Ethics and Professionalism in the Age of Social Data

Tuesday, Novemeber 21
4:00 - 5:30


Huan Liu

Dr. 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 a co-author of Social Media Mining: An Introduction by Cambridge University Press. He serves on journal editorial boards and numerous conference program committees, and is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction. He is an IEEE Fellow.

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Tanushree Mitra

Tanushree Mitra is an assistant professor of Computer Science at Virginia Tech, where she leads the Social Computing research group. She and her students study and build large-scale social computing systems using a range of interdisciplinary methods from the fields of data mining, machine learning, natural language processing, and human computer interaction. Dr. Mitra is particularly interested in addressing socially relevant problems which are created by social computing technologies and which are often amplified by participation in online social platforms. She received her Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech. Her research has been recognized through multiple awards and honors, including an Honorable Mention at ACM SIGCHI, an IBM PhD fellowship, and GVU center’s Foley Scholarship for research innovation and potential impact. Many of her academic contributions have also received widespread press coverage by notable news channels. She has also conducted social computing research in the neXus group at Microsoft Research and the Collaborative User Experience group at IBM Research.

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Eirini Ntoutsi

Eirini Ntoutsi is an associate professor of Electrical Engineering and Computer Science at the Leibniz University of Hanover (LUH), Germany and member of the L3S research center. Prior to joining LUH, she was a post-doctoral researcher at the Ludwig-Maximilians-University (LMU) in Munich, Germany in the group of Prof. Hans-Peter Kriegel. She joined the group in 2010 as a post-doctoral fellow of the Alexander von Humboldt Foundation. In 2009 she worked as a data mining expert for the national telecomunication provider of Greece. She obtained her PhD from the University of Piraeus, Greece where she defended her thesis "Similarity Issues in Data Mining - Methodologies and Techniques" in 2008. Her research interests are in the areas of data mining and machine learning and can be summarized as learning over complex data (e.g., high dimensional, multi-view, noisy) and data streams. She serves on numerous conference program committees and is publicity co-chair for ICDM 2017.

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Jilles Vreeken

Jilles Vreeken leads the Exploratory Data Analysis group at Saarland University, and in addition is a Senior Researcher at the Max Planck Institute for Informatics. He pursued his Ph.D. at Utrecht University, the Netherlands, where he defended his thesis 'Making Pattern Mining Useful' in 2009. Between 2009 and 2013 he was a post-doctoral researcher at the University of Antwerp, Belgium. His research interests include data mining and machine learning. He is particularly interested in developing well-founded theory and efficient methods for extracting informative models and characteristic patterns from large data, and putting these to good use. He has authored over 70 conference and journal papers, 3 book chapters, won the 2010 ACM SIGKDD Doctoral Dissertation Runner-Up Award, and two best paper awards. He was tutorial chair for SIAM SDM 2017, program co-chair for ECML PKDD 2016, sponsorship co-chair for ECML PKDD 2014, and workshop co-chair of IEEE ICDM 2012. He co-organised nine workshops and four tutorials. He is a member of the editorial board of Data Mining and Knowledge Discovery (DAMI) and of the ECML PKDD Journal Track Guest Editorial Board.

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