Conférences invitées

Iryna Gurevych is Professor of Ubiquitous Knowledge Processing in the Department of Computer Science at the Technical University of Darmstadt in Germany. She also is an adjunct professor at MBZUAI in Abu-Dhabi, UAE, and an affiliated professor at INSAIT in Sofia, Bulgaria. She is widely known for fundamental contributions to natural language processing (NLP) and machine learning. Professor Gurevych is a past president of the Association for Computational Linguistics (ACL), the leading professional society in NLP. Her many accolades include being a Fellow of the ACL, an ELLIS Fellow, and the recipient of an ERC Advanced Grant. Most recently, she has received the 2025 Milner award of the British Royal Society for her major contributions to NLP and artificial intelligence that combine deep understanding of human language and cognitive faculty with the latest paradigms in machine learning.

Welcoming AI as a New Colleague: How Should We Evaluate AI for Science?

AI is reshaping the work of researchers in real time. With the emergence of tools such as AI Scientist in 2024, a new era of AI-driven scientific discovery has begun. At the same time, high-profile venues are beginning to experiment with AI-assisted peer review. Yet the core question remains unresolved: How should we meaningfully evaluate AI for scientific work? In this talk, I will highlight challenges encountered in several projects focused on AI-assisted scientific communication and discuss how these challenges inform evaluation practices. I will examine methods for assessing AI-generated related-work sections and explore how automated reviewers can be evaluated with respect to research-design reasoning and novelty assessment. Together, these examples illustrate both the promise and the complexity of evaluating AI as it increasingly acts as a collaborator in scientific communication.

Johannes Schneider is Full Professor of Data Science and Artificial Intelligence at the University of Liechtenstein. He previously conducted research at the industrial research laboratories of IBM and ABB. He earned a PhD and MSc in Computer Science as well as a Master of Advanced Studies in Management, Technology, and Economics – all from ETH Zurich. His research spans both the theoretical foundations and practical applications of AI and data science. He has received multiple best paper awards, and his work appears in leading venues across computer science, information systems, and business, including conferences such as NeurIPS, ICML, AAAI, IJCAI, CIKM, SDM, ICIS, FOCS, and STOC, and journals such as the Journal of the ACM (JACM), Data Mining and Knowledge Discovery (DMKD), European Journal of Information Systems (EJIS), Journal of the Association of Information Systems (JAIS), International Journal of Information Management (IJIM), and Business & Information Systems Engineering (BISE).

AI agents: Where are they today? Where are they going?

AI agents promise to disrupt society. They increasingly operate autonomously, executing complex workflows. On the one hand, they solve PhD-level tasks, but they also fail at tasks that are simple for non-experts. They can use and create tools, and learn from a limited set of prior experiences. However, memory management and continuous learning through parameter updates remain major challenges. Against this background, this talk surveys the state of the art of AI agents, demonstrating their capabilities while also exposing their weaknesses. Though the talk is mostly focused on technology, it concludes with possible scenarios for how AI agents might impact society on a wider scale.

Titre de la présentation à venir