Our Speakers
Gustavo Alonso (ETH Zurich)
Gustavo Alonso is a professor in the Department of Computer Science of ETH Zurich where he is a member of the Systems Group. He graduated in Telecommunications Engineering from the Technical University of Madrid, Spain and did his MSc and PhD at the University of California at Santa Barbara. After graduation, he was a research scientists at the IBM Almaden Research Center in San Jose, California before joining ETH. His research interests include data management, distributed systems, cloud computing architecture, and hardware acceleration through reconfigurable computing. Gustavo has served as PC chair for conferences in several areas and was a member of the VLDB Endowment and the EDBT Executive Board and the Chair of EuroSys, the European Chapter of ACM SIGOPS.
Vasiliki Kalavri (Boston University)
Vasiliki (Vasia) Kalavri is an Assistant Professor of Computer Science at Boston University, where she leads the Complex Analytics and Scalable Processing (CASP) Systems lab. Vasia and her team enjoy doing research on multiple aspects of data-centric systems. Recently, they have been focusing on designing self-managed systems for data stream processing, scaling graph Machine Learning training on modern storage, and developing practical solutions for private collaborative analytics with Multi-party Computation. Before joining BU, Vasia was a postdoctoral fellow at ETH Zurich, where she was awarded the ETH Zurich Postdoctoral Fellowship. She received her PhD from KTH, Stockholm, and UCL, Belgium, after completing a joint doctoral program as an EMJD-DC fellow.
Fatemeh Nargesian (University of Rochester)
Fatemeh Nargesian is an assistant professor of computer science at the University of Rochester. She obtained her PhD at the University of Toronto. She is broadly interested in data management for AI-based data analytics and scientific data management. Her current research includes dataset discovery, responsible data integration, and climate time-series analysis.
Pınar Tözün (IT Uni. Copenhagen)
Pınar Tözün is an Associate Professor at IT University of Copenhagen. Before ITU, she was a research staff member at IBM Almaden Research Center. Prior to joining IBM, she received her PhD from EPFL. Her thesis received ACM SIGMOD Jim Gray Doctoral Dissertation Award Honorable Mention in 2016. Her research focuses on hardware-conscious machine learning, performance characterization of data-intensive systems, and scalability and efficiency of data-intensive systems on modern hardware.
Tilmann Rabl (HPI Berlin)
Tilmann Rabl holds the chair for Data Engineering Systems at the Hasso Plattner Institute and is Professor at the Digital Engineering Faculty of the University of Potsdam. He is also cofounder and scientific director of the startup bankmark. Tilmann Rabl received his PhD at the University of Passau in 2011. He spent 4 years at the University of Toronto as a postdoc in the Middleware Systems Research Group (MSRG). From 2015 to 2019, he was senior researcher and visiting professor at the Database Systems and Information Management (DIMA) group at Technische Universität Berlin and Vice Director of the Intelligent Analytics for Massive Data (IAM) Group at the German Research Center for Artificial Intelligence (DFKI). His research interests include data processing on modern hardware, stream processing, benchmarking, and end-to-end machine learning systems.
Alberto Lerner (University of Fribourg)
Alberto Lerner is a Senior Researcher at the eXascale Infolab at the University of Fribourg, Switzerland. His interests include systems that closely combine hardware and software to realize untapped performance and/or functionality. Previously, he spent years in the industry consulting for large, data-hungry verticals such as finance and advertisement. He had also been part of the teams behind a few different database engines: IBM’s DB2, working on robustness aspects of the query optimizer; Google’s Bigtable, on elasticity aspects; and MongoDB, on general architecture. Alberto received his Ph.D. from ENST - Paris (now ParisTech), having done his thesis research work at INRIA/Rocquencourt and NYU. He has also done post-doctoral work at IBM Research (both at T.J. Watson and Almaden Research labs).
Carsten Binnig (TU Darmstadt)
Carsten Binnig is a Full Professor in the Computer Science department at TU Darmstadt and a Visiting Researcher at the Google Systems Research Group. Carsten received his Ph.D. at the University of Heidelberg in 2008. Afterwards, he spent time as a postdoctoral researcher in the Systems Group at ETH Zurich and at SAP working on in-memory databases. Currently, his research focus is on the design of scalable data systems on modern hardware as well as machine learning for scalable data systems. His work has been awarded a Google Faculty Award, as well as multiple best paper and best demo awards.
Oana Balmau (McGill University)
Oana Balmau is an Assistant Professor in the School of Computer Science at McGill University, where she leads the Data-Intensive Storage and Computer Systems Lab (DISCS Lab). Her research focuses on storage systems and data management, with an emphasis on Machine Learning, Data Science, and Edge Computing workloads. She completed her PhD in Computer Science at the University of Sydney, advised by Prof. Willy Zwaenepoel. Before her PhD, Oana earned her Bachelors and Masters degrees in Computer Science from EPFL, Switzerland. Oana won the CORE John Makepeace Bennet Award 2021 for the best computer science dissertation in Australia and New Zealand, an Honorable Mention for the ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award 2021, as well as a Best Paper Award in the USENIX Annual Technical Conference (USENIX ATC) 2019. Before joining McGill, Oana worked with Nutanix, ABB Research, and HP Vertica. She is also a part of MLCommons, an open engineering consortium that aims to accelerate machine learning innovation, where she is leading the effort for storage benchmarking.
Ioana Manolescu (INRIA Saclay)
Ioana Manolescu is a senior researcher at Inria Saclay and a professor at Ecole Polytechnique, France, where she leads the CEDAR INRIA team focusing on rich data analytics at cloud scale. She has co-authored more than 160 articles in international journals and conferences and co-authored books on “Web Data Management” and on “Cloud-based RDF Data Management”. She has been member of the PVLDB Endowment Board of Trustees, multiple times Associate Editor for PVLDB, president of the ACM SIGMOD PhD Award Committee, chair of the IEEE ICDE conference, and a program chair of EDBT, SSDBM, ICWE among others. She is also a recipient of the ACM SIGMOD Contribution Award 2020. Her research activity spans over semistructured data models, scalable data management, and novel methods and algorithms for fact-checking and data journalism.
Tudor Cioara (UT Cluj-Napoca)
Tudor Cioara is a professor of Computer Science at the Technical University of Cluj-Napoca and leads a research laboratory on distributed systems (https://dsrl.eu/). His research interest is focused on distributed ledgers and their applications in the decentralized management and control of the smart energy grid. He is leading several EU-funded projects that address challenges related to blockchain, peer-to-peer trading, and decentralized energy communities. He received the Romanian Academy award for his contributions in the area of intelligent solutions for energy ecosystems.
