ADIA Lab Summer School: Responsible AI in the Generative and Agentic AI Era,
in collaboration with the University of Granada, Spain
Speakers
Francisco (Paco) Herrera
Francisco Herrera received his M.Sc. in Mathematics in 1988 and Ph.D. in Mathematics in 1991, both from the University of Granada, Spain. He is a Professor in the Department of Computer Science and Artificial Intelligence at the University of Granada and Director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI). He's an academician in the Royal Academy of Engineering (Spain).
has been the supervisor over 60 Ph.D. students. He has published more than 600 journal papers, receiving more than 170000 citations (Scholar Google, H-index 190). He has been nominated as a Highly Cited Researcher (in the fields of Computer Science and Engineering, respectively, 2014 to present, Clarivate Analytics). He acts as editorial member of a dozen of journals.
His current research interests include among others, computational intelligence, information fusion and decision making, trustworthy artificial intelligence, general purpose artificial intelligence and data science.
Bastian Bergmann
Bastian Bergmann is the Executive Director of the ETH Risk Center. He is the Co-Founder of the ETH FinsureTech Hub which started as an initiative inside the ETH Risk Center and is now with the Department of Mathematics at ETH. His focus is on education and outreach initiatives on Master and Professional Education level.
He has a background in Finance (PhD) as well as a Master in Philosophy. In addition, he has more than five years’ experience in the finance industry.
Josef Teichmann
In recent work Josef Teichmann and his co-authors develop machine learning tools for the financial industry. Deep hedging, for instance, is a project conducted jointly with investment bankers, where generic hedging tasks are solved by cutting edge machine learning technology in a fully realistic market environment, i.e. in the presence of market frictions and trading constraints. Further projects include deep calibration, deep simulation, and deep prediction. Theoretical foundations from approximation theory and stochastic analysis accompany successful concrete implementations to make such approaches eligible for industry applications.
Johannes Schneider
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, 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
Torsten Hoefler
Torsten Hoefler is a Professor of Computer Science at ETH Zurich, a member of Academia Europaea, and a Fellow of the ACM, IEEE, and ELLIS. He received the 2024 ACM Prize in Computing, one of the highest honors in the field. Following a Performance as a Science vision, he combines mathematical models of architectures and applications to design optimized computing systems. Before joining ETH Zurich, he led the performance modeling and simulation efforts for the first sustained Petascale supercomputer, Blue Waters, at the University of Illinois at Urbana-Champaign. He is also a key contributor to the Message Passing Interface (MPI) standard where he chaired the "Collective Operations and Topologies" working group. Torsten won best paper awards at his field's top conference ACM/IEEE Supercomputing in 2010, 2013, 2014, 2019, 2022, 2023, 2024, and at other international conferences. He has published numerous peer-reviewed scientific articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. For his work, Torsten received the IEEE CS Sidney Fernbach Memorial Award in 2022, the ACM Gordon Bell Prize in 2019, the ACM Gordon Bell Prize in Climate Modeling in 2025 Germany's Max Planck-Humboldt Medal, the ISC Jack Dongarra award, the IEEE TCSC Award of Excellence (MCR), ETH Zurich's Latsis Prize, the SIAM SIAG/Supercomputing Junior Scientist Prize, the IEEE TCSC Young Achievers in Scalable Computing Award, and the BenchCouncil Rising Star Award. Following his Ph.D., he received the 2014 Young Alumni Award and the 2022 Distinguished Alumni Award of his alma mater, Indiana University. Torsten was elected to the first steering committee of ACM's SIGHPC in 2013 and he was re-elected for every term since then. He was the first European to receive many of those honors; he also received both an ERC Starting and Consolidator grant. His research interests revolve around the central topic of performance-centric system design and include scalable networks, parallel programming techniques, and performance modeling for large-scale simulations and artificial intelligence systems. Additional information about Torsten can be found on his homepage at htor.inf.ethz.ch.
