet Graph Transformer (TGT) model that can learn higher order node interactions via a novel tripled attention mechanism. Combined with a novel three-stage learning strategy TGT achieves new state-of-the-art results on molecular property prediction tasks on challenge benchmarks. Prof Zaki also talked about his work on directed graph transformer (DiGT).
Prof. Mohammed J Zaki is a Professor and Department Head of Computer Science at RPI. He received his Ph.D in computer science from the University of Rochester in 1998. His research interests focus on novel data mining and machine learning techniques, particularly for learning from graph structured and textual data, with applications in bioinformatics, personal health and financial analytics. He has around 300 publications (and 6 patents), including the Data Mining and Machine Learning textbook (2nd Edition, Cambridge University Press, 2020). He is the founding co-chair for the BIOKDD series of workshops. He is currently an associate editor for Data Mining and Knowledge Discovery, and he has also served as Area Editor for Statistical Analysis and Data Mining, and as Associate Editor for ACM Transactions on Knowledge Discovery from Data, and Social Networks and Mining. He was the program co-chair for SDM’08, SIGKDD’09, PAKDD’10, BIBM’11, CIKM’12, ICDM’12, IEEE BigData’15, and CIKM’18, and he recently co-chaired CIKM’22. He is currently serving on the Board of Directors for ACM SIGKDD. He was a recipient of the National Science Foundation CAREER Award and the Department of Energy Early Career Principal Investigator Award, as well as HP Innovation Research Award, and Google Faculty Research Award. His research is supported in part by NSF, DARPA, NIH, DOE, IBM, Google, HP, and Nvidia. He is a Fellow of the IEEE, a Fellow of the ACM, and a Fellow of the AAAS.
June 2024