retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=210&ordering=slug
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "title": "Talent Pitch Switzerland 2026",
            "slug": "talent-pitch-switzerland-2026",
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            "start_date": "2026-05-06",
            "end_date": "2026-05-06",
            "start_time": "18:00:00",
            "end_time": "22:30:00",
            "description": "<p>Talent Pitch is a pitching contest that will take place for the fourth time on May 6, 2026, at the Volkshaus in Zurich. Our partner universities will send their top start-ups to the event, with all founding teams currently studying at their respective institutions. Both the audience and the jury will have the opportunity to decide which start-up emerges as the winner. <br>\r\n<br>\r\n<a href=\"https://talent-pitch.org/\">more info here</a></p>",
            "image_description": "",
            "creation_date": "2025-12-10T12:02:25",
            "last_modification_date": "2026-03-17T16:34:05",
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            "contact": "<a href=\"mailto:[email protected]\">Noah Bellwald</a>",
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            "id": 71283,
            "title": "TBA",
            "slug": "tba-128",
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            "lang": "en",
            "start_date": "2026-04-22",
            "end_date": "2026-04-22",
            "start_time": "14:15:00",
            "end_time": "15:15:00",
            "description": "<p>TBA<br>\r\n </p>",
            "image_description": "",
            "creation_date": "2026-03-03T09:23:22",
            "last_modification_date": "2026-03-25T12:25:59",
            "link_label": "",
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            "speaker": "Annika Thiele, Humboldt-Universität zu Berlin",
            "organizer": "Markus Kirolos",
            "contact": "Maroussia Schaffner",
            "is_internal": "False",
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            "id": 71270,
            "title": "TBA",
            "slug": "tba-136",
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            "start_date": "2026-04-17",
            "end_date": "2026-04-17",
            "start_time": "15:15:00",
            "end_time": "16:15:00",
            "description": "<p>TBA</p>",
            "image_description": "",
            "creation_date": "2026-03-02T09:46:57",
            "last_modification_date": "2026-03-02T09:50:51",
            "link_label": "",
            "link_url": "https://www.epfl.ch/schools/sb/research/math/statistics-seminars/",
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            "speaker": "Sam Allen, KIT",
            "organizer": "Rajita Chandak",
            "contact": "Maroussia Schaffner",
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        {
            "id": 58413,
            "title": "[ The Cogito Foundation | “Public understanding of Science” ]",
            "slug": "the-cogito-foundation-public-understanding-of-sc-4",
            "event_url": "https://memento.epfl.ch/event/the-cogito-foundation-public-understanding-of-sc-4",
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            "lang": "en",
            "start_date": "2026-05-01",
            "end_date": "2026-05-01",
            "start_time": null,
            "end_time": null,
            "description": "<p>The Foundation <strong>offers funding for projects, congresses and events</strong> that aim to increase the public understanding of science and scientific thinking <strong>in Switzerland.</strong><br>\r\n<br>\r\n<br>\r\n<strong>Restriction</strong> : The Foundation <strong>does not grant additional costs</strong> for projects already funded by <strong>SNSF, ERC or similar agencies</strong>, and <strong>does not cover institutional overheads</strong>; <strong>infrastructure must be provided by the applicant</strong>.<br>\r\n<br>\r\n \r\n</p><ol>\r\n\t<li>PUBLIC UNDERSTANDING OF SCIENCE</li>\r\n</ol>\r\n\r\n<ul>\r\n\t<li><u>For what</u>:  Activities and projects <strong>in Switzerland</strong> that strengthen the public understanding of scientific thinking. (Overheads are <strong>not</strong> covered.)</li>\r\n\t<li><u>How much</u>: Grants are typically <strong>around CHF 10,000 or CHF 50,000</strong>, and <strong>rarely exceed CHF 100,000</strong>.</li>\r\n</ul>\r\n \r\n\r\n<ol start=\"2\">\r\n\t<li>CONGRESSES</li>\r\n</ol>\r\n\r\n<ul>\r\n\t<li><u>For what</u>: <strong>Congresses and events that increase the public understanding of science and scientific thinking in Switzerland</strong></li>\r\n\t<li><u>How much</u>: Typically <strong>around CHF 10,000 or CHF 50,000</strong>; <strong>rarely above CHF 100,000</strong>.