retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=100&ordering=-event__category
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "title": "Master's Graduation",
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            "id": 66557,
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            "lang": "en",
            "start_date": "2026-08-31",
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            "description": "<p>This day is an opportunity for architecture students from the 2nd year Bachelor to the 2nd year Master to attend presentations of the studio and teaching unit programmes, to enable them to choose their options and finalise their enrolments.There will be no online replay and the event is not recorded. The presentation documents are available on the dedicated pages:<br>\r\n<br>\r\n<a href=\"https://go.epfl.ch/sar-website-studios-fr\">Design studios and teaching units</a>  ↗︎<br>\r\n<br>\r\n<a href=\"https://memento.epfl.ch/event/inscriptions-automne-ateliers-ue/\">Registration dates</a>  ↗︎</p>",
            "image_description": "",
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            "title": "Understanding and Predicting the Membrane Permeability of Macrocyclic Peptides Based on Large-Scale Data",
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            "start_date": "2026-09-15",
            "end_date": "2026-09-15",
            "start_time": "16:15:00",
            "end_time": "17:15:00",
            "description": "<p>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.<br>\r\n<br>\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.<br>\r\n<br>\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.</p>",
            "image_description": "Prof. Shinsuke Sando",
            "creation_date": "2026-05-22T16:51:02",
            "last_modification_date": "2026-05-22T16:51:02",
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            "canceled": "False",
            "cancel_reason": "",
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            "speaker": "Prof. Shinsuke Sando, University of Tokyo",
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            "id": 71933,
            "title": "Controlling and Guiding Generative Models for Three-Dimensional Shape Optimization",
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            "visual_url": null,
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            "start_date": "2026-07-07",
            "end_date": "2026-07-07",
            "start_time": "11:00:00",
            "end_time": "13:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Martin Rajman<br>\r\nThesis advisor: Prof. Pascal Fua<br>\r\nCo-examiner: Prof. Mark Pauly<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nOptimizing 3D shapes within the latent spaces of deep generative models is fundamental to computer assisted engineering, yet remains prone to a critical failure mode we term manifold drift: the tendency of gradient-based optimization to move latent vectors away from the manifold of valid shapes. This problem is exacerbated in state-of-the-art 3D shape generative models that operate in increasingly high-dimensional latent spaces where valid shapes occupy a vanishingly small fraction of the full space. Existing mitigation strategies, including latent regularization and flow-matching approaches, either sacrifice expressiveness, demand a difficult trade-off between objective guidance and generative fidelity that remains prone to manifold drift, or are computationally infeasible to scale to modern, large-capacity 3D shape models. We introduce a novel optimizer-corrector framework that alternates between gradient steps for objective minimization and guided flow matching to drive the latent state back to the valid shape manifold. By decoupling objective minimization from flow-based correction, optimizing freely and correcting strictly, this alternating design avoids inherent trade-offs, preserving geometric validity without sacrificing expressiveness while remaining computationally feasible on modern 3D shape models. We demonstrate its effectiveness across generative priors of varying complexity, from simple vector latent spaces to large-scale architectures across a variety of downstream optimization tasks, including aerodynamic drag reduction and object compliance optimization.<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\n ",
            "image_description": "",
            "creation_date": "2026-05-22T13:14:54",
            "last_modification_date": "2026-05-22T13:14:54",
            "link_label": "",
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            "cancel_reason": "",
            "place_and_room": "BC 333",
            "url_place_and_room": "https://plan.epfl.ch/?room==BC%20333",
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            "spoken_languages": [],
            "speaker": "Emilien Seiler",
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            "keywords": "EDIC candidacy exam",
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        {
            "id": 71932,
            "title": "Failure-Aware LLM Serving for Agentic Workloads",
            "slug": "failure-aware-llm-serving-for-agentic-workloads",
            "event_url": "https://memento.epfl.ch/event/failure-aware-llm-serving-for-agentic-workloads",
            "visual_url": null,
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            "start_date": "2026-06-17",
            "end_date": "2026-06-17",
            "start_time": "09:00:00",
            "end_time": "11:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Anastasia Ailamaki<br>\r\nThesis advisor: Prof. Anne-Marie Kermarrec<br>\r\nCo-examiner: Prof. Robert West<br>\r\n<br>\r\n<u>Abstract</u><br>\r\n<br>\r\n<br>\r\n<u>Selected papers</u>\r\n<ul>\r\n\t<li>ReAct (<a href=\"https://arxiv.org/pdf/2210.03629\" target=\"_blank\">https://arxiv.org/pdf/2210.03629</a>)</li>\r\n\t<li>Agentix (<a href=\"https://www.usenix.org/system/files/nsdi26-luo.pdf\" target=\"_blank\">https://www.usenix.org/system/files/nsdi26-luo.pdf</a>)</li>\r\n\t<li>Why do multi-agent systems fail? (<a href=\"https://arxiv.org/pdf/2503.13657\" target=\"_blank\">https://arxiv.org/pdf/2503.13657</a>)</li>\r\n</ul>",
            "image_description": "",
            "creation_date": "2026-05-22T13:11:09",
            "last_modification_date": "2026-05-22T13:12:05",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
            "cancel_reason": "",
