retrieve:
Return the details about the given Memento id.

list:
List all Memento objects.

GET /api/v1/mementos/5/events/?format=api&offset=10
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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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>",
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            "creation_date": "2026-03-02T09:46:57",
            "last_modification_date": "2026-03-02T09:50:51",
            "link_label": "",
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            "speaker": "Sam Allen, KIT",
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            "id": 71498,
            "title": "From Helical Motifs to Oral Drugs: Design Principles for Bioavailable Macrocyclic Peptides",
            "slug": "from-helical-motifs-to-oral-drugs-design-principle",
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            "start_date": "2026-04-20",
            "end_date": "2026-04-20",
            "start_time": "14:15:00",
            "end_time": "15:15:00",
            "description": "<p>In this seminar, I will discuss our efforts to design conformationally constrained helical macrocyclic peptides and outline the principles that enable effective targeting of protein–protein interactions beyond classical stapled peptides. In the second part, I will show how a subtle isosteric backbone modification—thioamidation—can be used to impart oral bioavailability to bioactive macrocyclic peptides. I will further illustrate how conformational restriction enhances membrane permeability and highlight the critical role of metabolic stability in achieving oral bioavailability.</p>",
            "image_description": "Prof. Jayanta Chatterjee",
            "creation_date": "2026-03-30T19:14:23",
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            "speaker": "Prof. Jayanta Chatterjee, Indian Institute of Science, Bangalore, India",
            "organizer": "C. Heinis",
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            "id": 70900,
            "title": "FAIR Data Management of Theoretical Spectroscopy and Green’s Function Methods",
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            "start_date": "2026-04-20",
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            "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/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377\">https://www.cecam.org/workshop-details/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377</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\nBig-data-driven methodologies have emerged as a fundamental paradigm of science, but require an enormous amount of resources to achieve their promised impact. The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles [1] ensure that scientific data can be shared and reutilized, providing an efficient route for accumulating data and taking advantage of these powerful techniques. FAIR data management allows essential knowledge to be systematically extracted from data, accelerating discoveries and innovations across various domains [2]. Furthermore, open science is essential for the verifiability and reproducibility of results and has been a topic of major discussion over the last decade. In materials science, data-driven methodologies, coupled with the appropriate FAIR data management practices, are invaluable for the discovery of new materials due to the vast combinatorial space of chemical systems that emerge from the periodic table [3, 4]. Such methodologies have been successfully applied, e.g., to design and predict new materials with desired properties using ab-initio ground state simulations, i.e., data generated from Density Functional Theory (DFT) calculations [5]. However, there remains a critical gap in replicating this success in the context of other simulation frameworks. <br>\r\nTheoretical spectroscopy and Green's function method simulations [6, 7], including data simulated using the GW approximation, Time-Dependent Density Functional Theory (TDDFT), the Bethe-Salpeter equation (BSE), Dynamical Mean-Field Theory (DMFT), and Korringa-Kohn-Rostoker (KKR), pose especially difficult challenges in the context of FAIR data management. These simulations not only involve extensive computational resources and produce large datasets with associated complex workflows but are also executed using a large variety of public and in-house simulation software. At the same time, these methodologies are essential for understanding excited state properties of complex materials; they are more accurate than DFT calculations and provide better comparisons with experimental results since they incorporate excited states and electronic correlation effects in a more consistent manner [8]. <br>\r\nThere has recently been a number of individual efforts to improve the accessibility of  data produced by theoretical spectroscopy and Green’s function methods through the usage of publicly accessible databases. For