</li>\r\n</ul>\r\n<br>\r\n<strong>DEADLINES</strong>: <strong>1 May</strong> and <strong>1 October</strong> (every year) at 1 p.m. CET.<br>\r\nDecisions: end of June and beginning of November.<br>\r\n<br>\r\n<strong>Application</strong>: Submit your application in English or German, as a single PDF-document, to <a href=\"mailto:[email protected]\">[email protected]</a>. <strong>Guidelines </strong>for applicants are available at this <a href=\"https://www.cogitofoundation.ch/en/guidelines-submission-proposals\">link</a>.<br>\r\n<br>\r\n<strong>Selection process</strong>:\r\n\r\n<ul>\r\n\t<li>ELIGIBILITY CHECK: the executive committee of the Foundation Council checks if the application is in line with the goals of the Foundation and <u>immediately</u> informs the applicant if this is not the case.</li>\r\n\t<li>EVALUATION: proposals passing the eligibility check are submitted to the <a href=\"https://www.cogitofoundation.ch/en/council\">Foundation Council</a>.<br>\r\n\t </li>\r\n</ul>\r\n<strong>For further information</strong>, please have a look at the <a href=\"https://www.cogitofoundation.ch/en/home\">foundation website</a>.<br>\r\n ",
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            "last_modification_date": "2026-03-23T10:26:29",
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            "keywords": "research funding",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/100832/",
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                "id": 16,
                "code": "PROP",
                "fr_label": "Appel à proposition",
                "en_label": "Call for proposal",
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        {
            "id": 70040,
            "title": "“The end of KRAS cancers?”",
            "slug": "the-end-of-kras-cancers",
            "event_url": "https://memento.epfl.ch/event/the-end-of-kras-cancers",
            "visual_url": "https://memento.epfl.ch/image/31503/200x112.jpg",
            "visual_large_url": "https://memento.epfl.ch/image/31503/720x405.jpg",
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            "lang": "en",
            "start_date": "2026-05-07",
            "end_date": "2026-05-07",
            "start_time": "12:15:00",
            "end_time": "13:15:00",
            "description": "<strong>A Lola and John Grace Distinguished Lecture in Cancer Research</strong>\r\n<div class=\"elementor-element elementor-element-98cefd8 elementor-widget elementor-widget-heading\">\r\n<div class=\"elementor-widget-container\"><br>\r\nFrank McCormick, PhD, is a Professor at the UCSF Helen Diller Family Comprehensive Cancer Center and holds the David A. Wood Chair of Tumor Biology and Cancer Research. Prior to joining the UCSF faculty, Dr. McCormick pursued cancer-related work with several Bay Area biotechnology firms and held positions with Cetus Corporation (Director of Molecular Biology, 1981-1990; Vice President of Research, 1990-1991) and Chiron Corporation, where he was Vice President of Research. In 1992 he founded Onyx Pharmaceuticals, a company dedicated to developing new cancer therapies, and served as its Chief Scientific Officer until 1996. At Onyx Pharmaceuticals, he initiated drug discovery efforts that led to the approval of Sorafenib in 2005 for treatment of renal cell cancer, and for liver cancer in 2007, and the approval of ONYX-015 in 2006 in China for treatment of nasopharyngeal cancer. In addition, Dr. McCormick’s group led to the identification of the CDK4 kinase inhibitor, Palbociclib, approved for treating advanced breast cancer. Dr. McCormick's current research interests center on ways of targeting Ras proteins and their regulators, including the NF1 protein neurofibromin.<br>\r\n<br>\r\nDr. McCormick was Director of the Helen Diller Family Comprehensive Cancer Center from 1997 to 2014 and he served as President, 2012-2013, for the American Association for Cancer Research. Since 2013, Dr. McCormick has led the National Cancer Institute’s Ras Initiative at the Frederick National Laboratories for Cancer Research overseeing the national effort to develop therapies against Ras-driven cancers. Dr. McCormick was recently awarded (September 2025) the Inaugural Stephenson Global Prize Award in recognition of his research and discoveries that have transformed the field of RAS-driven cancers. <br>\r\n<br>\r\nDr. McCormick is the author of over 430 scientific publications and holds more than 20 issued patents and is a Fellow of the Royal Society and a member of the National Academy of Sciences.<br>\r\n </div>\r\n</div>\r\n\r\n<div class=\"elementor-element elementor-element-e552a16 elementor-widget elementor-widget-text-editor\">\r\n<div class=\"elementor-widget-container\"> </div>\r\n</div>",
