All lectures take place in TU Wien’s beautiful Festsaal, and are also streamed via Zoom. For details, please see individual lecture announcements below.

Upcoming Lectures

March 12, 2026, 14:00-15:30 — Kristian Kersting

Technical University of Darmstadt

Professor Dr. Kristian Kersting is a co-director of the Hessian Center for AI (hessian.AI), head of the research department “Foundations of Systemic AI” at the German Research Center for AI (DFKI), and a professor of AI and Machine Learning at TU Darmstadt. After receiving his PhD at the University of Freiburg in 2006, he was with MIT, Fraunhofer IAIS, the University of Bonn, and TU Dortmund University. He is a Fellow of the Association for the Advancement of AI (AAAI), the European Association for AI (EurAI), and the European Lab for Learning and Intelligent Systems (ELLIS), a book author (“How Machines Learn”), and received the inaugural German AI Award 2019. He wrote a regular AI column in the German newspaper Welt (am Sonntag).

March 16, 2026, 10:00-11:30 — Kate Smith-Miles

University of Melbourne

Professor Kate Smith-Miles is a Melbourne Laureate Professor of Applied Mathematics at the University of Melbourne, where she is also Pro Vice-Chancellor (Research Capability), responsible for supporting researchers across all disciplines to deliver research of the highest quality, integrity and impact. She also works closely with industry as Director of the ARC Training Centre for Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). Kate is internationally recognized for her contributions to optimisation, neural networks, machine learning, applied mathematics, and the development of methodologies for trustworthy algorithm evaluation. Her research has pioneered Instance Space Analysis, a framework that reveals when and why algorithms succeed or fail across diverse problem landscapes. This work led to the creation of MATILDA, an online platform supporting rigorous algorithm benchmarking and transparent stress‑testing. Kate has published two books and over 300 refereed papers, supervised more than 30 PhD graduates, and attracted over AUD$70 million in competitive research funding. She has received numerous medals and awards for her research, including a prestigious Australian Laureate Fellowship. She is a Fellow of the Australian Academy of Science, a former President of the Australian Mathematical Society, and was appointed an Officer of the Order of Australia in 2024 for distinguished service to applied mathematics and advocacy for women in STEM.

March 19, 2026, 10:00-11:30 — Matthias Scheutz

Tufts University

Matthias Scheutz, is the Karol Family Applied Technology Professor of computer science and mechanical engineering in the Department of Computer Science at Tufts University in the School of Engineering, the Director of the Human-AI Interaction Center at the Tufts Institute of Artificial Intelligence, and the Director of the Human-Robot Interaction (HRI) Laboratory and the HRI Masters and PhD programs. He is a AAAI and AAAS Fellow with close to 500 peer-reviewed publications in artificial intelligence, artificial life, agent-based computing, natural language understanding, cognitive modeling, robotics, human-robot interaction and foundations of AI and cognitive science. His current research focuses on complex ethical AI-enabled robots with natural language interaction, problem-solving, and fast instruction-based learning capabilities in open worlds.

March 24, 2026, 10:00-11:30 — Shahar Mendelson

Texas A&M University

Shahar Mendelson studies the mathematical foundations of AI and data science. He has been making seminal contributions to the area over three decades, with far reaching implications in machine learning, high dimensional statistics and related aspects of signal processing. Mendelson identified the surprising fact that certain crucial aspects of data science are actually deep mathematical questions in high-dimensional geometry – an area of pure mathematics that explores (counter-intuitive) phenomena that occur when the dimension of the space becomes very large. Thanks to his discovery and the mathematical machinery he has been developing, Mendelson solved some of the most difficult, long-standing open problems in mathematical data science. Mendelson was awarded the medal of the Australian Mathematical Society in 2008 (the highest award given by the AustMS to researchers under the age of 40), and was elected to the Australian Academy of Science in 2024. He holds the Thomas W. Powell ’62 Chair for Science at Texas A&M University, and previously held professorship positions at the Australian National University, Technion-I.I.T, and the University of Warwick, and the Excellence Chair in Artificial Intelligence at Sorbonne University.

Recorded Lectures

February 5, 2026, 10:00-11:30 — Edith Elkind

Northwestern University

Edith Elkind is a Ginny Rometty Professor of Computer Science at Northwestern University. She obtained her PhD from Princeton in 2005 and worked in Israel, Singapore, and the UK before joining Northwestern in 2024. She works on strategic foundations of multiagent systems, with a focus on algorithms for collective decision making. Her book “Computational aspects of cooperative game theory” is a standard reference for the respective field. She is a recipient of an ERC Starting Grant, the SIGAI Autonomous Agents Research Award and is a Fellow of EurAI and ELLIS. She served/is serving as a chair of multiple leading conferences in AI and algorithmic game theory (including IJCAI, AAAI, ACM EC, AAMAS, WINE and COMSOC), and is currently an editor in chief of the Journal of AI Research.

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