retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=50&ordering=-event__url_place_and_room
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "id": 71748,
            "title": "Reasoning Under Uncertainty: Trustworthy LLMs for High-Stakes Medicine",
            "slug": "reasoning-under-uncertainty-trustworthy-llms-for-h",
            "event_url": "https://memento.epfl.ch/event/reasoning-under-uncertainty-trustworthy-llms-for-h",
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            "start_date": "2026-06-26",
            "end_date": "2026-06-26",
            "start_time": "09:30:00",
            "end_time": "11:30:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Robert West<br>\r\nThesis advisor: Prof. Mary-Anne Hartley<br>\r\nCo-examiner: Prof. Martin Jaggi<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nCurrent machine learning systems are very good at tasks reducible to statistical pattern recognition but falter on problems requiring deliberate, structured inference. Clinical reasoning exemplifies the latter: physicians generate hypotheses abductively, revise beliefs probabilistically as evidence accumulates, and choose among actions whose costs are deeply asymmetric. The harm of a missed diagnosis is not the harm of an unnecessary test. Large language models, increasingly deployed for clinical decision support, inherit this limitation. They conflate knowledge with inference: the same parameters that store medical facts are asked to reason over them, which leaves no explicit mechanism to quantify uncertainty, to abstain when evidence is insufficient, or to weight outcomes by their true clinical costs. This work argues that progress toward trustworthy medical AI requires separating the representation of knowledge from the machinery of inference, and grounding the latter in formal frameworks drawn from statistical decision theory. We investigate how these frameworks can be embedded into LLM reasoning pipelines and imposed as external scaffolding around them, maintaining competing hypotheses, guiding evidence gathering, and selecting actions that reflect the asymmetric cost structure of clinical practice. The goal is a class of systems capable of reasoning over their uncertainty, systems that know when they do not know.<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
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            "speaker": "Yusuf Kesmen",
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            "id": 70771,
            "title": "Training \"Reshaping Information Research with AI\"",
            "slug": "training-reshaping-information-research-with-ai-9",
            "event_url": "https://memento.epfl.ch/event/training-reshaping-information-research-with-ai-9",
            "visual_url": "https://memento.epfl.ch/image/32182/200x112.jpg",
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            "start_date": "2026-06-02",
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            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<strong>In the last few years, many AI-powered tools promise to change forever the way we look for information. During this workshop, which will be held in presence only, we will explore some of them, focusing on the so-called \"research assistants\" in order to understand how they work and how we can exploit them to make our research better.</strong><br>\r\n<br>\r\nAfter attending this workshop, you will be able to:\r\n<ul>\r\n\t<li>Identify the main challenges brought by AI to the information retrieval.</li>\r\n\t<li>Compare 4 AI-powered research assistants.</li>\r\n\t<li>Recognize the main difference with the traditional information retrieval strategy.</li>\r\n</ul>\r\n<a href=\"https://bookwhen.com/epfl_library/e/ev-sdtus-20260602100000\">Registration</a><br>\r\n<br>\r\nMore information about <a href=\"https://www.epfl.ch/campus/library/training/\">EPFL Library Teaching offer</a>",
            "image_description": "",
            "creation_date": "2026-01-06T09:25:25",
            "last_modification_date": "2026-01-06T09:27:05",
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            "id": 71413,
            "title": "Summer School: Capitalizing on Uncertainty — Structures, Processes, Mindsets",
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            "lang": "en",
            "start_date": "2026-08-31",
            "end_date": "2026-09-05",
            "start_time": "09:00:00",
            "end_time": "18:00:00",
            "description": "<p>A summer school taking place this September will bring together EPFL and ETH Zurich PhD students to explore how uncertainty can become a productive resource in design and fabrication through a hands-on construction robotics challenge.<br>\r\n<br>\r\nThe program combines lectures in architecture, robotics, and work psychology with the full-scale construction of a timber structure from irregular timber stock, using an ABB industrial robot in a human-robot fabrication workflow.<br>\r\n<br>\r\nNo previous experience in construction robotics is required, only curiosity.<br>\r\n<br>\r\nMore details, including the program, dates, and registration information, are available on the website: <a data-auth=\"NotApplicable\" data-linkindex=\"0\" href=\"https://cap-uncertainty.epfl.ch/\" id=\"OWAa905ab2b-2f22-4a32-d755-d21d9266332e\" rel=\"noopener noreferrer\" target=\"_blank\" title=\"https://cap-uncertainty.epfl.ch/\">https://cap-uncertainty.epfl.ch/</a><br>\r\n<br>\r\nFor questions, please contact: [email protected]</p>",
            "image_description": "",
            "creation_date": "2026-03-20T11:43:14",
            "last_modification_date": "2026-03-20T12:14:19",
            "link_label": "website",
            "link_url": "https://cap-uncertainty.epfl.ch/",
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        {