            "image_description": "",
            "creation_date": "2025-10-07T11:05:07",
            "last_modification_date": "2026-01-06T12:15:21",
            "link_label": "",
            "link_url": "",
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            "cancel_reason": "",
            "place_and_room": "SV 1717",
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            "speaker": "<strong><em>Frank McCormick, PhD, FRS, DSc (Hon), </em></strong>UCSF Helen Diller Family Comprehensive Cancer Center and David A. Wood Chair of Tumor Biology and Cancer Research",
            "organizer": "Prof. Doug Hanahan",
            "contact": "Lisa Smith, ISREC Administrative Assistant",
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            "keywords": "Grace Lecture, cancer",
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        {
            "id": 71402,
            "title": "The World at Play : play, create, think",
            "slug": "the-world-at-play-play-create-think",
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            "lang": "en",
            "start_date": "2026-03-18",
            "end_date": "2026-04-30",
            "start_time": null,
            "end_time": null,
            "description": "<p>From digital puzzles to space simulations, play has become a major arena for creation, innovation, and reflection. Through a curated selection of video games, history books, essays, and academic research, the Library invites you to discover the many dimensions of games and gaming culture. Borrow the documents and keep the experience going at home!</p>",
            "image_description": "CC-BY-NC-SA EPFL Library",
            "creation_date": "2026-03-18T09:56:25",
            "last_modification_date": "2026-03-18T09:56:55",
            "link_label": "Sélection documentaire en ligne",
            "link_url": "https://slsp-epfl.primo.exlibrisgroup.com/discovery/collectionDiscovery?vid=41SLSP_EPF:prod&collectionId=8196759420005516&lang=fr",
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            "cancel_reason": "",
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            "keywords": "Jeux, jeux vidéo, théorie des jeux",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/120117/",
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        {
            "id": 70950,
            "title": "Theoretical Realisation of Quantum Phenomena In Computational Materials Discovery",
            "slug": "theoretical-realisation-of-quantum-phenomena-in--2",
            "event_url": "https://memento.epfl.ch/event/theoretical-realisation-of-quantum-phenomena-in--2",
            "visual_url": "https://memento.epfl.ch/image/32338/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-06-22",
            "end_date": "2026-06-24",
            "start_time": null,
            "end_time": null,
            "description": "<p>You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: <a href=\"https://www.cecam.org/workshop-details/theoretical-realisation-of-quantum-phenomena-in-computational-materials-discovery-1485\">https://www.cecam.org/workshop-details/theoretical-realisation-of-quantum-phenomena-in-computational-materials-discovery-1485</a>.<br>\r\n<br>\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any).  However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the <a href=\"mailto:[email protected]\">CECAM Event Manager</a> if you have any question.<br>\r\n<br>\r\n<strong>Description</strong><br>\r\n<br>\r\nQuantum phenomena in materials underpin a range of emerging technologies, including spin-based quantum technologies, efficient energy transport materials and ultra-narrow bandwidth lasers.<sup>1,2,3</sup> Emergent behaviour such as quantum magnetism, superconductivity and superradiance<sup>4</sup> arise from the complex interplay between electronic and structural properties; electronic features including strong electron correlation, spin-orbit coupling and reduced dimensionality can lead to phenomena such as unconventional superconductivity and room-temperature spin coherences, whilst structural factors such as crystal symmetry, doping concentrations and Moiré twist patterns are pivotal in shaping these quantum characteristics.<sup>5,6</sup> Computational quantum materials discovery requires both highly advanced theoretical models of the electronic structure and high-throughput approaches for identifying stable crystal structures and predicting their properties.