Karl Aberer is a full professor for Distributed Information Systems at EPFL Lausanne, Switzerland, since 2000; from 2005 to 2012 the director of the Swiss National Research Center for Mobile Information and Communication Systems (NCCR-MICS, www.mics.ch); since September 2012 he is Vice-President of EPFL responsible for information systems; member of the editorial boards of VLDB Journal, ACM Transaction on Autonomous and Adaptive Systems and World Wide Web Journal.
Assistant Professor in the department of computer systems technology at North Carolina A & T State University. Research interests: Big data Analytics, Cloud Computing, Topic Modelling, and Geo Spatial information systems. Member of IEEE, ACM, and ASEE. Published more than 50 referred journal and conference papers and 4 book chapters.
Ilkay Altintas is a research scientist at SDSC, UCSD since 2001. She has worked on different aspects of data science and scientific computing in leadership roles across a wide range of cross-disciplinary projects. She is a co-initiator of and an active contributor to the open-source Kepler Workflow System, and co-author of publications at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, sensor systems, conceptual data querying, and software modeling.
Jaume Bacardit is a Senior Lecturer in Biodata Mining at Newcastle University. His research is focused on the development of machine learning methods for complex, and large-scale datasets, and the application of these to biological/biomedical problems.
Claudia Bauzer Medeiros is full professor of databases at the Institute of Computing, University of Campinas (Unicamp), Brazil. She has received Brazilian and international awards for research, teaching, and for her work in fostering the participation of women in IT-related activities. Reserch centered on the management of scientific data and eScience, in particular involving agro-environmental planning, biodiversity, workflow systems and geographic information.
Hamilton Distinguished Professor in Computer Science at RPI. Fellow of the ACM, IEEE, and AAAS. Inaugural recipient of the ACM/IEEE-CS Ken Kennedy Award for "influential leadership in the design, development, and deployment of national-scale cyberinfrastructure." U.S. lead of the Research Data Alliance (RDA) and RDA Council co-Chair. Chair of the Anita Borg Institute Board of Trustees. Former Director of the San Diego Supercomputer Center. Former Vice President for Research at RPI.
Christian Bird is a researcher in the empirical software engineering group at Microsoft Research. Christian received B.S. from BYU and his Ph.D. from U.C. Davis.
Research Fellow at the University of New South Wales working on complex network analysis (brain networks, muscle networks and social networks) and electrophysiology.
Christine L. Borgman, Professor & Presidential Chair in Information Studies at UCLA, is the author Big Data, Little Data, No Data ( 2015), Scholarship in the Digital Age (2007) and From Gutenberg to the Global Information Infrastructure (2000), and about 200 other publications in information studies, computer science, and communication. She is a Fellow of the ACM and of AAAS; and a member of the Board of Directors of the Electronic Privacy Information Center.
Léon's primary research interest is machine learning. His contributions to this field address theory, algorithms and large scale applications. Léon's secondary research interest is data compression and coding. His best known contributions are his work on large scale learning and on the DjVu document compression technology. He is serving or has served on the boards of the Journal of Machine Learning Research, IEEE Transactions on Pattern Analysis and Machine and Pattern Recognition Letters.
Titus Brown received his BA in Math from Reed College in 1997, and his PhD in Developmental Biology at Caltech in 2006. He has worked in digital evolution, climate measurements, molecular and evolutionary developmental biology, and both regulatory genomics and transcriptomics. His current focus is on using novel computer science data structures and algorithms to explore big sequencing data sets from metagenomics and transcriptomics.