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Keynotes


Keynote Speakers





Professor and Lab Director
 
EPFL, Switzerland

Prof. Anastasia Ailamaki


Talk : TBD

Abstract : TBD

Bio : Anastasia Ailamaki is a Professor of Computer Sciences at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland and the co-founder of RAW Labs SA, a swiss company developing real-time analytics infrastructures for heterogeneous big data. Her research interests are in data-intensive systems and applications, and in particular (a) in strengthening the interaction between the database software and emerging hardware and I/O devices, and (b) in automating data management to support computationally- demanding, data-intensive scientific applications. She has received an ERC Consolidator Award (2013), a Finmeccanica endowed chair from the Computer Science Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), an NSF CAREER award (2002), and ten best-paper awards in database, storage, and computer architecture conferences. She holds a Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. She is an ACM fellow, an IEEE fellow, the Laureate for the 2018 Nemitsas Prize in Computer Science, and an elected member of the Swiss National Research Council. She has served as a CRA-W mentor, and is a member of the Expert Network of the World Economic Forum.








Computer Science Department and Centre for Cognitive Science
 
TU Darmstadt

Prof. Kristian Kersting


Talk : TBD

Abstract : TBD

Bio : Kristian Kersting is a Professor (W3) for Machine Learning at the Computer Science Department of the TU Darmstadt University, Germany, where he heads the machine learning lab. He is also a Deputy Director of the Centre for Cognitive Science. After receiving his Ph.D. from the University of Freiburg in 2006, he was with the MIT, Fraunhofer IAIS, the University of Bonn, and the TU Dortmund University, where he was a member of the DFG CRC 876 "Providing Information by Resource-Constrained Data Analysis" and also a Co-Director of the Dortmund Center for Data-Based Media Analysis (DOCMA). His main research interests are statistical relational artificial intelligence (AI), probabilistic deep learning, machine learning, and data mining, as well as their applications. Kristian has published over 160 peer-reviewed technical papers and co-authored a book on statistical relational AI. He received the European Association for Artificial Intelligence (EurAI, formerly ECCAI) Dissertation Award 2006 for the best AI dissertation in Europe, a Fraunhofer Attract Research Grant with a budget of 2.5 Million Euro over 5 years (2008-2013), two best-paper awards (ECML 2006, AIIDE 2015), one best poster award (GIS 2011), one best presentation award (NC^2 2015), two outstanding PC/reviewer awards (AAAI 2013, ECCV 2016), a Distinguished Lecturer Award from the University of Jena (2017). In 2019 he was named Top 100 Influential Scholar 2018 for Aritificial Intelligence by AMiner. Kristian was also an ERCIM Cor Baayen Award 2009 finalist, gave several tutorials at top conferences, co-chaired several international workshops such as BeyondLabeler, BUDA, CMPL, CoLISD, DeLBP, DS+J, MLG, SRL, and SymInfOpt as well as the AAAI Student Abstract track and the Starting AI Research Symposium (STAIRS), and cofounded the international workshop series on Statistical Relational AI (StarAI). He regularly serves on the PC (often at senior level) for several top conference, co-chaired the PC of ECML PKDD 2013 and UAI 2017, and is an elected PC co-chair of ECML PKDD 2020. He is the founding Speciality Co-Editor-in-Chief for Machine Learning and AI of Frontiers in Big Data, and is (past) action editor of TPAMI, JAIR, AIJ, DAMI, and MLJ as well as on the editorial boards of KI, NGC, Information, and Big Data and Cognitive Computing.








Professor, Computer Science & Engineering
 
Wright State University

Prof. Amit Sheth


Talk : TBD

Abstract : TBD

Bio : Prof. Sheth is working towards a vision of Computing for Human Experience, which focuses on human-centric future intelligent computing. His recent themes have included semantic-cognitive-perceptual computing over physical-cyber-social big data. Technical components of his work involves semantics empowered Web 3.0 involving enterprise, social, sensor/IoT data as well as services and cloud interoperability. His recent research themes include smart data (coined 2004), semantic sensor web (coined 2007), citizen sensing (coined 2008), and semantic perception (initiated 2010). His earlier work was on federated databases, semantic interoperability and workflow management. His extensive collaborations with clinicians and biomedical researchers encompasses biomedical knowledge discovery; and novel use social media and sensor data for patient-centered care and patient empowerment. Sheth’s most prized achievement is the exceptional success of his past advisees; as of early 2015, 10 of 18 past PhD advisees have 1000+ citations each; two with 5000+ citations.








Full Professor, Computer Science & Engineering
 
University of Washington

Prof. Dan Suciu


Talk : TBD

Abstract : TBD

Bio : I am a full professor in Computer Science and Engineering at the University of Washington. I teach databases and do research in data management. I apply formal theory to novel and difficult data management tasks. My past work has addressed various aspects of managing semistructured data, including query languages, compression, query processing and type inference. My recent work focuses on query processing, both on a single server and on a cluster, probabilistic databases, and finding causal connections in databases.