example, the Computational Materials Repository (CMR) [9] contains several individual databases, amongst which the Computational 2D Materials Database (C2DB) [10] contains GW and BSE data for a specific set of parameters and properties. The MaterialsCloud [11] database has some individual datasets published for these methodologies, however there is not a clear data structure for them. The NIST-JARVIS [12] database has a specific app for BeyondDFT simulations with DMFT data, but only for a specific simulation code. By making datasets findable, these efforts aim to avoid redundant computations and thus build upon existing work more efficiently. While these efforts represent an important step in the right direction, they fall short of fully achieving their goal due to a continued lack of consistency (i.e., <em>interoperability</em>) between individual databases. Moreover, these self-managed databases typically lack the ability to store the complete provenance of the simulated workflow, which is essential to ensure reproducibility. <br>\r\nRecently, FAIRmat [13], a consortium of the German research data infrastructure (NFDI) association, was formed to construct a scalable data infrastructure for Materials Science that can be easily customized for individual communities. This infrastructure consists of a primary software and repository called NOMAD [14]—a free web-service that enables the organization, analysis, sharing, and publishing of materials science data. One of the tasks within FAIRmat’s scope is to build support for theoretical spectroscopy and Green’s function simulations within NOMAD. Support for several of these methodologies have now been successfully built, and there already exists over 10 000 entries in the NOMAD repository containing GW [15], BSE [16], and DMFT [17] data, along with the full provenance of the corresponding complex workflows. The next step to developing a FAIR data infrastructure for these methods is to tackle the interoperability problem.<br>\r\nInteroperability within this domain is extremely challenging due to the heterogeneous character of theoretical spectroscopy and Green’s function simulations. Consequently, the adoption of common structures (e.g., describing the Green’s function, the self-energy, or the dielectric function) is the key for improving interoperability. Thus, various members of the community, including method developers, materials and data scientists, and data management experts, must come together to reach a consensus on specific common data structures.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://cmr.fysik.dtu.dk/\" target=\"_blank\">[1] Computational Materials Repository (CMR) website</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41467-024-48169-5\" target=\"_blank\">[2] S. Di Cataldo, P. Worm, J. Tomczak, L. Si, K. Held, Nat. Commun., <strong>15</strong>, 3952 (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1103/physrevmaterials.8.013801\" target=\"_blank\">[3] F. Meng, B. Maurer, F. Peschel, S. Selcuk, M. Hybertsen, X. Qu, C. Vorwerk, C. Draxl, J. Vinson, D. Lu, Phys. Rev. Materials, <strong>8</strong>, 013801 (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1021/acs.jctc.5b00453\" target=\"_blank\">[4] M. van Setten, F. Caruso, S. Sharifzadeh, X. Ren, M. Scheffler, F. Liu, J. Lischner, L. Lin, J. Deslippe, S. Louie, C. Yang, F. Weigend, J. Neaton, F. Evers, P. Rinke, J. Chem. Theory Comput., <strong>11</strong>, 5665-5687 (2015)</a><br>\r\n<a href=\"http://dx.doi.org/10.21105/joss.05388\" target=\"_blank\">[5] M. Scheidgen, L. Himanen, A. Ladines, D. Sikter, M. Nakhaee, Á. Fekete, T. Chang, A. Golparvar, J. Márquez, S. Brockhauser, S. Brückner, L. Ghiringhelli, F. Dietrich, D. Lehmberg, T. Denell, A. Albino, H. Näsström, S. Shabih, F. Dobener, M. Kühbach, R. Mozumder, J. Rudzinski, N. Daelman, J. Pizarro, M. Kuban, C. Salazar, P. Ondračka, H. Bungartz, C. Draxl, JOSS., <strong>8</strong>, 5388 (2023)</a><br>\r\n<a href=\"https://www.fairmat-nfdi.eu/fairmat/\" target=\"_blank\">[6] FAIRmat website</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41524-020-00440-1\" target=\"_blank\">[7] K. Choudhary, K. Garrity, A. Reid, B. DeCost, A. Biacchi, A. Hight Walker, Z. Trautt, J. Hattrick-Simpers, A. Kusne, A. Centrone, A. Davydov, J. Jiang, R. Pachter, G. Cheon, E. Reed, A. Agrawal, X. Qian, V. Sharma, H. Zhuang, S. Kalinin, B. Sumpter, G. Pilania, P. Acar, S. Mandal, K. Haule, D. Vanderbilt, K. Rabe, F. Tavazza, npj. Comput. Mater., <strong>6</strong>, 173 (2020)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41597-020-00637-5\" target=\"_blank\">[8] L. Talirz, S. Kumbhar, E. Passaro, A. Yakutovich, V. Granata, F. Gargiulo, M. Borelli, M. Uhrin, S. Huber, S. Zoupanos, C. Adorf, C. Andersen, O. Schütt, C. Pignedoli, D. Passerone, J. VandeVondele, T. Schulthess, B. Smit, G. Pizzi, N. Marzari, Sci. Data., <strong>7</strong>, 299 (2020)</a><br>\r\n<a href=\"http://dx.doi.org/10.1088/2053-1583/aacfc1\" target=\"_blank\">[9] S. Haastrup, M. Strange, M. Pandey, T. Deilmann, P. Schmidt, N. Hinsche, M. Gjerding, D. Torelli, P. Larsen, A. Riis-Jensen, J. Gath, K. Jacobsen, J. Jørgen Mortensen, T. Olsen, K. Thygesen, 2D Mater., <strong>5</strong>, 042002 (2018)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/sdata.2016.18\" target=\"_blank\">[10] M. Wilkinson, M. Dumontier, I. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, L. da Silva Santos, P. Bourne, J. Bouwman, A. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C. Evelo, R. Finkers, A. Gonzalez-Beltran, A. Gray, P. Groth, C. Goble, J. Grethe, J. Heringa, P. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S. Lusher, M. Martone, A. Mons, A. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, Sci. Data., <strong>3</strong>, 160018 (2016)</a><br>\r\n<a href=\"https://www.sciencedirect.com/journal/comptes-rendus-physique/vol/10/issue/6\" target=\"_blank\">[11] L. Reining et al., Comptes Rendus Physique 10, 6 (2009)</a><br>\r\n<a href=\"http://dx.doi.org/10.1088/2516-1075/ad48ec\" target=\"_blank\">[12] V. Blum, R. Asahi, J. Autschbach, C. Bannwarth, G. Bihlmayer, S. Blügel, L. Burns, T. Crawford, W. Dawson, W. de Jong, C. Draxl, C. Filippi, L. Genovese, P. Giannozzi, N. Govind, S. Hammes-Schiffer, J. Hammond, B. Hourahine, A. Jain, Y. Kanai, P. Kent, A. Larsen, S. Lehtola, X. Li, R. Lindh, S. Maeda, N. Makri, J. Moussa, T. Nakajima, J. Nash, M. Oliveira, P. Patel, G. Pizzi, G. Pourtois, B. Pritchard, E. Rabani, M. Reiher, L. Reining, X. Ren, M. Rossi, H. Schlegel, N. Seriani, L. Slipchenko, A. Thom, E. Valeev, B. Van Troeye, L. Visscher, V. Vlcek, H. Werner, D. Williams-Young, T. Windus, Electron. Struct., (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41597-023-02501-8\" target=\"_blank\">[13] L. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. Koch, M. Kühbach, A. Ladines, P. Lambrix, M. Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, M. Scheffler, Sci. Data., <strong>10</strong>, 626 (2023)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41524-019-0221-0\" target=\"_blank\">[14] J. Schmidt, M. Marques, S. Botti, M. Marques, npj. Comput. Mater., <strong>5</strong>, 83 (2019)</a><br>\r\n<a href=\"http://dx.doi.org/10.1002/advs.201900808\" target=\"_blank\">[15] L. Himanen, A. Geurts, A. Foster, P. Rinke, Advanced Science, <strong>6</strong>, (2019)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41586-022-04501-x\" target=\"_blank\">[16] M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H. Bungartz, C. Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. Nagel, M. Scheidgen, C. Wöll, C. Draxl, Nature, <strong>604</strong>, 635-642 (2022)</a><br>\r\n<a href=\"http://dx.doi.org/10.1557/mrs.2018.208\" target=\"_blank\">[17] C. Draxl, M. Scheffler, MRS Bull., <strong>43</strong>, 676-682 (2018)</a></p>",
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            "link_label": "FAIR Data Management of Theoretical Spectroscopy and Green’s Function Methods",
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            "contact": "<a href=\"mailto:[email protected]\"><strong>Cornelia Bujenita</strong></a>, CECAM Events and Operations Manager",
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        {
            "id": 71426,
            "title": "7T MRI Seminar: Leveraging the potential of UHF scanners for fMRI studies",
            "slug": "7t-mri-seminar-leveraging-the-potential-of-uhf-sca",
            "event_url": "https://memento.epfl.ch/event/7t-mri-seminar-leveraging-the-potential-of-uhf-sca",
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            "lang": "en",
            "start_date": "2026-04-21",
            "end_date": "2026-04-21",
            "start_time": "10:00:00",
            "end_time": "11:30:00",
            "description": "<p>Hosted by <a href=\"https://cibm.ch/community/frederic-grouiller/\">Frédéric Grouiller</a>, CIBM MRI HUG-UNIGE Section head, we are pleased  to invite you to attend the CIBM 7T MRI Seminar on April 21st at 10:00 CEST by Caroline Le Ster from the CEA Neurospin, Paris who will be sharing on<strong> “Leveraging the potential of UHF scanners for fMRI studies”.<br>\r\nAbstract</strong><br>\r\nThere is a growing availability of 7T scanners, with approximately 100 systems currently installed worldwide. These ultra-high-filed (UHF) scanners are particularly relevant for neuroimaging, where anatomical and functional images can be acquired with higher spatial and temporal resolution than on conventional scanners. However, UHF scanners remain difficult to operate, and understanding their specific limitations is essential. These systems indeed face several challenges arising from MR physics and biological effects that must be addressed within engineering constraints. Leverage the potential of UHF scanners, for instance through field monitoring, is therefore important to make the most of these scanners and benefit from the intrinsic SNR gain.<br>\r\nfMRI particularly benefits from the increase in magnetic field strength, enabling studies to be performed at higher resolution than at lower fields. In order to maintain reasonable acquisition times despite larger imaging matrices, several acceleration strategies have been developed, e.g. multi-slice EPI (SMS-EPI), three-dimensional EPI (3D-EPI) and non-Cartesian sampling schemes. In addition, functional contrasts also benefit from the field increase, including improved spatial localization of the BOLD contrast and the possibility to exploit VASO contrast.</p>",
