Academic Lectures
We have invited several high-level experts and research leaders to give lectures and share knowledge with you. Here is a short overview of their background and abstracts.
Andrea Stocco – Testing of Autonomous Driving Systems: From Simulated to Real-world Environments
Technical University of Munich Homepage, Google Scholar
Abstract: Autonomous driving systems (ADS) require extensive testing to ensure safety, reliability, and robustness across a wide spectrum of operational conditions. This talk introduces the state of the art in testing and evaluation of ADS, with a particular focus on simulation-based techniques and the challenges of transferring results from simulation to real-world environments. We discuss approaches for scenario generation and performance assessment, as well as current limitations in realism, sensor modeling, and non-deterministic behavior. Finally, the talk explores emerging research directions, such as sim2real consistency analysis, uncertainty quantification, and AI-driven test generation.
Bio: Andrea Stocco is an Assistant Professor at the Technical University of Munich at the Chair of Software Engineering for Data-intensive Applications of the School of Computation, Information and Technology. He is also the head of the Automated Software Testing unit at fortiss. His research focuses on the interface between software engineering and deep learning with the goals of improving the robustness, reliability, and dependability of data-intensive software systems. He is the recipient of several awards, including a Distinguished Paper Award at the 33rd IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2026), and two Distinguished Paper Awards at the 18th International Conference on Software Testing, Verification and Validation (ICST 2025). He serves on the program committees of top-tier software engineering conferences such as ICSE, FSE, ASE, ISSTA and ICST, and reviews for numerous software engineering journals including TSE, TOSEM, EMSE, JSS, and IST.
Pan Hui - Reinventing Education and Art with AI and Metaverse
University of Helsinki Homepage, Google Scholar
Abstract: Talk explores groundbreaking innovations in education and creative expression through the pioneering work of the Center for Metaverse and Computational Creativity (MC2) at HKUST(GZ). The presentation examines three transformative initiatives reshaping the educational landscape: the Metaverse classroom that bridges geographical barriers between campuses through immersive virtual environments, the world's first AI lecturers successfully deployed in higher education with 90% student approval, and the upcoming interactive AI lecturers capable of real-time engagement and personalized feedback.
These implementations demonstrate how cutting-edge technology creates more inclusive, interactive, and engaging learning experiences. The presentation highlights student responses, global media recognition, and research findings that validate the potential of these technologies to complement rather than replace traditional teaching methods, fostering collaborative learning that transcends physical limitations.
As we move toward the speaker’s vision of “Surreality”—a future in which virtual and physical worlds seamlessly coexist—this talk explores how AI and Metaverse technologies can serve not merely as tools, but as catalysts for reimagining the foundations of education and artistic creation. It examines how these emerging technologies prepare learners for a world where the boundaries between the digital and the physical dissolve into immersive, collaborative experiences, transforming both teaching and creative expression. Curated by the speaker, the Surreality exhibition was the world’s first large-scale MR × AI art exhibition, offering audiences a glimpse into this emerging future—where a new reality awaits.
Bio: Professor Pan Hui is a Chair Professor of Computational Media and Arts, and Director of the Center for Metaverse and Computational Creativity at Hong Kong University of Science and Technology (Guangzhou), and a Chair Professor of Emerging Interdisciplinary Areas at Hong Kong University of Science and Technology. He is also the Nokia Chair in Data Science at the University of Helsinki. He was a senior research scientist and then a Distinguished Scientist for Telekom Innovation Laboratories (T-labs) Germany. His industrial profile also includes his research at Intel Research Cambridge and Thomson Research Paris. His research has been generously sponsored by major industry players such as Nokia, Deutsche Telekom, Microsoft Research, and China Mobile. He has published more than 500 research papers and with over 40,000 citations. He has 32 European and US patents. Prof. Hui is an internationally recognized scholar, having been elected as an International Fellow of the Royal Academy of Engineering and a Member of the Academia Europaea. He is also a Fellow of IEEE and a Distinguished Scientist of the ACM. In addition to his academic accomplishments, Prof. Hui is a founding member of the INTEPOL Expert Group on Metaverse and a member of the World Economic Forum Global Future Council on the Future of Metaverse. Prof. Hui obtained his Computer Science PhD degree from the University of Cambridge.
Vaclav (Vashek) Matyas – Process, Proof, and Practice: A Deep Dive into Common Criteria Security Certification; The Reality of Certified Security: Mining the CC and FIPS Ecosystems with Sec-Certs
Professor at Masaryk University Homepage, Google Scholar
Abstract: First talk offers a clear overview of the Common Criteria (CC) certification ecosystem - how Protection Profiles and EAL levels shape evaluations, and why the scheme emphasizes the development process as a proxy for product security. It also examines the role of formal verification within CC and reflects on the framework’s strengths, limitations, and where modern updates are most needed.
Second talk: Even under rigorous frameworks like Common Criteria and FIPS 140, critical vulnerabilities (e.g., RoCA, TPM-Fail) still emerge in highly assured products, and assessing their impact is complicated by fragmented certification data and hidden dependencies. This talk presents large-scale automated analyses of tens of thousands of certification documents and shows how the open-source sec-certs toolkit links vulnerabilities to certificates and reconstructs product dependency networks to enable faster, more effective mitigation.
