Speakers & Lecturers

Keynote Speakers

Sihem Amer-Yahia

Research Director, Deputy Director
CNRS, LIG, France
https://lig-membres.imag.fr/amery/

Sihem Amer-Yahia is a Silver Medal CNRS Research Director and Deputy Director of the Lab of Informatics of Grenoble. She works on exploratory data analysis and algorithmic upskilling. Sihem worked as Principal Scientist at QCRI, Senior Scientist at Yahoo! Research and Member of Technical Staff at at&t Labs. Sihem served as PC chair for SIGMOD 2023 and as the coordinator of the Diversity, Equity and Inclusion initiative for the database community. In 2024, she received the 2024 IEEE TCDE Impact Award, the SIGMOD Contributions Award, and the VLDB Women in Database Award.

Keynote Talk: Building Data-Intensive Systems that Care

Wolfgang Lehner

Research Head, Institute Director
TU Dresden
https://tu-dresden.de/ing/informatik/sya/db/die-professur/inhaber-in

Wolfgang Lehner is professor at TU Dresden, leading the database technology group as well as the institute of systems architecture. He is mostly interested in cross-cutting data management themes from complex analytical tasks and workflows to technologies pushing the envelope in compile and runtime of a data system. He serves the international database community in many ways (e.g. VLDB Endowment, PVLDB Management Editor, PC-CoChair/MetaReviewer/Reviewer activities). He is an appointed member of the German Council for the Sciences and Humanities as well as a member of the Academy of Europe. In this talk, he presents some of the research he and his research team has been conducting regarding "optimizing the optimizer".

Keynote Talk: On Optimizing the Optimizer

Volker Markl

Professor, Group Leader
Technische Universität Berlin - Database Systems and Information Management (DIMA) Group, Germany
https://www.tu.berlin/en/dima/about-us/prof-dr-volker-markl

Volker Markl is a German Professor of Computer Science. He leads the Chair of Database Systems and Information Management (DIMA) at TU Berlin and the Intelligent Analytics for Massive Data Research Department at the German Research Center for Artificial Intelligence (DFKI). In addition, he is Director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD). He is a database systems researcher, conducting research at the intersection of distributed systems, scalable data processing, and machine learning. Between 2010 - 2015, Volker led the DFG-funded Stratosphere project, which resulted in the creation of Apache Flink. He has received numerous honors and prestigious awards including two ACM SIGMOD Research Highlight Awards and best paper awards at leading conferences, such as ACM SIGMOD, VLDB, IEEE ICDE, and EDBT. In 2020, he was named an ACM Fellow for his contributions to query optimization, scalable data processing, and data programmability and earned the ACM SIGMOD Systems Award for Apache Flink in 2023. In 2014, he was elected one of Germany's leading “Digital Minds“ (Digitale Köpfe) by the German Informatics Society. He also is a member of the Berlin-Brandenburg Academy of Sciences (BBAW) and serves as advisor to academic institutions, governmental organizations, and technology companies. Volker holds eighteen patents and has been co-founder and mentor to several startups.

Keynote Talk: Mosaics in Big Data

Course Speakers

Stefania Dumbrava

Associate Professor
ENSIIE - Télécom SudParis, France
https://web4.ensiie.fr/~stefania.dumbrava/

Stefania Dumbrava is an Associate Professor at ENSIIE and at Télécom SudParis, in France. She holds a PhD from Paris-Saclay University in formally verifying data-centric specifications. She is interested in graph databases and the reliability of database query languages, algorithms, and systems. She co-received a SIGMOD Best Industrial Paper Award in 2023, a VLDB Best Regular Paper Runner-Up Award, and a SIGMOD Research Highlight Award in 2022. She co-organized and lectured at the VLDB Summer School (2024 and 2025 editions) and is a regular reviewer and PC member for premier conferences and journals, i.e., EDBT, VLDB, SIGMOD, ICDE, CIKM, WWW, VLDBJ, and TGDK.

Lecture: Graph Databases: Foundations and Data Science Applications

Bettina Kemme

Assistant Professor
School of Computer Science, McGill University, Canada
https://www.cs.mcgill.ca/~kemme/

Bettina Kemme is a Professor of the School of Computer Science at McGill University, Montreal, where she leads the Distributed Information Systems lab. Her general research interests lie in large-scale data management and distributed computing. Her recent projects involved graph-based database management, sustainable data systems for data science, and platform support for advanced data analytics. Bettina holds a PhD degree in Computer Science from ETH Zurich and an undergraduate degree from the Friedrich-Alexander-Universität Erlangen, Germany. She has published well over 100 publications in major journals and conferences in the areas of database systems and distributed systems, including a VLDB Test-of-Time award and a best paper award (runner up). She has served on the editorial board of the VLDB Journal and Information Systems and has been on the program committee or area chair of major database and distributed systems conferences. She was the PC Co-Chair of Middleware 2017, DEBS 2023 and EDBT 2025, and is a senior IEEE member. She co-created the Canadian Workshop series on Data Systems meet Data Science (DSDS).

