Date
Friday January 26, 2024 from 1:00 PM to 5:00 PMLocation
TU/e campus | P1 | Auditorium | Blauwe ZaalCo-organizer
ASMLPrice
FreeBuilding
AuditoriumObjective of the Summit:
The primary goal is to foster AI Research in the Semiconductor industry, creating an environment conducive to collaboration and innovation. We aim to ignite discussions on new and exciting topics in the realm of artificial intelligence applied to the semiconductor industry, driving forward the collective intelligence of our research communities.
This event is targeted at ASML and TU/e Researchers, Students, and Partners.
Agenda Highlights:
1. ASML and TU/e Research Roadmap: Explore the future of artificial intelligence in the semiconductor domain, as we delve into topics such as model discovery, next-generation algorithms, knowledge representation, and human-data interaction. This roadmap is a collaborative effort between ASML and TU/e researchers, charting the course for groundbreaking advancements in AI, and will be the basis for new consortiums with universities and other partners.
2. Project Showcase: Discover projects at the forefront of AI innovation. From groundbreaking research to real-world applications, these projects exemplify the synergies between ASML and TU/e. Immerse yourself in the possibilities as we present tangible outcomes and demonstrate the impact of collaborative efforts in the field of artificial intelligence.
3. Networking and Discussion: The Flagship is a forum for fostering connections and sparking meaningful conversations. Engage with like-minded researchers, exchange ideas, and explore new frontiers in AI. This summit aims to bring together the best minds from ASML, TU/e, and other institutions, to encourage collaborative discussions on emerging topics and pave the way for future breakthroughs. This Flagship will become a central, inclusive place for partners working with the ASML and TU/e.
Program
13.00 Welcome by Jacek Kustra (ASML) and Shane O'Seasnáin (TU/e)
13.05 Opening by Sjoerd Verduyn Lunel |Research Department Manager at ASML
13.20 Keynote by professor Hendrik Blockeel | Neuro-symbolic learning and reasoning
KU Leuven, Computer Science Department
13.50 Roadmap & elevator pitches
14.20 Break
14.35 Presentations
Jakub Tomczak | Generative AI in industrial applications
Associate Professor Generative AI Team, TU/e
Lina Ochoa Venegas
Assistant Professor Software Engineering & Technology Group, TU/e
Fons van der Sommen | Towards robust and reliable AI for high-tech applications
Associate Professor Video Coding and Architectures Group, TU/e
15.35 Panel Discussion with Jakub Tomczak, Line Ochoa Venegas, Fons van der Sommen,
Hendrik Blockeel and Sjoerd Verduyn Lunel
16.00 Networking drinks
Speaker
Hendrik Blockeel | Professor at KU Leuven
Title
Neuro-symbolic learning and reasoning
Biography
Hendrik Blockeel is a professor at the Department of Computer Science of KU Leuven.
His research interests cover a wide range of topics in machine learning and knowledge representation. His main expertise is in decision-tree learning, and in logic-based approaches to learning (inductive logic programming). He has also made contributions in the areas of statistical relational learning, probabilistic graphical models, multi-label classification, multi-instance learning, clustering, multi-target regression, query-based data mining, predictive clustering, versatile models, and other topics.
He is an action editor for several top journals in the field, program committee member of many conferences yearly, former program chair or organizer of multiple international conferences, workshops and summer schools.
He is a fellow of the European Association for AI, and publications chair for ECML/PKDD, Europe’s premier conference on machine learning and data mining.
Speaker
Jakub Tomczak | Associate Professor Generative AI Team, TU/e
Title
Generative AI in semi-conductor applications
Biography
Jakub M. Tomczak is an associate professor and the PI of the Generative AI group at the Eindhoven University of Technology (TU/e).
Before joining the TU/e, he was an assistant professor at Vrije Universiteit Amsterdam, a deep learning researcher (Engineer, Staff) in Qualcomm AI Research in Amsterdam, a Marie Sklodowska-Curie individual fellow in Prof. Max Welling's group at the University of Amsterdam, and an assistant professor and a postdoc at the Wroclaw University of Technology.
His main research interests include deep generative modeling, deep learning, and Bayesian inference, with applications to image/text processing, Life Sciences, and Molecular Sciences. He serves as an action editor of "Transactions of Machine Learning Research", and an area chair of major AI conferences (e.g., NeurIPS, ICML, AISTATS).
He will be a Program Chair of NeurIPS 2024. He is the author of the book entitled "Deep Generative Modeling", the first comprehensive book on Generative AI.
Speaker
Lina Ochoa Venegas | Assistant Professor at the Software Engineering and Technology (SET) group, TU/e
Title
Unveiling Software Architecture with Generative AI
Biography
Lina Ochoa is an Assistant Professor in the Software Engineering and Technology (SET) department at Eindhoven University of Technology (TU/e). She is passionate about studying the phenomena of software evolution, with a particular interest in software analysis and maintenance.
Currently, she is involved in a collaborative project between TU/e and ASML, focusing on applying generative AI to enhance the company's codebase.
Speaker
Fons van der Sommen | Associate Professor Video Coding and Architectures Group, TU/e
Title
Towards robust and reliable AI for high-tech applications
Biography
Fons van der Sommen is an associate professor at the department of Electrical Engineering of Eindhoven University of Technology, holding a BSc and MSc in electrical engineering and a PhD in computer vision. Heading the healthcare & high-tech cluster of the VCA research group,
Fons has worked on a variety of image processing and computer vision applications, ranging from image denoising to computer-aided diagnosis. Fons has a strong interest in signal processing and information theory, and strives to exploit methods from these fields to improve the robustness, efficiency and interpretability of modern-day AI architectures.
Eindhoven Artificial Intelligence Systems Institute
EAISI brings together all AI activities of the TU/e. Top researchers from various departments and research groups work together to create new and exciting AI applications with a direct impact on the real world. All this in close collaboration with our students and representatives from industry.