Living systems consume energy and information to survive, grow, and reproduce. These vital dynamics occur across many scales of space and time, but the most fundamental is molecular: atoms and the bonds between them. The genetic code is written in atoms. It in turn specifies the atomic structures of proteins, biology’s energy and information processing units, which execute their functions in molecular space. Therefore, in a deep sense, atomic motion is the foundation from which life emerges. I seek to understand that motion.
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\r\nOne direct and powerful route is to film macromolecules with chemical resolution in both space (Å) and time (fs). I will describe a technology that uniquely enables us to achieve both simultaneously – the X-ray free-electron laser – and show how my team has used XFELs to watch two proteins at work.
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\r\nFirst, I will present our experiments on photolyase, an enzyme that harnesses light to repair life-threatening DNA damage. We found photolyase achieves very high repair quantum efficiency through an unexpected mechanism: by locking its photoexcited chromophore into a bent configuration. Further, photolyase achieves product/substrate specificity geometrically, using a rigid active site that matches substrate but not product. Second, I will share preliminary results on cryptochrome 4, a descendant of photolyase that has been proposed to act as an avian magnetosensor. Do birds navigate using a quantum magnetic compass? Our experimental program is investigating this provocative hypothesis.
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The talk is jointly organized by the EPFL AI Center and the EPFL Signal Processing Laboratory (LTS5) as part of the AI Fundamentals seminar series.
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\r\nHost: Prof. Jean-Philippe Thiran
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\r\nTitle
\r\nDeep Learning Solution of the Eigenvalue Problem for Differential Operators
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\r\nAbstract
\r\nSolving the eigenvalue problem for differential operators is a common problem in many scientific fields. We introduce a novel Neural Network (NN) -based solver for the eigenvalue problem of differential self-adjoint operators, where the eigenpairs are learned in an unsupervised end-to-end fashion. We propose several training procedures for solving increasingly challenging tasks towards the general eigenvalue problem. The proposed solver is capable of finding the M smallest eigenpairs for a general linear differential operator. Our proposed method simultaneously solves several eigenpairs and can be easily used on free-form domains. We exemplify it on L-shape and circular cut domains. A significant contribution of this
\r\nwork is an analysis of the numerical error of this method. In particular an upper bound for the (unknown) solution error is given in terms of the (measured) truncation error of the PDE and the network structure.
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\r\nBio
\r\nNir Sochen, finished his B.Sc studies in Physics 1986 and his M.Sc. studies in theoretical physics 1988 both in the University of Tel-Aviv. Received his PhD in Theoretical physics 1992 from the Universit\\’e de Paris-Sud while conducting his research in the Service de Physique Th\\’eorique at the Centre d’Etude Nucleaire at Saclay, France. He continued with a one year research in the Ecole Normale Superieure in Paris on the Haute Etude Scientifique fellowship, and a three years NSF fellowship in the physics department of the University of California at Berkeley. It is in Berkeley that his interests shifted from quantum field theories and integrable models, related to high-energy physics and string theory, to computer vision and image processing. He spent one year in the physics department at the University of Tel-Aviv and two years in the Faculty of Electrical Engineering in the Technion-Israel Institute of Technology. Currently he is a senior lecturer in the Department of Applied Mathematics, University of Tel-Aviv. He is also a member of the Ollendorf center in the Technion.
\r\nHis main research interests are the applications of differential geometry and statistical physics in image processing and computational vision.
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Thesis Director: Prof. E. Charbon,
\r\nMicrosystems and Microelectronics doctoral program
\r\nThesis Nr. 11261
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\r\nTo take part in the public defense, please contact directly the speaker
To promote research and education in cyber-defence, the EPFL and the Cyber-Defence (CYD) Campus have jointly launched the “CYD Fellowships – A Talent Program for Cyber-Defence Research.”
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\r\nThe 14th call for applications is now open with a rolling call for Master Thesis Fellowship and Proof of Concept Fellowship applications, and with a deadline of 19 August 2026 (17:00 CEST) for Doctoral and Distinguished Postdoctoral Fellowship applications.
\r\nEPFL and the CYD Campus organise an online applicant workshop dedicated to the CYD Fellowships 14th call for applications.
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\r\nThe workshop will target researchers (master, doctoral, postdoctoral level) and entrepreneurs who are willing to engage with cross-cutting issues in cyber-defence, with a particular emphasis on:\r\n
To promote research and education in cyber-defence, EPFL, the Swiss Federal Institute of Technology in Lausanne, and the Cyber-Defence (CYD) Campus have jointly launched the “CYD Fellowships – A Talent Program for Cyber-Defence Research”. There are two calls per year and the 14th call is now open.
\r\nCYD Fellowships are designed to promote new solutions to major challenges in the fields of security and data science by bringing together basic and applied research. They are open to researchers at master, doctoral, or postdoctoral level who are willing to engage with innovative issues in cyber-defence, with a particular emphasis on:\r\n
This two-week programme will be held from 06 to 17 July 2026 at the Bernoulli Center.
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\r\nThe first week features a series of lecture courses primarily aimed at early-career researchers. The second week is a research conference.
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\r\nA central theme of the meeting is Functorial Quantum Field Theories beyond TQFTs and the Segal-Stolz–Teichner programme.
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\r\nThe event will highlight recent developments in extended functorial field theories; analytic structures in quantum field theory, including higher categorical analogues of von Neumann algebras and Hilbert spaces; categorified geometric structures, such as higher vector bundles and stringor bundles; and, supersymmetry and its role in generalized cohomology theories.
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\r\nThe workshop and conference hope to provide an opportunity to advance the interface between homotopy theory, operator algebras, and quantum field theory.