Lecture: Sustainable Machine Learning

Volker Markl

Professor, Group Leader
Technische Universität Berlin - Database Systems and Information Management (DIMA) Group, Germany
https://www.tu.berlin/en/dima/about-us/prof-dr-volker-markl

Lecture: NebulaStream – Data Stream Processing for the Edge-Cloud-Continuum

Panayiotis Tsaparas

Associate Professor
University of Ioannina, Greece
https://www.cs.uoi.gr/~tsap/

Panayiotis Tsaparas is Associate Professor at the Department of Computer Science and Engineering at the University of Ioannina. He received his Ph.D. from University of Toronto in 2003. Before joining University of Ioannina, he worked as a post-doctoral fellow at University of Rome, “La Sapienza” and at University of Helsinki, and as a researcher at Microsoft Research. His research interests include Data Mining & Machine Learning, Social Network Analysis, and Algorithmic Fairness. He is a Senior ACM member, and he has served several times as a PC and Senior PC member, and reviewer for premier Data Mining and Data Bases conferences and journals. He was PC co-Chair for WSDM 2023. He is currently associate editor for the TKDE and OSNM journals. He has published 75 papers in peer-reviewed conferences and journals, and has filed 12 patents, 8 of which have been awarded.

Lecture: Network Data Science

Yannis Velegrakis

Professor, Group Leader
Utrecht University - Data Intensive Systems, Netherlands
https://velgias.github.io/

Yannis Velegrakis is a professor of Computer Science at Utrecht University, holding a chair on Very Large Data Management. He is the head the Data Intensive Systems group and the leader of the Master’s in Data Science. He is also a professor (on leave) at the University of Trento. His research area of expertise includes Dataset Management, Knowledge Management, Information Integration, Data Curation, and Data Quality. He holds a PhD degree in Computer Science from the University of Toronto. He has been a researcher at the AT&T Research Labs, and has also spent time as a research visitor at IBM Almaden Research Center, the Huawei European Research Center in Munich, the University of California, Santa-Cruz, and the University of Paris-Saclay. He has served in program committees of major Data Management conferences. He has been the general chair for VLDB13 and ICDE24, and the PC Chair for EDBT21. He is serving as a member of the VLDB Endowment and as president of the EDBT Executive Committee. He has also been associate editor or Area Chair for SIGMOD, VLDB, EDBT, and ICDE.

Lecture: From Data Quality to Data Reduction for a Sustainable Future (w. Ramon Rico as the Lab Coordinator)

Lab Coordinators / Assistants

Aljoscha Lepping

Researcher, PhD Candidate
Database Systems and Information Management (DIMA) Group , Germany

https://www.bifold.berlin/people/aljoscha-peter-lepping.html

Aljoscha Lepping is a Ph.D. student in his third year at BIFOLD/TU Berlin, working under Prof. Mark's research group since October 2022. Aljoscha holds both a B.Sc. and M.Sc. in Computer Science from TU Berlin. His research focuses on scalable and extensible end-to-end stream processing on raw data.

Lecture: From Data Quality to Data Reduction for a Sustainable Future (Lab Coordinator/Assistant)

Ramon Rico

Researcher, PhD Candidate
Utrecht University - Data Intensive Systems, Netherlands
https://www.uu.nl/staff/RRicoCuevas

Ramon Rico is a researcher and PhD candidate in Computer Science, a member of the Data Intensive Systems group and of the AI Lab for Sustainable Finance at Utrecht University. He is also an external AI researcher at the ING group in Amsterdam. He has received his BSc Hons. degree in Mathematics from the Autonomous University of Madrid, and his MSc in Computer Science from Utrecht University. He conducted his master thesis on the forefront of data reduction methods, advancing the current state of the art in data forgetting methods. His scientific interests include submodular optimization methods for big data reduction and machine learning methods for financial crime detection, specifically anti-money laundering.

Lecture: From Data Quality to Data Reduction for a Sustainable Future (Lab Coordinator/Assistant)

Speakers & Lecturers

Keynote Speakers

Sihem Amer-Yahia

Wolfgang Lehner

Volker Markl

Course Speakers

Stefania Dumbrava

Bettina Kemme

Volker Markl

Panayiotis Tsaparas

Yannis Velegrakis

Lab Coordinators / Assistants

Aljoscha Lepping

Ramon Rico

Participate

Courses

Venue

Organizers & Committee