Home > Seminars > Meng Jiang - Computational Behavior Modeling (New Graduate-level Course in Spring): A Quick Look of Applications, Challenges, and Models

Meng Jiang - Computational Behavior Modeling (New Graduate-level Course in Spring): A Quick Look of Applications, Challenges, and Models


10/31/2019 at 3:30PM


10/31/2019 at 4:45PM


131 DeBartolo


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Gregory Madey

Gregory Madey

VIEW FULL PROFILE Email: gmadey@nd.edu
Phone: 574-631-8752
Website: http://www.nd.edu/~gmadey/
Office: 325B Cushing Hall


College of Engineering Research Professor
Dr. Madey's research focuses on the use of computer science to develop solutions to a wide range of problems. Recent problem domains include environmental science, the open source software phenomenon, disaster management, modeling & simulation of disease transmission, cyberinfrastructure and ...
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Given massive behavior data available from online platforms, there has been great needs of computational models for tasks such as pattern analysis, prediction, recommendation, and fraud/spam detection. The models are expected to discover knowledge from behavior data to facilitate decision making; however, behavior is complicated – it is produced by various user intention, personal preference, social influence, and spatiotemporal context. The speaker is opening a new graduate-level course in Spring 2020: The focus of this course will primarily be on a series of computational models in data mining and machine learning for building recommender systems and suspicious behavior detection systems. The course will give students an opportunity to implement and experiment with some of the models (e.g., collaborative filtering, matrix factorization, transfer learning, network embedding, spectral graph analysis, graph summarization, and graph neural networks). In this talk, the speaker will take a quick look at applications, challenges, and models of the topic.

Seminar Speaker:

Meng Jiang

Meng Jiang

University of Notre Dame

Meng Jiang is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame. His research interests include data mining, machine learning, and information extraction. His research work focuses on computational behavior modeling. He has published over 50 conference and journal papers of this topic. His work was recognized as ACM SIGKDD 2014 Best Paper Finalist. He has delivered six tutorials in conferences such as ACM KDD, SIGMOD, WWW, CIKM, and IEEE ICDM. His research activities are mainly supported by National Science Foundation. Technologies he developed have been successfully transferred to industry and Army Research Lab.