Bio: Vashek (Václav) Matyáš is a Professor at Masaryk University, Brno, heading its Centre for Research on Cryptography and Security. His research interests relate to applied cryptography and security; with over 200 peer-reviewed papers and articles. He worked also with Cybernetica, Red Hat Czech, CyLab at Carnegie Mellon University, as a Fulbright-Masaryk Visiting Scholar at Harvard University, Microsoft Research Cambridge, University College Dublin, Ubilab at UBS AG, and as a Royal Society Postdoctoral Fellow with the Cambridge University Computer Lab. Vashek also worked on the Common Criteria and in ISO/IEC JTC1 SC27. He can be contacted at matyas@mfi.muni.cz.
Michael Felderer – Applying LLMs and AI Agents to Aerospace and Quantum Computing: Use Cases, Challenges, and Solutions
DLR Institute of Software Technology and Full Professor of Computer Science at the University of Cologne Homepage, Google Scholar
Abstract: Large Language Models (LLMs) and AI agents are transforming complex engineering and research workflows. In this talk, we showcase cutting-edge applications developed at the German Aerospace Center (DLR), where LLMs and AI agents are tackling current challenges in aerospace engineering and quantum computing research. The use cases covered include LLMs for space systems requirements engineering, secure agentic co-pilots for aircraft operations, and LLM-driven quantum algorithm design. For each case, we will essential domain context and dive into the novel AI techniques behind the scenes — including test-time scaling for efficient inference and symbolic validation layers that verify every agent action before execution against a model of physical constraints, mission axioms and trust boundaries.
Bio: Prof. Michael Felderer is Director of the Institute of Software Technology at the German Aerospace Center (DLR) and a full professor at the University of Cologne (Germany). Prior to this, he served as a professor at the University of Innsbruck (Austria), held a guest professorship at the Blekinge Institute of Technology (Sweden), and was CEO of an academic spin-off. His research aims to enhance the quality, resilience, and trustworthiness of software and AI systems — particularly in safety-critical domains such as aerospace, automotive, or critical infrastructures. His expertise spans software and system quality assurance, AI engineering, as well as software systems engineering for AI, quantum and digital twin technologies. Michael Felderer’s research is performed in close collaboration with research organizations and companies, and has led to over 200 publications and 15 best paper awards. He is recognized by the Journal of Systems and Software (JSS) as one of the twenty most active established Software Engineering researchers world-wide in the period 2013 to 2020.
Anastasija Nikiforova - Governing AI in Practice: Responsible Adoption, Human-AI Delegation, and Sustainable AI Lifecycle
University of Tartu Homepage, Google Scholar
Abstract:
Artificial Intelligence is rapidly moving from experimentation into real organizational and societal settings. Yet successful AI adoption depends on far more than technical performance alone. As a fundamentally sociotechnical phenomenon, AI reshapes decision-making, organizational routines, accountability structures, and resource dependencies. Its adoption therefore requires governance mechanisms that address human oversight, responsibility, delegation of authority, and long-term sustainability. This talk examines how organizations can—and should—adopt AI responsibly across the full AI lifecycle. It explores the practical challenges of sharing and delegating tasks between humans and AI systems, i.e., when AI should augment decisions, when human control must remain central, and how effective delegation boundaries can be designed in practice. The talk further introduces emerging perspectives on Sustainable and Green AI, highlighting the environmental and material dimensions of AI as a sociomaterial phenomenon—from model training and infrastructure demands to semiconductor supply chains, raw material extraction, and end-of-life hardware. Building on this, it presents the concept of a supply-chain-aware AI lifecycle. By combining technical, organizational, and societal perspectives, the session offers a practical framework for understanding AI governance beyond abstract principles and toward responsible real-world implementation.
Bio:
Anastasija Nikiforova is an Associate Professor of Applied AI and Information Systems at the at University of Tartu (Faculty of Science and Technology, Institute of Computer Science, Chair of Software Engineering) (Estonia), where she also leads the Information Systems research group. Her research focuses on data and AI governance and digital transformation, with particular emphasis on the responsible adoption of emerging technologies, particularly Artificial Intelligence (AI). She examines how (Gen)AI shapes organizational processes and data governance, including data quality, human–AI collaboration, and delegation mechanisms, as well as their ethical, societal, and environmental implications, such as responsible, sustainable, and Green AI within (public) data and digital ecosystems. By exploring the interplay between technology, society, and policy, her work contributes to the resilience, sustainability, and inclusiveness of complex socio-technical systems and informs AI governance and decision-making. In essence, she studies where AI ambitions collide with governance, legitimacy, and readiness, and how to design systems that remain robust under such pressures. Anastasija serves on the editorial boards of several leading journals, including International Journal of Information Management, Government Information Quarterly, IEEE Transactions on Technology and Society, and Data & Policy. She is a track chair for major conferences in information systems, AI, and public administration (e.g., IFIP EGOV-CEDEM-EPART, dg.o, AMCIS, HICSS) and contributes to workshops at ECAI, IJCAI, PRICAI, and CBI-EDOC. Her work involves close collaboration with the KNOW Center, the European Commission’s Joint Research Centre, the Digital Statecraft Academy, the European Open Science Cloud (“FAIR Metrics and Digital Objects” Task Force), and the Latvian Open Technology Association. She is actively engaged in international research and professional communities, including the International Federation for Information Processing Working Group 8.5 (IFIP WG 8.5 on ICT and Public Administration), the European Digital Skills Certificate (EDSC), the Association of Information Systems Women’s Network College, and Women in AI. She also serves as a mentor for the GovStack Women in GovTech Challenge 2026 and is a board member of the Digital Government Society.