Mohammed J. Zaki
Professor and Department Head, Computer Science
Mohammed J. Zaki is a Professor and Department Head of Computer Science at RPI. He received his Ph.D. degree in computer science from the University of Rochester in 1998. His research interests focus on developing novel data mining and machine learning techniques, especially for applications in text mining, social networks, bioinformatics and personal health. 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 is co-chairing 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 and a Fellow of the ACM.
Ph.D., Computer Science, July 1998, University of Rochester, Rochester, New York
M.S., Computer Science, May 1995, University of Rochester, Rochester, New York
B.S., Computer Science and Mathematics (dual), May 1993, Angelo State University, San Angelo, Texas
- Machine Learning
- Data Mining
- Text Mining
- Graph Mining and Learning
- Data Mining and Machine Learning: Fundamental Concepts and Algorithms, Second Edition, Mohammed J. Zaki and Wagner Meira, Jr, Cambridge University Press, March 2020 (ISBN: 978-1108473989).
- Md. Shamim Hussain, Mohammed J. Zaki, and Dharmashankar Subramanian. Global self-attention as a replacement for graph convolution. In 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Aug 2022.
- Muhammad Abulaish, Mohd Fazil, and Mohammed J. Zaki. Domain-specific keyword extraction using joint modeling of local and global contextual semantics. ACM Transactions on Knowledge Discovery from Data, 16(4):Article 70, January 2022.
- Yuchen Liang, Chaitanya K. Ryali, Benjamin Hoover, Leopold Grinberg, Saket Navlakha, Mohammed J. Zaki, and Dmitry Krotov. Can a fruit fly learn word embeddings. In International Conference on Learning Representations (ICLR). May 2021.
- Yu Chen, Ananya Subburathinam, Ching-Hua Chen, and Mohammed J. Zaki. Personalized food recommendation as constrained question answering over a large-scale food knowledge graph. In Fourteenth ACM International Conference on Web Search and Data Mining (WSDM). Mar 2021.
- Jonathan J. Harris, Ching-Hua Chen, and Mohammed J. Zaki. A framework for generating summaries from temporal personal health data. ACM Transactions on Computing for Healthcare, 2(3):Article 21, 2021.
- Yu Chen, Lingfei Wu, and Mohammed J. Zaki. Iterative deep graph learning for graph neural networks: better and robust node embeddings. In Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS). Dec 2020.
- Diya Li and Mohammed J. Zaki. RECIPTOR: an effective pretrained model for recipe representation learning. In ACM SIGKDD International Conference on Data Mining and Knowledge Discovery. Aug 2020.