Arizona State University- April 9, 2021
New College of Interdisciplinary Arts and Science
- 8:30 AM – 9:00 AM – Registration/Check in
- 9:00 AM – 5:00 PM – Event on Zoom
Open to Current College & University students, Business and Industry professionals
You are invited to Arizona State University’s virtual Machine Learning Day.
Some Unique Problems with Social Media Data for Machine Learning and AI
Social media data is distinctive from its traditional counterpart and opens the door for interdisciplinary research and allows researchers to collectively study large-scale human behavior otherwise impossible. The study of social media data brings about new challenges for machine learning and data mining. In this talk, we will introduce some unique issues of big social media data, e.g., the big data paradox, the privacy-utility ‘trade-off’, and the evaluation dilemma. We will also mention some efforts of using AI for good if time allows. With data abundance and algorithmic development, we are better equipped than ever to answer challenging and novel research questions and advance AI and CS.
Dr. Huan Liu is a 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, machine learning, social computing, and data science to investigate problems that arise in real-world applications with high-dimensional data of disparate forms. He is a co-author of the textbook, Social Media Mining: An Introduction, by Cambridge University Press. He is Field Chief Editor of Frontiers in Big Data, its Specialty Chief Editor of Data Mining and Management, and a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction. He is a Fellow of ACM, AAAI, AAAS, and IEEE.
The events at Machine Learning Day include keynote speeches from top researchers in academic and industry, oral research presentations, and a virtual poster session. The topics of keynote addresses, presentations and posters cover the theory and practices of machine learning including:
- Adversarial machine learning
- Models, algorithms, and methods of machine learning
- Machine learning for recommendation systems
- Mathematical analysis and machine learning
- Practical applications of machine learning for cybersecurity and online privacy
- Statistical analysis and machine learning
Important things to know:
- Event is FREE
- The event will be held on Zoom
- Registration will close once all spots are full.
- Registration is required