Julia Hernández
Julia Hernández is a Generative AI Specialist at Google Cloud, supporting Enterprise and Digital Native accounts across Spain and Portugal. Her work centers on architecting and deploying GenAI applications, agentic workflows, and RAG pipelines for startups and large organizations. In her role, she regularly partners with engineering teams to build scalable LLM architectures utilizing Vertex AI, Gemini APIs, and the Google Agent Development Kit (ADK). A former professional football player, Julia brings a disciplined and team-oriented approach to technical problem-solving and engineering leadership
Carme Artigas
Carme Artigas is a highly regarded leader in AI, big data, cybersecurity, and technology innovation, with over 30 years of experience. She co-founded Synergic Partners, a pioneering European Big Data company, which was acquired by the Telefonica Group in 2015. From 2020 to 2023, she served as Spain’s first Secretary of State for Digitalization and AI, where she played a crucial role in advancing the EU AI Act during the Spanish Presidency of the EU. She is now Co-Chair of the United Nations AI Advisory Body and a Senior Fellow at Harvard’s Belfer Center. Throughout her career, she has held senior positions at Procter & Gamble, the City of Barcelona, and Ericsson, where she led their European venture capital firm. Artigas holds a Master of Science in Chemical Engineering and has completed postgraduate programs at Berkeley and the Max Planck Institute. She has been named an ambassador for Stanford’s "Women in Data Science (WIDS)" initiative and is widely recognized as an international expert in AI regulation and governance.
Aaron Conrardy
Aaron Conrardy is a PhD student at the Luxembourg Institute for Science and Technology with a background in computer science. His research focuses on leveraging software engineering techniques to democratize the development of adaptive user interfaces by integrating AI technologies into everyday applications. Specifically, he investigates the creation of inclusive user interfaces that adapt to factors such as accessibility needs, language proficiency, emotion, and other user characteristics.
Arijit Patra
Dr Arijit Patra is a Senior Principal Scientist at UCB UK and a Honorary Senior Lecturer (Associate Professor) at the University of Glasgow. He holds a PhD in machine learning for healthcare imaging from the University of Oxford, where he was a Rhodes Scholar (India & Exeter, 2016). Prior to that, he completed a dual degree in Mechanical Engineering from the Indian Institute of Technology (IIT) at Kharagpur, India. He has also been associated with AstraZeneca, Shell, Microsoft Research and CSIR-South Africa at various points in his career and has been actively involved in the AI4SG (AI for Social Good) community, and was an invited expert to the UK-India Track 1.5 Dialogues on technology security and diplomacy. He has authored several publications around machine learning and medical imaging and is a reviewer for multiple peer reviewed venues such as NeurIPS, ICML, MICCAI and several journals, and has spoken at more than 50 conferences, panels, trade and multilateral events, and allied venues. Arijit has been appointed as a Rising Leaders fellow of the Aspen Institute UK, and as an International Strategy Forum fellow in 2024, and won the Society of Toxicology RSESS Award in 2026.
Natalia Ana Díaz Rodríguez
Natalia Díaz Rodríguez has a double PhD from University of Granada (Spain) and Åbo Akademi University (Finland) and is associate professor at the DaSCI Andalusian Research Institute in data science and computational intelligence (DaSCI.es) at the Dept. of Computer Science and AI of the University of Granada (Spain) since 2024. Earlier, she was Marie Curie postdoctoral researcher; and Prof. of at the Autonomous Systems and Robotics Lab at ENSTA, Institut Polytechnique Paris, INRIA Flowers team on developmental robotics, and worked on open-ended learning and continual/lifelong learning for applications in computer vision and robotics. She has worked in industry, academia and gubernamental institutions in Silicon Valley, CERN, Philips Research, University of California Santa Cruz and NASA. She cofounded the non-profit ContinualAI.org and worked doing Responsible AI Governance industry assessments and writing the guidelines for the regulatory sandbox pilot of the AI Act for the Spanish Secretary of Estate. She received multiple prizes (among others, from the Royal Academy of Engineering to Young Research Scientists) and is listed in the «Ranking of the World’s Top 2% Scientists» from Stanford University (California) that identifies the most relevant scientists in the world according to the impact of their publications' citations.
Oier Mentxaka
Oier Mentxaka is a PhD researcher at the University of Granada (UGR), specializing in AI governance and the auditability of high‑risk AI systems. His work focuses on developing practical auditing methodologies aligned with emerging regulations and standards, including the EU AI Act and ISO/IEC 42001. He examines how requirements such as accountability, transparency, and risk management can be translated into concrete audit criteria, evidence, and processes applicable to real‑world deployments, particularly in high‑impact public‑sector contexts.