            "id": 69172,
            "title": "Dynamic Decisions and Temporal Frictions in On-Demand Mobility",
            "slug": "dynamic-decisions-and-temporal-frictions-in-on-d-2",
            "event_url": "https://memento.epfl.ch/event/dynamic-decisions-and-temporal-frictions-in-on-d-2",
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            "start_date": "2026-06-22",
            "end_date": "2026-06-22",
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            "description": "<strong>ABSTRACT</strong><br>\r\nApp-based, on-demand transport systems have transformed urban mobility by enabling real-time coordination between vehicles and users. Yet behind this flexibility lies a fundamental tension: operational decisions that appear beneficial in the present can deteriorate the future state of the system. This talk explores these temporal frictions in assigned on-demand systems—where passengers and vehicles are matched before meeting—and how they shape the performance and reliability of shared mobility services.<br>\r\nFirst, we show how assignment decisions evolve through what we term the Increasing Gap Dynamics, a negative feedback cycle through which vehicles progressively concentrate in space, reducing system efficiency over time. We then examine how a tension between efficiency and reliability emerges: while highly dynamic operations can improve short-term efficiency and flexibility, they may also increase unreliability by exposing passengers to future, uncertain requests. We discuss how this tension manifests both in routing decisions and in the selection of pickup and dropoff locations, and show how carefully designed anticipatory techniques can help reconcile these competing objectives.<br>\r\n<br>\r\n <br>\r\n<strong>SHORT BIO</strong><br>\r\nDr Andrés Fielbaum is a Senior Lecturer in Transport Engineering at the University of Sydney and a DECRA Fellow of the Australian Research Council. His work lies at the intersection of transport systems and applied mathematics, with a focus on public transport, on-demand mobility, and developing analytical models to inform system design and operations. He completed his PhD in Systems Engineering at Universidad de Chile in 2019 and held a postdoctoral appointment at TU Delft between 2019-2023.<br>\r\n<br>\r\nDr Fielbaum has authored over 35 peer-reviewed journal articles in leading outlets and serves as an Associate Editor for Transportation Research Part B: Methodological,  and the Journal of Intelligent Transportation Systems.<br>\r\n<br>\r\n ",
            "image_description": "",
            "creation_date": "2025-05-15T16:13:27",
            "last_modification_date": "2026-05-13T08:28:12",
            "link_label": "",
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            "speaker": "Dr Andrés Fielbaum",
            "organizer": "HOMES - Prof. Kenan Zhang",
            "contact": "Prof. Kenan Zhang<br>\r\nAdministrative: Mélanie Thuillard",
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            "id": 71783,
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            "start_date": "2026-06-01",
            "end_date": "2026-06-01",
            "start_time": "15:00:00",
            "end_time": "16:00:00",
            "description": "",
            "image_description": "",
            "creation_date": "2026-05-04T09:56:23",
            "last_modification_date": "2026-05-05T13:13:57",
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            "speaker": "Hong Wang ( IHES &amp; NYU)",
            "organizer": "Chair of Stochastic Analysis (STOAN)",
            "contact": "[email protected]",
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        {
            "id": 71918,
            "title": "Brain-wide representations of olfactory behavior in C. elegans",
            "slug": "brain-wide-representations-of-olfactory-behavior-i",
            "event_url": "https://memento.epfl.ch/event/brain-wide-representations-of-olfactory-behavior-i",
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            "start_date": "2026-06-08",
            "end_date": "2026-06-08",
            "start_time": "14:30:00",
            "end_time": "15:30:00",
            "description": "<p>Abstract:<br>\r\nOlfactory navigation emerges from dynamic interactions among sensory input, brain activity, and the animal’s own movements. In C. elegans, a compact nervous system enables brain-wide imaging in behaving animals exposed to controlled olfactory environments, and undulatory locomotion reduces navigation to transitions among forward runs, reversals, and turns. Here, we used brain-wide tracking microscopy to record neural activity in freely crawling worms navigating spatial odor gradients or isotropic environments, and in immobilized worms responding to temporal odor pulses. Across conditions, we identified strongly correlated brain-wide activity patterns spanning olfactory sensory neurons, interneurons, and premotor neurons. Motor-state transitions and brain-wide correlation structure differed between freely moving and immobilized animals, demonstrating that olfactory sensory representations depend jointly on sensory input, motor activity, and behavioral context. Together, these findings show that brain-wide representations of olfactory behavior are extensively reconfigured by sensory input, self-motion, and behavioral context.<br>\r\n </p>",
            "image_description": "",
            "creation_date": "2026-05-21T13:36:09",
            "last_modification_date": "2026-05-21T13:36:09",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
            "cancel_reason": "",
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            "spoken_languages": [
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            ],