<sup>3,7</sup><br>\r\nStrongly correlated electrons, ubiquitous in quantum materials, challenge conventional density functional theory (DFT). Quantum embedding methods, such as Density Matrix Embedding Theory (DMET) and Quantum Defect Embedding Theory (QDET), are powerful tools for describing strongly correlated electronic states in materials. QDET solves an effective Hamiltonian for a strongly-correlated subset of DFT orbitals using full configuration interaction, parameterized via a Green's function approach.<sup>8</sup> DMET, however, maps the solid-state problem onto a self-consistent quantum impurity coupled to a mean-field bath, with the impurity solved by high-level methods.<sup>9</sup> The application of these advanced techniques is rapidly growing, from analysing superconducting cuprates to describing quantum spin defects in semiconductors.<sup>8,9</sup><br>\r\nModel Hamiltonians, such as the multi-band Hubbard model, are increasingly used to describe the low-energy physics of quantum materials.<sup>10</sup> While the constrained random phase approximation is the traditional choice for parametrising these models,<sup>11</sup> the newly developed moment-conserved RPA may offer superior accuracy by conserving instantaneous two-point correlation functions.<sup>12,13</sup> Powerful numerical techniques like Determinant Quantum Monte Carlo have recently been pioneered for solving the model Hamiltonian and predicting quantum phenomena such as pairing susceptibilities.<sup>14</sup><br>\r\nSuch theoretical methods are also essential for computational discovery of spin defects in semiconductors, a promising platform for room-temperature qubits.<sup>3,15</sup> Advanced theoretical treatments are essential to predict defect electronic, magnetic, and optical properties, incorporating effects like spin-orbit and spin-phonon coupling which determine spin coherence and optical manipulation characteristics. The current state-of-the-art combines DFT studies of semiconductor bulk properties with ab initio treatments of the defect; quantum embedding methods are emerging as a promising alternative.<sup>16,17</sup><br>\r\nGiven the immense diversity of materials, high-throughput screening is a cornerstone of modern materials discovery. DFT, particularly with state-of-the-art approximations like r2SCAN+rVV10, remains the workhorse for reliably determining material structures; such calculations often offer critical insight into both a systems stability and electronic structure.<sup>7,18,19,20</sup> Machine learning (ML) is transforming materials discovery by slashing the computational cost of such calculations, allowing a wider exploration of composition space.<sup>21,22</sup><br>\r\nComputational quantum materials modelling is advancing rapidly, however reconciling methods treating strongly correlated electrons with computational workflows employed in modern materials discovery remains relatively unexploited. The synergy of advanced theory, high-performance computing and ML has the potential to drive breakthroughs in quantum materials discovery and accelerate development of emerging technologies, from novel qubit platforms to room-temperature superconductors.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.132.076401\" target=\"_blank\">[1] C. Scott, G. Booth, Phys. Rev. Lett., <strong>132</strong>, 076401 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41524-025-01554-0\" target=\"_blank\">[2] X. Jiang, W. Wang, S. Tian, H. Wang, T. Lookman, Y. Su, npj. Comput. Mater., <strong>11</strong>, 79 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.triboint.2024.110438\" target=\"_blank\">[3] S. Giaremis, M. Righi, Tribology International, <strong>204</strong>, 110438 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41524-024-01437-w\" target=\"_blank\">[4] Z. Zhu, J. Park, H. Sahasrabuddhe, A. Ganose, R. Chang, J. Lawson, A. Jain, npj. Comput. Mater., <strong>10</strong>, 258 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1002/jcc.26353\" target=\"_blank\">[5] R. Nelson, C. Ertural, J. George, V. Deringer, G. Hautier, R. Dronskowski, J. Comput. Chem., <strong>41</strong>, 1931-1940 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1021/acsmaterialsau.2c00059\" target=\"_blank\">[6] M. Kothakonda, A. Kaplan, E. Isaacs, C. Bartel, J. Furness, J. Ning, C. Wolverton, J. Perdew, J. Sun, ACS Mater. Au, <strong>3</strong>, 102-111 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41524-025-01547-z\" target=\"_blank\">[7] V. Briganti, A. Lunghi, npj. Comput. Mater., <strong>11</strong>, 62 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.5c00355\" target=\"_blank\">[8] A. Kundu, F. Martinelli, G. Galli, J. Phys. Chem. Lett., <strong>16</strong>, 