Panel

Chair Gerti Kappel

Gerti Kappel is full professor at the Institute of Information Systems Engineering at TU Wien, in the Business Informatics Group. Prior to that, from 1993 to 2001, she was a full professor of computer science (database systems) and head of the Department of Information Systems at the Johannes Kepler University Linz. From 2016 to 2019, she was a member of the dean’s team of the Faculty of Informatics responsible for research, diversity, and financial affairs. Since the beginning of 2020 she acts as the dean of the Faculty of Informatics at TU Wien. Her current research interests include Model Engineering, Web Engineering, and Process Engineering, with a special emphasis on cyber-physical production systems. Striving for the unity of research and teaching, she co-authored and co-edited among others „UML@Work“ (dpunkt.verlag, 3rd ed, 2005), „UML@Classroom“ (Springer, 2015), and „Web Engineering“ (Wiley, 2006).

Monika Henzinger

Monika Henzinger specializes in the design of algorithmic systems, including in the area of big data analysis. Her current research focuses include efficient combinatorial algorithms and data structures, especially graph algorithms, and privacy preserving technologies. Monika Henzinger was on the faculty of the University of Vienna from 2009 to 2022 and has been a professor at the Institute of Science and Technology Austria since 2023, where she is currently also the VP of Technology Transfer. After studying computer science in her native country, Germany, she earned her doctorate at Princeton University in the US and worked at Cornell University as an assistant professor. A temporary switch to the private sector culminated in Henzinger’s position as Director of Research at Google. She has authored over 200 academic papers and holds over 80 patents. Her numerous research awards include two Advanced Grants from the European Research Council ERC and the FWF Wittgenstein Award.

Bettina Könighofer

Bettina Könighofer is assistant professor of Formal Methods and Machine Learning at Graz University of Technology. Her research interests lie primarily in the area of reinforcement learning, formal verification, model checking, and runtime monitoring and enforcement. Bettina founded the group Trusted AI, and in her research, she and her group are using state-of-the-art formal methods to test, to verify, and to monitor AI systems with the goal to make sure that AI systems are safe, secure, transparent, accountable, robust, and unbiased. Bettina’s research was the first that provided provable correctness guarantees for deep learning systems.

Gabriele Kotsis

Gabriele Kotsis started her scientific career at the University of Vienna. She received her master’s degree (1991, honored with the Award of the Austrian Computer Society), her PhD (1995, honored with the Heinz-Zemanek Preis) and the venia docendi in computer science (2000) from the University of Vienna. Before joining Johannes Kepler University of Linz (JKU Linz) in October 2002, she was working as a researcher and teacher at the University of Vienna (1991-2001), at the Vienna University for Economics and Business (2001) and at the Copenhagen Business School (2002). Since 2002, Gabriele Kotsis is holding a full professor position in computer science at JKU Linz. She is chairing the Department of Telecooperation with a research focus in mobile computing, multimedia and hypermedia systems as well as cooperative and collaborative systems. Research in those areas includes the investigation of methods, techniques and tools for system development as well as evaluation and analysis with focus on performance evaluation. The Department is participating in numerous national and international projects, including CRUISE, a European network of excellence in sensor networks, EuroFGI, a network of excellence on Future Generation Internet, the AustrianGrid project, or ModelCVS a project on semantics in SW and system modelling, and actively involved in the organisation of international conferences, including for example iiWAS and MoMM. Prof. Kotsis is author of numerous publications in international conferences and journals and is co-editor of several books. She is member of the OCG and the ACM. From April 2003 to April 2007 she was president of the Austrian Computer Society.Since October 2008 she is Vice Rector for Research at the JKU Linz.

Laura Kovács

Laura Kovács is Professor and Head of the Research Unit Formal Methods in Systems Engineering at TU Wien Informatics, where she leads the Automated Program Reasoning (APRe) group. Her research focuses on the design and development of new theories, technologies, and tools for program analysis, with a particular focus on automated assertion generation, symbolic summation, computer algebra, and automated theorem proving. She is the co-developer of the Vampire theorem prover and a Wallenberg Academy Fellow of Sweden. Her research has been awarded with an ERC Starting Grant (2014), two ERC Proof of Concept Grants (2018 and 2025), an ERC Consolidator Grant (2020), and two Amazon Research Awards (2020 and 2023). She receives financial support from LEA (Let’s empower Austria) to promote and organize unplugged computer science workshops for elementary school children as part of TU Wien’s eduLAB.

Claudia Plant

Claudia Plant is professor and head of the Data Mining and Machine Learning research group at the Faculty of Computer Science University of Vienna. Her research group focuses on new methods for exploratory data mining, e.g., clustering, anomaly detection, graph mining and matrix factorization. Many approaches relate unsupervised learning to data compression, i.e., the better the found patterns compress the data the more information we have learned. Other methods rely on finding statistically independent patterns or multiple non-redundant solutions, on ensemble learning or on nature-inspired concepts such as synchronization. Indexing techniques and methods for parallel hardware support exploring massive data. Claudia Plant has co-authored over 150 peer-reviewed publications, among them more than 30 contributions to the top-level data mining conferences KDD and ICDM and 4 Best Paper Awards. Papers on scalability aspects appeared at SIGMOD, ICDE, and the results of interdisciplinary projects in leading application-related journals such as Bioinformatics, Cerebral Cortex and Water Research.

Marta Sabou

Marta Sabou is professor for Information Systems and Business Engineering at the Department for Information Systems and Operations Management at the Vienna University of Economics and Business. Prior to this she was an FWF Elise-Richter Fellow at TU Wien. At TU Wien, she lead the Semantic Systems Research Lab which performs foundational and applied research in the area of information systems enabled by semantic (web) technologies. She has also held positions as Research Fellow at the Knowledge Media Institute (Open University, UK), Assistant Professor at the Department of New Media Technology (MODUL University, AT) and Key Expert in Semantic Technologies (Siemens). Her work is situated at the confluence of Semantic Web and Human Computation research areas. She is an accomplished academic (over 100 peer-reviewed papers, h-index 45) and takes an active role in the Semantic Web research community. Marta Sabou is a Key Researcher in the FWF Cluster of Excellence Bilateral AI, and she co-coordinates the WWTF Vienna Doctoral College on Digital Humanism. She acts as an editorial board member for three journals that publish Semantic Web research (SWJ, IJSWIS, JoDS) and has been engaged in several senior conference organization activities, including: Workshop and Tutorial Chair at ISWC’2022; Knowledge Graph Track co-chair at ESWC’2021; WebScience Track co-chair at WWW’16; Resources Track co-chair at ISWC’16 and program co-chair for ESWC’15 and iSemantics’2013.

Photographs and/or video will be taken at this event. By attending, you grant TU Wien Informatics full rights to use the material (and any reproductions or adaptations) for fundraising, publicity, or other purposes. This may include (but is not limited to) the right to use in our print and online publicity, social media, press releases, and funding applications. If you wish that no photographs explicitly depicting you are used for these purposes, please send an informal message. — Thank you!

Curious about our other news? Subscribe to our news feed, calendar, or newsletter, or follow us on social media.