            "speaker": "Prof. Aravinthan Samuel &lt;[email protected]&gt;\r\n\r\nDepartment of Physics &amp; Center for Brain Science, Harvard University",
            "organizer": "Prof. Sahand Jamal Rahi &lt;[email protected]&gt;\r\n\r\nJohanni Brea &lt;[email protected]&gt;",
            "contact": "Prof. Sahand Jamal Rahi &lt;[email protected]&gt;\r\n\r\nJohanni Brea &lt;[email protected]&gt;",
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        {
            "id": 71916,
            "title": "AI Center Seminar - AI for Health series - Prof. Li CHEN",
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            "start_time": "10:30:00",
            "end_time": "11:30:00",
            "description": "<p>The talk is jointly organized by the <a href=\"https://ai.epfl.ch/\">EPFL AI Center</a> and the EPFL <a href=\"https://www.epfl.ch/labs/gr-pu/\">Human-Computer Interaction Group</a> as part of the AI for Health seminar series.<br>\r\n<br>\r\n<strong><em>Hosting professor: Prof. Pearl Pu (GR-PU)</em></strong><br>\r\n<br>\r\n<strong>Title</strong><br>\r\nBeyond Recommendations: Designing Conversational Music Agents for Self-Awareness and Psychological Well-being<br>\r\n<br>\r\n<strong>Abstract</strong><br>\r\nAs the demand for scalable mental health tools grows, the potential of Large Language Models (LLMs) lies in their ability to move beyond generic retrieval toward deeply adaptive, trustworthy support. This talk explores how music-driven conversational systems can bridge the gap between algorithmic recommendation and psychological intervention. The journey begins with establishing a foundation of trust through user-centric exploration. Using conversational music recommenders as a case study, I will discuss how critiquing strategies—such as progressive and cascading suggestions—shape user perceptions of helpfulness and serendipity. However, because trust is personal, I demonstrate how individual traits, including personality and trust propensity, dictate whether a user thrives under system-led or user-led initiatives.<br>\r\nBuilding on this rapport, the talk examines how these interfaces transition from suggesting songs to fostering psychological well-being. I will illustrate how music acts as a catalyst for self-awareness, using agents to guide users through emotional resonance and self-reflection. Furthermore, I will share findings on the role of generative AI in music-based reminiscence for older adults, where adaptive dialogue helps overcome cognitive barriers to memory recall. Collectively, these studies provide a roadmap for designing AI that moves beyond the playlist, transforming music-based chatbots into sustained partners for emotional and psychological health.<br>\r\n<br>\r\n<strong>Bio</strong><br>\r\nProfessor Li Chen is currently a Full Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU). She obtained her PhD degree in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and her Bachelor's and Master's degrees from Peking University, China. Her recent research focus has mainly been on conversational AI, explainable AI, recommender systems, and human-computer interaction. She has authored and co-authored over 160 publications, with over 13,000 citations (H-index 53). Her co-authored papers have received several awards, such as the RecSys’24 Best Student Paper Award, CHI’22 Honourable Mention Award, UMAP’20 Best Student Paper Award, UMUAI 2018 Best Paper Award, and UMAP’15 Best Student Paper Award. She received the President’s Award for Outstanding Performance in Teaching (Individual) 2024/25 and the President’s Award for Outstanding Performance in Research Supervision 2022/23. She has been included in the list of the world’s top 2% most-cited scientists by Stanford University since 2021, and the list of the Best Computer Science Scientists 2025/2026 by Research.com.<br>\r\n<br>\r\nShe is now an ACM senior member, founding co-editor-in-chief of ACM Transactions on Recommender Systems (TORS), steering committee member of ACM Conference on Recommender Systems (RecSys), associate editor of International Journal of Human-Computer Studies (IJHCS), editorial board member of User Modeling and User-Adapted Interaction Journal (UMUAI), and associate editor of ACM Transactions on Interactive Intelligent Systems (TiiS). She has also served as program co-chair of IUI’26, general co-chair of ACM RecSys’23, program co-chair of ACM RecSys’20, and program co-chair of ACM UMAP’18.<br>\r\n </p>",
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        {
            "id": 71879,
            "title": "Mathematics Colloquium",
            "slug": "mathematics-colloquium-15",
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            "lang": "en",
            "start_date": "2026-06-09",
            "end_date": "2026-06-09",
            "start_time": "16:15:00",
            "end_time": "17:15:00",
            "description": "<strong>Title : </strong>On indefinite ternary quadratic forms<br>\r\n<br>\r\n<strong>Abstract : </strong><br>\r\nWe describe the solution to two problems concerning indefinite integral ternary quadratic forms.<br>\r\nThe first about anisotropic forms was popularized by Margulis following his solution of the Oppenheim Conjecture.<br>\r\nThe second about the density of isotropic forms was raised by Serre.<br>\r\nJoint work with A.Gamburd, A.Ghosh and J.Whang.<br>\r\n<br>\r\n<strong>Please register on the following form : </strong>https://forms.gle/w8PbDFZtRSs5V47Y8<br>\r\n ",
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            "creation_date": "2026-05-13T13:52:46",
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            "speaker": "Prof. Peter Sarnak (Institute of Advanced Study and Princeton University)",
            "organizer": "Institute of Mathematics",
            "contact": "Prof. Philippe Michel",