1973-1979 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1557/s43577-023-00659-5\" target=\"_blank\">[9] A. Gali, A. Schleife, A. Heinrich, A. Laucht, B. Schuler, C. Chakraborty, C. Anderson, C. Déprez, J. McCallum, L. Bassett, M. Friesen, M. Flatté, P. Maurer, S. Coppersmith, T. Zhong, V. Begum-Hudde, Y. Ping, MRS Bulletin, <strong>49</strong>, 256-276 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1073/pnas.2408717121\" target=\"_blank\">[10] P. Mai, B. Cohen-Stead, T. Maier, S. Johnston, Proc. Natl. Acad. Sci. U.S.A., <strong>121</strong>, (2024)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevb.108.064511\" target=\"_blank\">[11] C. Pellegrini, C. Kukkonen, A. Sanna, Phys. Rev. B, <strong>108</strong>, 064511 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1186/s40712-024-00202-7\" target=\"_blank\">[12] R. Goyal, S. Maharaj, P. Kumar, M. Chandrasekhar, J Mater. Sci: Mater Eng., <strong>20</strong>, 4 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41524-024-01314-6\" target=\"_blank\">[13] Y. Chang, E. van Loon, B. Eskridge, B. Busemeyer, M. Morales, C. Dreyer, A. Millis, S. Zhang, T. Wehling, L. Wagner, M. Rösner, npj. Comput. Mater., <strong>10</strong>, 129 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevx.15.021049\" target=\"_blank\">[14] H. Padma, J. Thomas, S. TenHuisen, W. He, Z. Guan, J. Li, B. Lee, Y. Wang, S. Lee, Z. Mao, H. Jang, V. Bisogni, J. Pelliciari, M. Dean, S. Johnston, M. Mitrano, Phys. Rev. X, <strong>15</strong>, 021049 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-025-56883-x\" target=\"_blank\">[15] Z. Cui, J. Yang, J. Tölle, H. Ye, S. Yuan, H. Zhai, G. Park, R. Kim, X. Zhang, L. Lin, T. Berkelbach, G. Chan, Nat. Commun., <strong>16</strong>, 1845 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.5c00287\" target=\"_blank\">[16] L. Otis, Y. Jin, V. Yu, S. Chen, L. Gagliardi, G. Galli, J. Phys. Chem. Lett., <strong>16</strong>, 3092-3099 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1039/d5dd00019j\" target=\"_blank\">[17] A. Ganose, H. Sahasrabuddhe, M. Asta, K. Beck, T. Biswas, A. Bonkowski, J. Bustamante, X. Chen, Y. Chiang, D. Chrzan, J. Clary, O. Cohen, C. Ertural, M. Gallant, J. George, S. Gerits, R. Goodall, R. Guha, G. Hautier, M. Horton, T. Inizan, A. Kaplan, R. Kingsbury, M. Kuner, B. Li, X. Linn, M. McDermott, R. Mohanakrishnan, A. Naik, J. Neaton, S. Parmar, K. Persson, G. Petretto, T. Purcell, F. Ricci, B. Rich, J. Riebesell, G. Rignanese, A. Rosen, M. Scheffler, J. Schmidt, J. Shen, A. Sobolev, R. Sundararaman, C. Tezak, V. Trinquet, J. Varley, D. Vigil-Fowler, D. Wang, D. Waroquiers, M. Wen, H. Yang, H. Zheng, J. Zheng, Z. Zhu, A. Jain, Digital Discovery, (2025)</a><br>\r\n<a href=\"https://doi.org/10.1002/adma.202106909\" target=\"_blank\">[18] W. Ko, Z. Gai, A. Puretzky, L. Liang, T. Berlijn, J. Hachtel, K. Xiao, P. Ganesh, M. Yoon, A. Li, Advanced Materials, <strong>35</strong>, (2022)</a><br>\r\n<a href=\"https://doi.org/10.1126/science.adg0014\" target=\"_blank\">[19] L. Du, M. Molas, Z. Huang, G. Zhang, F. Wang, Z. Sun, Science, <strong>379</strong>, (2023)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41586-023-07001-8\" target=\"_blank\">[20] C. Zhu, S. Boehme, L. Feld, A. Moskalenko, D. Dirin, R. Mahrt, T. Stöferle, M. Bodnarchuk, A. Efros, P. Sercel, M. Kovalenko, G. Rainò, Nature, <strong>626</strong>, 535-541 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1515/nanoph-2022-0723\" target=\"_blank\">[21] Á. Gali, Nanophotonics, <strong>12</strong>, 359-397 (2023)</a><br>\r\n<a href=\"https://doi.org/10.3389/fmats.2024.1343005\" target=\"_blank\">[22] V. Harris, P. Andalib, Front. Mater., <strong>11</strong>, (2024)</a></p>",
            "image_description": "",
            "creation_date": "2026-01-26T14:46:04",
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            "link_label": "Theoretical Realisation of Quantum Phenomena In Computational Materials Discovery",
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            "organizer": "<strong>Petros-Panagis Filippatos, </strong>University of Nottingham ; <strong>Katherine Inzani, </strong>University of Nottingham ; <strong>Tom Irons, </strong>University of Nottingham ; <strong>Connor Williamson, </strong>University of Nottingham",
            "contact": "<a href=\"mailto:[email protected]\"><strong>Cornelia Bujenita</strong></a>, CECAM Events and Operations Manager",
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        },
        {
            "id": 71486,
            "title": "Topological Data Analysis for Gait Pattern Classification",
            "slug": "topological-data-analysis-for-gait-pattern-classif",
