Jasmina Bogojeska is Full Professor at ZHAW School of Engineering. Previously, she was Senior Principal Data Scientist at Roche Diagnostics, and a machine learning scientist at IBM Research – Zurich working in the areas of machine learning, deep learning and natural language processing (NLP).

She received her M.S. and Ph.D. degrees both in Computer Science from the Max-Planck Institute for Informatics/Saarland University, Germany in 2007 and 2011, respectively. The main focus of her work is application-inspired machine learning where she is developing and applying machine learning solutions to various challenging real-world problems from the areas of healthcare, services research and document analysis. Jasmina has published her research in renowned international journals and presented her work at national and international conferences. She was a recipient of the IMPRS-CS fellowship awarded by the Max-Planck Society in 2005, IBM’s Corporate Research Award in 2017 and several IBM research accomplishment awards.

Univ.Prof. Dipl.-Inf. Dr.-Ing. Katja Hose was appointed as University Professor for Data Management at TU Wien with effect from March 1, 2023. She is assigned to the Institute of Logic and Computation , opens an external URL in a new window(E192) at the Faculty of Informatics, opens an external URL in a new window.

Katja Hose comes from Eschwege (Hesse) in central Germany and studied computer science at the TU Ilmenau in neighboring Thuringia, where she also wrote a dissertation in 2009 on the subject of "Processing Rank-Aware Queries in Schema-based P2P Systems, opens an external URL in a new window". After a 3-year stopover as a PostDoc at the Max Planck Institute for Computer Science in Saarbrücken (Saarland), she started her academic career at the Department of Computer Science at Aalborg University, opens an external URL in a new window in Denmark (Jutland); first as an assistant professor, from 2015 as an associate professor and finally from 2018 as a university professor. In that capacity, she was also ultimately the research director of the Data, Knowledge, and Web Engineering, opens an external URL in a new window research group in the Department of Computer Science.

Katja Hose's scientific home is the Research Unit of Database and AI, opens an external URL in a new window at the institute mentioned, where she deals with topics of data management and knowledge engineering and pursues the goal of developing new fundamentals and methods, Giving meaning to large amounts of heterogeneous data and making the best use of it.

Dr. Georgia Koutrika is Research Director at the Athena Research Center in Greece. Prior to that, she had more than 15 years of experience in multiple roles at HP Labs, IBM Almaden, and Stanford. Her work focuses on interactive and intelligent data exploration and data management systems and combines advanced data analysis, deep learning, and natural language processing techniques. Her work has been incorporated into commercial products, described in 14 granted patents and 26 patent applications in the US and worldwide, and published in more than 100 papers in top-tier conferences and journals.

Georgia is an ACM Senior Member, an IEEE Senior Member, and an ACM Distinguished Speaker. She is a member of the VLDB Endowment Board of Trustees and a member of the ACM-RAISE Working Group. She is co-EiC for the VLDB Journal, PC co-chair for VLDB 2023, and co-EiC of the Proceedings of the VLDB (PVLDB). She has served or serves as associate editor for top conferences (such as ACM SIGMOD and VLDB) and journals (TKDE and VLDB Journal), as well as in various organization roles, including EDBT 2023 and ICDE 2021 sponsorship chair and general chair for ACM SIGMOD 2016.

I am professor of Computer Science at Université Grenoble Alpes in the LIG laboratory. I am the head of the “Data Analytics, Intelligent and Scalable” DAISY team and the co-director of the M2 MoSIG (Master of Science in Informatics in Grenoble). My previous positions were associate professor at Université Paris-Saclay, visiting researcher at Inria and École Normale Supérieure, researcher at Huawei Hong Kong, and postdoctoral fellow at the University of Hong Kong.

I received my French research direction habilitation (HDR) in 2022 at Université Paris-Saclay, the Ph.D. degree in computer science from Télécom Paris in 2012, and my Dipl.Ing. from Politehnica University in Timisoara, Romania in 2005.

I am a Distinguished Professor of Computer Science at Universite Paris Cite, Senior Fellow of the French University Institute (IUF), a distinction that recognizes research excellence across all scientific disciplines, ACM Senior Member and Distinguished Speaker, Director of LIPADE (Computer Science department), and Director of the Data Intelligence Institute of Paris (diiP), an IdEx-funded (Initiative of Excellence) interdisciplinary institute that includes the Universite Paris Cite, Sciences Po university, the University Sorbonne Paris Nord, and the French Institute for Demographic Studies (INED).

Is My research is on problems related to data science, focusing on online and offline big data analytics and machine learning applications. It has been funded by the EU, IUF, CNRS, Facebook, IBM Research, HP Labs, Safran, Huawei, FMJH (supported by EDF and Thales), Telecom Italia, and PAT, and has led to an IBM Shared University Research Award, 3 Best Paper awards in international conferences, 10 US Patents (3 are part of commercial systems), 1 European Patent, and 2 French Patents.

My PhD focuses on the legal implications of scoring, profiling and more generally evaluating individuals. This involves articulating the existing package of EU laws regarding the matter (GDPR, DSA, DMA etc.) with its upcoming AI regulation. In this context, researching scores and profiles of individuals means crossing insights from pragmatist philosophy, the sociology of valuation and quantification or science and technology studies with classical legal interpretation of the above-mentioned regulations. This will allow me to clarify what it means to evaluate an individual, whether it is legal to do so - counterintuitively, this isn’t obvious! - and if yes, what substantial and processual protection is afforded to them.

Yannis Velegrakis is a professor of Computer Science at Utrecht University, where he holds the chair of Very Large Data Management. He is the head of the Data Intensive Systems group and the leader of the Master's in Data Science. He is also a faculty member at the University of Trento, and a PI with the Archimedes AI and Data Science hub, of the Athena Research Center.

His research areas of expertise include Big Data Management & Analytics, Knowledge Discovery, Graph Management, Highly Heterogeneous Information Integration, Dataset Querying, and Data Quality.

He holds a PhD degree from the University of Toronto and a MSc. and BSc. degree from the University of Crete, all in Computer Science. In the past he has been a researcher at the AT&T Research Labs. He has spent time as a visitor at the IBM Almaden Research Center, the Huawei European Research Center in Munich, the Center of Advanced Studies of the IBM Toronto Lab, the University of California, Santa-Cruz, the University of Paris-Saclay, and the University of Paris-Saclay, He has served in program committees of many national and international conferences and has been a reviewer for numerous international journals in the area of Data Management. He has been a general chair for VLDB2013, ICDE24 and PC Chair for EDBT21.