10:00 Start symposium
16:30 Closing drink
Autonomy and artificial intelligence are topics that we encounter more and more often today. We see very little of it within our electrical engineering study, but you can hear it passing by. In various master's courses, you sometimes hear that AI can offer a solution. However, it does not happen yet, because few students are multidisciplinary and have both an electrical engineering and computer science background. It is not without reason that there are reports that AI-related courses should be added to the curriculum.
Artificial intelligence and machine learning are the techniques of this century. It is closer to the ability of humans. Maybe we should even ask ourselves if there ever comes a point when technology passes us by. It arouses fears of the unknown. What is it? What does it do? Who is responsible?
But if we put all buzzwords aside. AI is something many have heard of, but few really know what it does, what it can do, or where the future can take us. The interface between curiosity, the incredible and perhaps fear, that is the place for a symposium.
Our journey in deepening autonomy and AI started with the self-driving car. Probably also the first thoughts on this subject for many. But if you delve deeper into the world of autonomy and AI, a world opens up for you. We were amazed at how widely AI can be applied. Just as an electrical engineer is trained broadly, we also want to keep the symposium broad, but still concrete enough.
Implementations of artificial intelligence can be seen in different sectors such as healthcare, transportation, logistics and retail. All these sectors can use AI. It can take over or assist tasks. Speed up, personalize or make processes more user-friendly.
Jens Kober is an associate professor at the TU Delft, Netherlands. He worked as a postdoctoral scholar jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. He graduated in 2012 with a PhD Degree in Engineering from TU Darmstadt and the MPI for Intelligent Systems. For his research he received the annually awarded Georges Giralt PhD Award for the best PhD thesis in robotics in Europe, the 2018 IEEE RAS Early Academic Career Award, and has received an ERC Starting grant. His research interests include motor skill learning, (deep) reinforcement learning, imitation learning, interactive learning, and machine learning for control.
Boudewijn P.F. Lelieveldt is professor of Biomedical Imaging at the Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands, where he is heading the Division of Image Processing (LKEB). He is also appointed as Medical Delta professor at the at Delft University of Technology in the context of the Medical Delta consortium. His main research interest is data analytics and machine learning for clinical imaging spatially resolved –omics data, with applications in clinical imaging and biology. Main challenge in his work is to make the translation between what is required in clinical practice and life-sciences on the one hand, and the recent technological developments on the other hand. How do you teach a computer
to see with the prior experience of a human, and with the accuracy of a machine?
Nicola Pezzotti is a Senior Scientist in Artificial Intelligence at Philips Research, Eindhoven, the Netherlands and assistant professor at Eindhoven University of Technology. His research interests include machine learning, medical imaging, visual analytics, explainable AI, optimization techniques and software engineering. He received his BSc and MSc degrees in Computer Science and Engineering from the University of Brescia, Italy, in 2009 and 2011. He received his PhD cum Laude from Delft University of Technology, the Netherlands, in 2018. Besides his experience in the startup world, he was a visiting scientist to INRIA Saclay, Paris, in 2017 and Google AI, Zurich, in 2018. He is recipient of several awards, including the IEEE VGTC Best Dissertation Award, TU Delft Excellence in Research and the Dirk Bartz Prize for Visual Computing in Medicine.
Dariu M. Gavrila received the PhD degree in computer science from the Univ. of Maryland at College Park, USA, in 1996. He was a Visiting Researcher at the MIT Media Laboratory in 1996. From 1997 till 2016 he has been with Daimler R&D in Ulm, Germany, where he eventually became a Distinguished Scientist. During 2004-2018, he also has been a professor in Intelligent Perception Systems at the Univ. of Amsterdam (part-time). Since 2016 he heads the Intelligent Vehicles group at the TU Delft as a professor (fulltime). Read more...
Nora Baka is an R&D engineer, team lead, and people manager at Tomtom. She works with her team on using AI for automating map creation for autonomous cars. Before that she had various post-doc positions and a PhD in medical image processing. She got her PhD from the Erasmus University, and her masters degree from Budapest University of Technology and Economics. She came to the Netherlands with an Erasmus scholarship during her masters degree in electrical engineering to attend a semester at TUDelft. That’s why she is very honored to be invited to the ETV symposium to give a talk there. The first part of her talk will be about maps, mapping, and challenges when going world-wide. Why do we need AI? What are the differences in the world of industry vs academia from the AI perspective? In the second part of the talk she is going to highlight some recent research from Tomtom.