Alexander S. Szalay
Alexander Szalay is a Bloomberg Distinguished Professor, the Alumni Centennial Professor of Astronomy, and Professor in the Department of Computer Science. He is the Director of the Institute for Data Intensive Science. He is a cosmologist, working on the statistical measures of the spatial distribution of galaxies and galaxy formation. He is a Corresponding Member of the Hungarian Academy of Sciences, and a Fellow of the American Academy of Arts and Sciences. In 2004 he received an Alexander Von Humboldt Award in Physical Sciences, in 2007 the Microsoft Jim Gray Award. In 2008 he became Doctor Honoris Causa of the Eotvos University, Budapest.
Source and more information: http://physics-astronomy.jhu.edu/directory/alexander-s-szalay/
Volker Markl is a Full Professor and Chair of the Database Systems and Information Management (DIMA) Group at the Technische Universität (TU) Berlin, Director of the Intelligent Analytics for Massive Data Research Group at the German Research Center for Artificial Intelligence (DFKI), and Director of the Berlin Big Data Center (BBDC). He has published numerous research papers on data management, big data, and data science, in particular in indexing, query optimization, lightweight information integration, and scalable data processing. He holds 19 patents, has transferred technology into multiple commercial products, and advises several companies and startups. He has been Speaker and Principal Investigator of the DFG funded Stratosphere research project that resulted in the Apache Flink Big Data Analytics System. Volker has earned many prestigious awards for his research, teaching, and innovation, including best paper awards at VLDB, EDBT, and BTW, faculty awards from IBM and open innovation awards from HP, and awards by government institutions such as the European Union and the German Ministry for Economics and Energy. He serves as the President-Elect of the VLDB Endowment and was elected as one of Germany’s leading Digital Minds (Digitale Köpfe) by the German Informatics (GI) Society. Most recently, Volker and his team earned an ACM SIGMOD Research Highlight Award 2016 for their work on “Implicit Parallelism Through Deep Language Embedding.”
Peter Z. Revesz
Peter Z. Revesz holds a Ph.D. degree in Computer Science from Brown University (dissertation title: Constraint Query Languages, advisor: Paris C. Kanellakis). He was a postdoctoral fellow at the University of Toronto before joining the University of Nebraska-Lincoln, where he is a professor in the Department of Computer Science and Engineering. He is an expert in databases, data mining and analytics, bioinformatics and computational linguistics. He is the author of Introduction to Databases: From Biological to Spatio-Temporal (Springer, 2010) and Introduction to Constraint Databases (Springer, 2002). Dr. Revesz held visiting appointments at the IBM T.J. Watson Research Center, INRIA, the Max Planck Institute for Computer Science, the University of Athens, the University of Hasselt, the U.S. Air Force Office of Scientific Research and the U.S. Department of State. He is a recipient of an AAAS Science & Technology Policy Fellowship, a J. William Fulbright Scholarship, an Alexander von Humboldt Research Fellowship, a Jefferson Science Fellowship, a National Science Foundation CAREER award, and a Faculty International Scholar of the Year award by Phi Beta Delta, the Honor Society for International Scholars.