Events Calendar

CS Colloquium: Huan Liu (Arizona State University) - Social Media Mining: A Bountiful Frontier in AI

Speaker: Huan Liu , Arizona State University

Talk Title: Social Media Mining: A Bountiful Frontier in AI

Series: CS Colloquium

Abstract: Social media data differs from conventional data in many ways. It is not only big, but also noisy, linked, multimodal, and user-generated. Unprecedented opportunities thus emerge for CS and AI research through the lens of social data. In this talk, I use examples to illustrate: (1) fundamental problems associated with social media, that challenge common practice and existential understanding in machine learning and data mining; (2) intriguing questions, unique to social media, that can be answered by mining social media; and (3) how we can make a difference -“ that is, contribute to society at large - by developing novel socially responsible AI algorithms in our work on social media mining and AI. There are great opportunities ahead for research, teaching, and interdisciplinary collaborations in advancing knowledge in CS, AI, and data science.

This lecture satisfies requirements for CSCI 591: Research Colloquium

Biography: Dr. Huan Liu is Professor of Computer Science and Engineering at Arizona State University. He was recognized for excellence in teaching and research in Computer Science and Engineering at ASU. His research interests include AI, data mining, feature selection, and social media mining. He co-authored the textbook, Social Media Mining: An Introduction, by Cambridge University Press. He graduated 32 PhD students at ASU and many of them won highly coveted awards (click here for their first job after graduation). He is Founding Field Chief Editor of Frontiers in Big Data, its Specialty Chief Editor of Data Mining and Management, Editor in Chief of ACM TIST, and Conference Co-Chair of ACM WSMD2022. His research has been funded by NSF, AFOSR, AFRL, ARL, ARO, DARPA, NASA, and ONR, among others. He is a Fellow of AAAI, AAAS, ACM, and IEEE.

Host: Laurent Itti

Location: Ronald Tutor Hall of Engineering (RTH) - 115

Audiences: Everyone Is Invited

Contact: Assistant to CS chair