Reza Zafarani is an Assistant Professor of EECS at Syracuse University. Reza's research interests are in Social Media Mining, Data Mining, Machine Learning, and Social Network Analysis.  His research emphasis has been on addressing challenges in large-scale data analytics to enhance the scientific discovery process from big data, especially in social media. These challenges include evaluation without ground truth, fast identification of relevant information in massive datasets, learning with limited information, user behavior analysis and modeling at scale, and information integration and modeling across multiple data sources.  His research has been published at major academic venues, and highlighted in various scientific outlets. Reza is the principal author of “Social Media Mining: An Introduction”, a textbook by Cambridge University Press and the associate editor for SIGKDD Explorations and Frontiers in communication. He is the winner of the President's Award for Innovation and outstanding teaching award at Arizona State University. 

Xinyi Zhou is a Ph.D. candidate of Computer and Information Science and Engineering at Syracuse University (SU). She also works as a research assistant at Data Lab advised by Dr. Reza Zafarani. Her research interests span machine learning, text and graph mining, and social computing with an emphasis on fake news research. Her work has been accepted to the conferences such as KDD, WSDM, CIKM, PAKDD, and ICWSM, and journals such as ACM Computing Surveys (CSUR).  She serves as a PC member for the conferences such as SIGIR and ECIR, and a reviewer for the journals such as CSUR, ACM Transactions on the Web (TWEB), IEEE Transactions on Multimedia (TMM) , and IEEE Intelligent Systems. Two of her first-author publications have been selected in The 100 Most Influential Research Papers in China in 2017. 

She awarded the National Scholarship and the Varshney Scholarship recognized to only one student at SU. She worked as a research intern at the University of Southern California, advised by Dr. Emilio Ferrara. For more information, please see her homepage: https://www.xzhou.net/

Kai Shu is a PhD student majoring in computer science at Arizona State University. He also works as a research assistant at the Data Mining and Machine Learning Lab (DMML), supervised by Dr. Huan Liu. He has published innovative works in top-tier conferences such as CIKM, WSDM, WWW, IJCAI, AAAI, ICDM. His current research interests include social media mining, machine learning, deep learning based generative models, fake news detection. He is the principal architect for FakeNewsTracker, an advanced visual analytic system for fake news collection, detection, and visualization, which also won the SBP disinformation challenge award in 2018. He also worked as a research intern at Yahoo Research in 2018.

Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He obtained his Ph.D. in Computer Science at University of Southern California and B.Eng. in Computer Science and Electrical Engineering at Shanghai JiaoTong University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. At Arizona State University, he was recognized for excellence in teaching and research in Computer Science and Engineering and received the 2014 President's Award for Innovation. His research interests are in data mining, machine learning, social computing, and artificial intelligence, investigating interdisciplinary problems that arise in many real-world, data-intensive applications with high-dimensional data of disparate forms such as social media. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He is an IEEE Fellow.