            "place_and_room": "BC 133",
            "url_place_and_room": "https://plan.epfl.ch/?room==BC%20133",
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            "spoken_languages": [],
            "speaker": "Palak",
            "organizer": "",
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            "keywords": "EDIC candidacy exam",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/120839/",
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                "https://memento.epfl.ch/api/v1/mementos/27/?format=api"
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        {
            "id": 71931,
            "title": "Access Bit Scanning for Page Replacement Policies",
            "slug": "access-bit-scanning-for-page-replacement-policies",
            "event_url": "https://memento.epfl.ch/event/access-bit-scanning-for-page-replacement-policies",
            "visual_url": null,
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            "lang": "en",
            "start_date": "2026-06-22",
            "end_date": "2026-06-22",
            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Thomas Bourgeat<br>\r\nThesis advisor: Prof. Babak Falsafi<br>\r\nCo-examiner: Prof. Sanidhya Kashyap<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nModern workloads with memory footprints ranging from hundreds of gigabytes to several terabytes have become widespread over the last decade. With memory accounting for nearly 50% of server costs in modern data centres, provisioning large DRAM capacities significantly increases total cost of ownership (TCO). Tiered memory architectures combine memories with different capacities, latencies, and cost characteristics to improve cost efficiency while satisfying application performance requirements. Application performance in these architectures is highly sensitive to page placement decisions. Consequently, making informed placement decisions requires precise tracking of data access patterns and accurate identification of hot pages.<br>\r\n<br>\r\nExisting operating systems commonly rely on hardware-maintained access bits in page table entries to estimate memory access behaviour and identify hot data regions. They periodically scan the application's entire virtual address space to construct workload access profiles. However, linear scanning of page table access bits does not scale for modern applications with terabyte-scale memory footprints. Since scanning overhead scales with the memory footprint, a single full scan can take several seconds for workloads with large memory footprints. Reducing scanning frequency lowers monitoring overhead but also decreases profiling accuracy and responsiveness to changing access patterns, resulting in a fundamental tradeoff between profiling accuracy and monitoring overhead. Therefore, we need scalable, low-overhead mechanisms for access monitoring in next-generation memory management systems.<br>\r\n<br>\r\nIn this talk, I will discuss recent approaches to scalable memory access profiling in large-memory systems. Specifically, I will present works that use techniques such as adaptive sampling, region-based monitoring, and hierarchical profiling of page table trees to reduce and bound scanning overhead. <br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
            "image_description": "",
            "creation_date": "2026-05-22T13:08:29",
            "last_modification_date": "2026-05-22T13:18:11",
            "link_label": "",
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            "canceled": "False",
            "cancel_reason": "",
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            "url_place_and_room": "https://plan.epfl.ch/?room==BC%20010",
            "url_online_room": "",
            "spoken_languages": [],
            "speaker": "<br>\r\nArunkrishna Annai Madalam Sivasubramanian  ",
            "organizer": "",
            "contact": "[email protected]",
            "is_internal": "False",
            "theme": "",
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            "keywords": "EDIC candidacy exam",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/120838/",
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                "https://memento.epfl.ch/api/v1/mementos/27/?format=api"
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        {
            "id": 71930,
            "title": "Generative models for black-box optimization of complex objectives",
            "slug": "generative-models-for-black-box-optimization-of-co",
            "event_url": "https://memento.epfl.ch/event/generative-models-for-black-box-optimization-of-co",
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            "lang": "en",
            "start_date": "2026-07-09",
            "end_date": "2026-07-09",
            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Nicolas Flammarion<br>\r\nThesis advisor: Prof. Pascal Fua<br>\r\nCo-examiner: Prof. Alexander Mathis<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nMany high-impact problems in science and engineering reduce to optimizing a complex objective, where each evaluation is costly and often unreliable: physical experiments fail, simulators diverge, and stochastic systems return noisy feedback. Classical black-box optimizers struggle in this regime, where evaluation budgets are tight and the feasible region is hard to characterize a priori. Our work investigates how the statistical expressivity of modern generative samplers can be leveraged in black-box optimization. We propose that these samplers enable efficient navigation of feasible sets and optimization of geometrically complex objectives under limited, unreliable observations. <br>\r\n<br>\r\nTwo complementary lines of work have already been studied. The main one, SPARROW, demonstrated that a sampler-driven optimizer can substantially reduce the number of function calls needed to maximize complex and unreliable objectives. A parallel line established that samplers can be steered to satisfy hard constraints without sacrificing the statistical diversity of the generated samples. Because SPARROW imposes minimal assumptions on the underlying sampler, these constrained samplers can drive it directly, opening a path to constrained black-box optimization.<br>\r\n<br>\r\nBuilding on these results, two directions are planned. The first is theoretical: a deeper mathematical study of sampler-driven optimization, drawing on the broader literature on sample-efficient black-box optimization, in order to derive stronger guarantees and more efficient algorithms. The second is applied: applying the methods to concrete domains and exploiting the structure those domains expose to sharpen performance beyond what a pure black-box treatment can achieve.<br>\r\n<br>\r\nThe applications of low-budget black-box optimization are diverse, including engineering design (e.g. aerodynamic shape optimization, mechanical components), scientific discovery (e.g. protein and molecule design under synthesizability and stability constraints), and the safety and security of opaque ML systems (e.g. query-efficient adversarial probing, red-teaming of black-box models).<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\n ",