            "event_url": "https://memento.epfl.ch/event/topological-data-analysis-for-gait-pattern-classif",
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            "lang": "en",
            "start_date": "2026-04-23",
            "end_date": "2026-04-23",
            "start_time": "10:00:00",
            "end_time": "11:00:00",
            "description": "<p>The classification of gait patterns is an important challenge in movement analysis, as it supports clinical assessment and decision-making by enabling diagnosis and severity stratification. In this talk, I will discuss the potential of Topological Data Analysis (TDA) for gait pattern classification. Unlike conventional approaches that rely on explicit detection of Gait Events (GEs) to compute Spatiotemporal Gait Parameters (SGPs), TDA characterises the global structure of gait signals directly, capturing relationships and patterns in the data without requiring GEs. This is particularly relevant in real-world settings, where GE detection can be diQicult due to heterogeneity in walking conditions and gait patterns, potentially biasing clinically relevant metrics and, consequently, decision-making.<br>\r\nWithin our department, preliminary results have shown that TDA-based features can achieve classification performance comparable to that of SGPs in fall-risk assessment. These findings suggest that topology oQers a competitive alternative for representing gait data, with the potential to better handle variability across subjects and pathological<br>\r\nconditions.<br>\r\nBuilding on these results, we plan to further extend the TDA framework in two directions. First, we aim to investigate time-aware topological methods to better capture the<br>\r\ntemporal structure of gait signals. Second, we will explore Topological Deep Learning (TDL) approaches to reduce reliance on handcrafted design choices and potentially<br>\r\nimprove classification performance. By combining the robustness of topology with datadriven representation learning, this work seeks to provide robust tools for the classification of typical and pathological gait patterns.<br>\r\n </p>",
            "image_description": "",
            "creation_date": "2026-03-30T09:44:37",
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            "link_label": "",
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            "speaker": "Elena Botti, Vrije Universiteit Brussel (VUB)",
            "organizer": "Markus Kirolos",
            "contact": "Maroussia Schaffner",
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        },
        {
            "id": 71448,
            "title": "Topological properties of rough fluids and plasmas",
            "slug": "topological-properties-of-rough-fluids-and-plasmas",
            "event_url": "https://memento.epfl.ch/event/topological-properties-of-rough-fluids-and-plasmas",
            "visual_url": "https://memento.epfl.ch/image/32796/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-04-24",
            "end_date": "2026-04-24",
            "start_time": "14:15:00",
            "end_time": null,
            "description": "<p>Abstract:<br>\r\nAs anticipated by Onsager's conjecture, low-regularity solutions of the Euler equations exhibit greater flexibility than classical solutions. In the first part of this talk we focus on steady solutions, showing that in the low-regularity regime their streamlines can realize any prescribed topology, a phenomenon that cannot occur for classical solutions. The key tool is a novel implementation of convex integration that preserves the topology of the streamlines throughout the iteration. In the second part we extend these ideas to the MHD equations, constructing continuous weak solutions with constant nonzero helicity that nevertheless fail to conserve energy and cross helicity.</p>",
            "image_description": "",
            "creation_date": "2026-03-25T09:22:27",
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            "speaker": "Dr. Javier Peñafiel-Tomás (ICMAT)",
            "organizer": "Prof. Maria Colombo",
            "contact": "Prof. Maria Colombo",
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        },
        {
            "id": 70951,
            "title": "Toward Intelligent Behavior in Macroscopic Active Matter",
            "slug": "toward-intelligent-behavior-in-macroscopic-active",
            "event_url": "https://memento.epfl.ch/event/toward-intelligent-behavior-in-macroscopic-active",
            "visual_url": "https://memento.epfl.ch/image/32339/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-07-06",
            "end_date": "2026-07-10",