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        {
            "id": 71885,
            "title": "Eveline Mayner's Public Defense",
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            "event_url": "https://memento.epfl.ch/event/eveline-mayner-s-public-defense",
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            "start_date": "2026-05-29",
            "end_date": "2026-05-29",
            "start_time": "04:00:00",
            "end_time": "22:00:00",
            "description": "<p>Two-dimensional (2D) materials have emerged as a versatile platform at the intersection of fundamental physics and applied science. Their atomically thin nature gives rise to distinctive electronic and optical properties, while simultaneously enabling them to function as highly sensitive, readily integrable probes of their local environment. Advanced optical techniques, such as super-resolution microscopy, have opened new opportunities to interrogate these materials at the nanoscale, providing optical access to individual defect behaviors, exciton diffusion and recombination dynamics, and charge transport pathways. Such approaches not only deepen our understanding of intrinsic material behavior but also position 2D systems as powerful sensors capable of resolving local dielectric variations, electric and magnetic fields, and other environmental perturbations.<br>\r\nCentral to this work is hexagonal boron nitride (hBN), a transparent, wide bandgap semiconductor that serves as a host for optically active defects. These defects function as reaction centers, single-photon emitters, and spatially resolved nanoscale sensors that can be readily integrated into electronic and photonic architectures. Owing to its optical transparency, chemical stability, and compatibility with diverse material platforms, hBN provides an exceptional foundation for optical sensing. Building upon this foundation, we explore material properties and present new methods for spatially resolved in situ optical imaging with hBN to advance dynamic, wide-field optical sensing.<br>\r\nWe investigate a previously reported class of emitters that arise from interactions between native hBN and organic solvents. These emitters are believed to originate from defect sites that bind transiently to solvent molecules. To study their behavior, we develop a platform for imaging the dynamics of these transient emitters while varying the electrochemical potential and applying electric fields with controlled orientations. By tracking the spectra of individual emitters, we enable multiplexed measurements that allow spatially resolved electrochemical imaging. Through systematic analysis, we rule out modulation mechanisms based on direct electric field effects or charge transfer. Instead, we identify a mechanism driven by changes in H⁺ concentration, which is modulated during the oxidation of trace water present in the solvent. This finding opens the possibility of using this platform for sensitive detection of H⁺ and trace water in methanol fuel cells, where such species critically influence operational efficiency.<br>\r\nIn the final part of the thesis, we focus on a well-characterized spin defect in hBN, the negatively charged boron vacancy, and explore strategies to enhance its photoluminescence (PL) through heterostructure engineering that facilitates energy and exciton transfer. We demonstrate the coupled structure’s improved utility in optical magnetometry compared to the defect by itself and discuss how improvements in PL could advance the development of wide-field optically detected magnetic resonance (ODMR) imaging using this spin defect. Using a defect in hBN would leverage 2D materials’ exceptional sensing capabilities and planar integrability.<br>\r\nOverall, this thesis aims to highlight the strengths of integrating 2D materials with optical sensing and to develop transferable techniques for introducing controlled stimuli, such as electrochemical potentials, electric fields, or electromagnetic waves, with high fidelity and minimal artifacts. These advances not only demonstrate the potential of hBN as a versatile sensing platform but also establish methodologies applicable to a wide range of low-dimensional material systems.<br>\r\n<br>\r\nFor zoom:<br>\r\n Meeting ID: 611 3428 2068 Passcode: 952027</p>",
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            "keywords": "Public Defense",
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            "id": 71670,
            "title": "EPFL Racing Team - Event",
            "slug": "epfl-racing-team-event",
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            "lang": "en",
            "start_date": "2026-05-27",
            "end_date": "2026-05-27",
            "start_time": "17:00:00",
            "end_time": "23:00:00",
            "description": "<p>EPFL racing team will provide an update on the main achievments of this year </p>",
            "image_description": "",
            "creation_date": "2026-04-22T11:10:32",
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            "canceled": "False",
            "cancel_reason": "",
            "place_and_room": "DLLEL 0 28",
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            "speaker": "EPFL Racing team",
            "organizer": "EPFL Racing Team",
            "contact": "<a class=\"hover:text-white transition-colors\" href=\"mailto:[email protected]\">[email protected]</a>",
            "is_internal": "False",
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                "fr_label": "Sur invitation",
                "en_label": "Invitation required"
            },
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            "icalendar_url": "https://memento.epfl.ch/event/export/120477/",
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