Presenter bios

Spiros Papadimitriou is mainly interested in data mining for graphs and streaming data, clustering, time series, large-scale data processing, and mobile applications. His interests span from the very small (embedded devices, and sensors; Arduino) to the very large (large-scale data processing and analysis; Hadoop). He has published more than forty papers on these topics in refereed conferences and journals. He received the best paper award in SDM 2008, has three invited journal publications in best paper issues, several book chapters and he has filed multiple patents. He has also been invited to give keynote talks and tutorials on various topics, including graph and social network analysis, time series, stream mining, and large-scale analytics. In the past, he has also developed and released a number of Android applications that have over 50,000 downloads. He is currently an associate professor at Rutgers University (MSIS-RBS). Prior to that, he was a research scientist at Google, and a research staff member at IBM Research. He was a Siebel scholarship recipient in 2005. He obtained his MSc and PhD degrees from Carnegie Mellon University.

Tina Eliassi-Rad is an Associate Professor of Computer Science at Northeastern University in Boston, MA. She is also on the faculty of Northeastern's Network Science Institute. Prior to joining Northeastern, Tina was an Associate Professor of Computer Science at Rutgers University; and before that she was a Member of Technical Staff and Principal Investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison. Her research is rooted in data mining and machine learning; and spans theory, algorithms, and applications of massive data from networked representations of physical and social phenomena. Tina's work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, and cyber situational awareness. Her algorithms have been incorporated into systems used by the government and industry (e.g., IBM System G Graph Analytics) as well as open-source software (e.g., Stanford Network Analysis Project). In 2010, she received an Outstanding Mentor Award from the Office of Science at the US Department of Energy. For more details, visit her website.

Katharina Morik is full professor for computer science at the TU Dortmund University, Germany. She earned her Ph.D. (1981) at the University of Hamburg and her habilitation (1988) at the TU Berlin. Starting with natural language processing, her interest moved to machine learning ranging from inductive logic programming to statistical learning, then to the analysis of very large data collections, high-dimensional data, and resource awareness. Her aim to share scientific results supports strongly as well open source products as students contributing to them. For instance, RapidMiner started out at her lab which continues to contribute to it. Since 2011 she is leading the collaborative research center SFB876 on resource-aware data analysis, an interdisciplinary center comprising 12 projects, 19 professors, and about 50 Ph D students or Postdocs. She was in the first Steering Committee of the IEEE International Conference on Data Mining and chairing the program of this conference in 2004.. She was the program chair of the European Conference on Machine Learning (ECML) in 1989 and one of the program chairs of ECML PKDD 2008. She is in the editorial boards of the international journals “Knowledge and Information Systems” and “Data Mining and Knowledge Discovery”.

Dimitrios Gunopulos got his PhD from Princeton University in 1995. He was a Postoctoral Fellow at the Max-Planck-Institut for Informatics, Research Associate at the IBM Almaden Research Center, Visiting Researcher at the University of Helsinki, Assistant, Associate, and Full Professor at the Department of Computer Science and Engineering in the University of California Riverside, and Visiting Researcher in Microsoft Research, Silicon Valley. His research is in the areas of Data Mining, Data Management, Databases, Sensor and Peer-to-Peer systems, and Algorithms. He has co-authored over a hundred journal and conference papers that have been widely cited (h-index 62) and a book. He has 12 Ph.D. students that have joined industry labs or have taken academic positions. His research has been supported by NSF, the DoD, the European Commission, the General Secretariat of Research and Technology, AT&T, Yahoo, and Nokia. He has served as a General co-Chair in SIAM SDM 2017, HDMS 2011 and IEEE ICDM 2010, and as a PC co-Chair in ECML/PKDD 2011, IEEE ICDM 2008, ACM SIGKDD 2006, SSDBM 2003 and DMKD 2000.