            "start_time": null,
            "end_time": null,
            "description": "<p>You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: <a href=\"https://www.cecam.org/workshop-details/toward-intelligent-behavior-in-macroscopic-active-matter-1481\">https://www.cecam.org/workshop-details/toward-intelligent-behavior-in-macroscopic-active-matter-1481</a>.<br>\r\n<br>\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any).  However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the <a href=\"mailto:[email protected]\">CECAM Event Manager</a> if you have any question.<br>\r\n<br>\r\n<strong>Description</strong><br>\r\n<br>\r\nActive matter has emerged as a central framework for understanding systems composed of self-driven units across scales, ranging from molecular motors and cytoskeletal filaments to animal groups and robotic swarms. Initially, many foundational models focused on macroscopic agents – such as flocks, swarms, and driven granular particles – where simple interaction rules give rise to rich collective phenomena. However, over the past two decades, much of the focus has shifted toward microscopic and mesoscopic active systems, especially in soft and biological matter, supported by the technological development of high-resolution imaging, force measurement, and microfabrication. These advances have driven a more refined theoretical understanding, connecting microscopic dynamics with hydrodynamic and continuum-scale descriptions, and have found applications in biophysics, material science, and cellular biology. <br>\r\nIn parallel, yet often semi-independently, active matter concepts have flourished in ecological and robotic systems. In these domains, the agents – be they insects, birds, autonomous vehicles, or soft robots – not only self-propel and interact, but also sense their environments, make decisions, and adapt their behavior. These systems extend the classical framework of active matter by incorporating elements of intelligence, information processing, and environmental feedback. Notably, such systems can operate far from equilibrium and exhibit coordinated behavior that seems tuned for functional outcomes – navigation, foraging, or collective decision-making.<br>\r\nThese trends point toward a convergence: macroscopic active matter systems capable of intelligent, adaptive, or programmable behavior. This includes both natural systems (e.g., flocking insects, social insects, animal herds) and artificial systems (e.g., modular robots, programmable matter, active granular agents). The interplay of self-propulsion, interaction rules, information exchange, learning or memory, and system-level feedback opens exciting new directions for both fundamental science and applications. Recent efforts in this space combine techniques from statistical physics, nonlinear dynamics, robotics, and machine learning.<br>\r\nHowever, the communities working on these different aspects of active matter – soft matter physicists, ecologists, roboticists, and complexity scientists – remain fragmented, with limited opportunity for sustained dialogue. Bridging these communities is essential to develop a shared language, identify unifying principles, and guide the development of new experimental platforms and theoretical frameworks.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1038/s41586-024-08514-6\" target=\"_blank\">[1] F. Gu, B. Guiselin, N. Bain, I. Zuriguel, D. Bartolo, Nature, <strong>638</strong>, 112-119 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1126/scirobotics.aav7874\" target=\"_blank\">[2] A. Rafsanjani, K. Bertoldi, A. Studart, Sci. Robot., <strong>4</strong>, (2019)</a><br>\r\n<a href=\"https://doi.org/10.34133/cbsystems.0301\" target=\"_blank\">[3] J. Tirado, A. Parvaresh, B. Seyidoğlu, D. Bedford, J. Jørgensen, A. Rafsanjani, Cyborg. Bionic. Syst., <strong>6</strong>, (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s42254-021-00406-2\" target=\"_blank\">[4] J. O’Byrne, Y. Kafri, J. Tailleur, F. van Wijland, Nat. Rev. Phys., <strong>4</strong>, 167-183 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41567-022-01704-x\" target=\"_blank\">[5] P. Baconnier, D. Shohat, C. López, C. Coulais, V. Démery, G. Düring, O. Dauchot, Nat. Phys., <strong>18</strong>, 1234-1239 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41567-023-02028-0\" target=\"_blank\">[6] A. Cavagna, L. Di Carlo, I. Giardina, T. Grigera, S. Melillo, L. Parisi, G. Pisegna, M. Scandolo, Nat. Phys., <strong>19</strong>, 1043-1049 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1155/2013/987549\" target=\"_blank\">[7] M. Bischof, E. 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