            "image_description": "",
            "creation_date": "2026-05-22T12:53:32",
            "last_modification_date": "2026-05-22T13:09:04",
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            "link_url": "",
            "canceled": "False",
            "cancel_reason": "",
            "place_and_room": "BC 333",
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            "spoken_languages": [],
            "speaker": "Edouard Dufour",
            "organizer": "",
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            },
            "keywords": "EDIC candidacy exam",
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        },
        {
            "id": 71919,
            "title": "MEchanics GAthering –MEGA- Seminar: Navigating the shift from academia to the industrial sector",
            "slug": "mechanics-gathering-mega-seminar-navigating-the-sh",
            "event_url": "https://memento.epfl.ch/event/mechanics-gathering-mega-seminar-navigating-the-sh",
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            "lang": "en",
            "start_date": "2026-05-28",
            "end_date": "2026-05-28",
            "start_time": "13:05:00",
            "end_time": "14:00:00",
            "description": "<strong>Abstract:</strong> What does it mean to move from an academic career into industry after a PhD or postdoctoral experience? Which skills transfer naturally, which challenges emerge along the way, and how can scientists prepare for the shift?<br>\r\nIn this seminar, two speakers from different scientific backgrounds will share their personal journeys from academia to industry.They will offer honest, complementary perspectives on leaving university research, exploring the practical realities, challenges, and distinct working cultures of the industry sector.<br>\r\nThrough their experiences, participants will gain practical insights into recruitment processes, workplace expectations, and the opportunities available to scientists in industry.<br>\r\n<br>\r\n<strong>Tristans's Bio: </strong>I got a PhD in aeronautical Engineering in 2011 from KTH, Stockholm, Sweden, with a thesis on Aerodynamics simulations of ground vehicles in unsteady crosswind.<br>\r\nAfter this, I worked with various Formula One teams from 2012 to 2025, starting as a CFD Engineer and moving to an Aerodynamicist role in 2014. Between 2022 and 2025, I have been involved in the development of the British Challenger for the 37th America’s Cup (iconic Yacht competition), leading the Fluid Dynamics team towards the end.<br>\r\nSince summer 2025, I am a scientist at LFMI on a FNS funded project “Why do albatrosses and pelicans morph to an arch-shaped wing configuration when gliding near the water surface?”.<strong> <br>\r\n<br>\r\nBertrand's Bio: </strong>After completing an Aerospace Engineering degree from ISAE-SUPAERO (Toulouse, France) and Université de Toulouse, where I specialized on Earth observation, numerical modeling and climate science, I completed my PhD at Météo-France's Center for Snow Studies (CEN, Grenoble, France). I worked for four years as a postdoc at the Snow and Avalanche Research Lab (SLF, Davos, Switzerland), at the interface between research and operational flood forecasting. Since 2025, I joined Hydrique Ingénieurs, in Lausanne, where I do numerical modeling for various projects related to water resources management and flood forecasting.<br>\r\n<br>\r\nThe talk will be followed by an informal apero!<br>\r\n ",
            "image_description": "",
            "creation_date": "2026-05-21T15:33:37",
            "last_modification_date": "2026-05-22T16:07:51",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
            "cancel_reason": "",
            "place_and_room": "ME B1 10",
            "url_place_and_room": "https://plan.epfl.ch/?room==ME%20B1%2010",
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            "spoken_languages": [
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            "speaker": "<a href=\"https://people.epfl.ch/tristan.favre?lang=en\">Tristan Favre</a> (<a href=\"https://lfmi.epfl.ch/\">LFMI</a>, EPFL), Bertrand Cluzet (<a href=\"https://hydrique.ch/fr\">Hydrique Ingénieurs</a>)",
            "organizer": "MEGA.Seminar Organizing Committee",
            "contact": "<a href=\"http://[email protected]/\">Aliénor Riviere</a>, <a href=\"http://[email protected]/\">Danick Lamoureux</a>, <a href=\"http://[email protected]/\">Jacopo Bilotto</a>",
            "is_internal": "False",
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                "fr_label": "Entrée libre",
                "en_label": "Free"
            },
            "keywords": "Career Development, Transferable Skills",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/120824/",
            "category": {
                "id": 1,
                "code": "CONF",
                "fr_label": "Conférences - Séminaires",
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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",
            "visual_url": "https://memento.epfl.ch/image/33235/200x112.jpg",
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            "lang": "en",
            "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": "",
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            "canceled": "False",
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            "place_and_room": "GA 3 21",
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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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            "icalendar_url": "https://memento.epfl.ch/event/export/120823/",
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