Macrocyclic peptides are promising molecules for targeting intracellular protein–protein interactions and other challenging biological targets. However, their poor membrane permeability often limits their biological and therapeutic applications. Understanding the structural factors that govern passive membrane permeation is therefore essential for the rational design of cell-permeable macrocyclic peptides.
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\r\nIn this seminar, I will present our recent efforts to understand and predict the membrane permeability of macrocyclic peptides using large-scale experimental data, conformational analysis, and machine learning. We aim to clarify how conformational flexibility, including molecular chameleonicity, influences membrane permeability.
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\r\nI will also introduce our ongoing efforts toward DNA-encoded macrocyclic N-methyl peptide libraries as a future platform for discovering functional intracellular binders.
Thesis Director: Prof. J. Luterbacher,
\r\nChemistry and Chemical Engineering doctoral program
\r\nThesis Nr. 11539
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\r\nTo take part in the public defense, please contact directly the speaker
The programme aims to support innovative, interdisciplinary research that places natural daylight at the centre of the research question and research plan.
\r\nThe ambition is to:\r\n
Recent advances in foundation models are extending AI beyond perception and language understanding toward embodied systems that can perceive, reason, and act in the physical world. This transition is accelerating the development of vision-language-action (VLA) models and robot foundation models that aim to provide robots with more general, adaptive, and deployable intelligence.
\r\nThis talk presents recent progress toward self-working humanoid robots, covering key ideas in embodied AI such as multimodal understanding, long-horizon planning, action generation, and real-world deployment. It also introduces recent research from Seoul National University BI Lab and AI Institute on human-robot interaction, personalization, continual adaptation, and language-conditioned robot learning, together with the Habilis framework developed at Tommoro Robotics for deployable humanoid intelligence.
\r\nFinally, the talk discusses a future architecture for self-working humanoids that integrates perception, memory, reasoning, planning, and action into a unified learning system. The central theme is that while large language models enabled machines to communicate, vision-language-action models will enable machines to work autonomously in the real world.
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\r\nByoung-Tak Zhang's biography
\r\nPresent:
\r\nProfessor of Computer Science, Seoul National University,
\r\nDirector of the Humanoid AI Robot Center (HARC),
\r\nChairman of the K-Humanoid Alliance (Korean Government)
\r\n2019-2025:
\r\nFounding Director of SNU AI Institute (AIIS)
\r\n2007-2008:
\r\nVisiting Professor, Samsung Advanced Institute of Technology
\r\n2003-2004:
\r\nVisiting Professor, MIT CS&AI Lab (CSAIL)
\r\n1992-1995:
\r\nResearch Associate, German National Research Center for Computer Science (GMD)
\r\n1988-1992:
\r\nPhD in Computer Science, University of Bonn
\r\n1982-1988:
\r\nBS and MS in Computer Science, Seoul National University
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An abundance of systems has been studied as potential models of artificial life: from classical discrete cellular automata, to their randomized versions such as random Boolean networks, continuous systems including neural CAs or Lenia systems, or even simple programming languages. In this workshop, we would like to focus on the fundamental question of how to measure the complexity of such systems and detect emerging patterns within them. The conference will be held at EPFL Bernoulli Center.
\r\nMore information : https://www.dem.eco/
Are you finding it difficult to come up with a truly innovative idea for your next grant application? Do you ever feel stuck in an experiment, in familiar ways of thinking, even when you know there must be new angles to explore?
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\r\nScience progress moves between two complementary modes: Day Science, the rigorous testing of ideas, and Night Science, the creative process where those ideas first emerge. Indeed, what we call the scientific method tells us what to do once we have a hypothesis – but where do these hypotheses come from in the first place? François Jacob famously called this part the realm of ‘Night Science’.
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\r\nDrawing on the Night Science training framework developed by Profs Itai Yanai and Martin Lercher, this workshop will introduce thinking tools and exercises to help you foster exploratory thinking, interdisciplinarity and a general attitude of openness towards new ideas applied to your own research challenges. This course is provided by a certified Night Science trainer from the EPFL Research Office.
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\r\nThis interactive workshop is designed specifically for postdoctoral researchers who want to:\r\n