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            "creation_date": "2026-03-23T10:36:15",
            "last_modification_date": "2026-03-23T10:39:08",
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            "speaker": "<strong>Caroline Le Ster</strong>, CEA Neurospin, Paris, France",
            "organizer": "<a href=\"https://cibm.ch\">CIBM Center for Biomedical Imaging</a>",
            "contact": "<strong>Miguel Molina</strong>, CIBM Media &amp; Events Manager",
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            "keywords": "7T MRI scanner, fMRI, UHF, Biomedical imaging",
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        },
        {
            "id": 71319,
            "title": "Uniform dimension results of level-sets of stable sheets",
            "slug": "uniform-dimension-results-of-level-sets-of-stabl-2",
            "event_url": "https://memento.epfl.ch/event/uniform-dimension-results-of-level-sets-of-stabl-2",
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            "start_date": "2026-04-21",
            "end_date": "2026-04-21",
            "start_time": "17:00:00",
            "end_time": null,
            "description": "<p>Thesis Director: Prof. T. Mountford,<br>\r\nMathematics doctoral program<br>\r\nThesis Nr. 11211<br>\r\n<br>\r\nTo take part in the public defense, please contact directly the speaker</p>",
            "image_description": "",
            "creation_date": "2026-03-06T13:07:23",
            "last_modification_date": "2026-03-06T13:07:23",
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            "spoken_languages": [],
            "speaker": "<a href=\"mailto:[email protected]\"><strong>Keming CHEN</strong></a>",
            "organizer": "",
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            "keywords": "EDMA",
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            "category": {
                "id": 12,
                "code": "SOUTE",
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        },
        {
            "id": 71405,
            "title": "AI & Compute - Research Computing Platform (RCP) - Exchange session",
            "slug": "ai-compute-research-computing-platform-rcp-exch-26",
            "event_url": "https://memento.epfl.ch/event/ai-compute-research-computing-platform-rcp-exch-26",
            "visual_url": "https://memento.epfl.ch/image/32752/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-04-22",
            "end_date": "2026-04-22",
            "start_time": "14:00:00",
            "end_time": "15:30:00",
            "description": "<p>The<strong> <a href=\"https://ai.epfl.ch/\">EPFL AI Center </a></strong>is delighted to invite you to join the exchange session about the <strong><a href=\"https://www.epfl.ch/research/facilities/rcp/\">Research Computing Platform (RCP)</a></strong>.<br>\r\n<br>\r\nAre you building, training ML models? Are you currently facing challenges regarding IT infrastructure, and looking for reliable, collaborative, high-capacity, and affordable storage solutions to manage your research data? Are you seeking information about the computing costs? <br>\r\n<br>\r\nThe <strong><a href=\"https://www.epfl.ch/research/facilities/rcp/\">Research Computing Platform (RCP)</a></strong> offers campus-wide IT infrastructure geared for the research community. The offering includes a GPU infrastructure (&gt; 400) aiming at making AI compute as accessible as possible throughout the campus. <br>\r\n<br>\r\nThis event will provide insights into the various services RCP offers to the EPFL research community. <br>\r\n<br>\r\n<strong>Event Details:</strong>\r\n</p><ul>\r\n\t<li><strong>Date:</strong> April 22, 2026 </li>\r\n\t<li><strong>Time:</strong> 14:00-15:30</li>\r\n\t<li><strong>Location:</strong> ELE 117 - AI Center Lounge </li>\r\n\t<li><strong>Registration required, with your EPFL email address: <a href=\"https://forms.office.com/e/KvKgmVrjsh\">HERE</a></strong></li>\r\n</ul>\r\n<strong>Program</strong>\r\n\r\n<ul>\r\n\t<li><strong>14:00-14:30: Presentation of the RCP infrastructure and services</strong> <strong>(</strong>incl. storage, compute, file transfer, GPU-based service offer, HaaS…)</li>\r\n\t<li><strong>14:30-15:30: Q&amp;A and hands-on questions with the RCP team</strong></li>\r\n</ul>\r\n<em>(Refreshments provided)</em><br>\r\n<br>\r\n<strong>How It Works:</strong>\r\n\r\n<ol>\r\n\t<li><strong>Register and share some previous thoughts:</strong> Did you know about the RCP before? Are you running simulations? Have you planned computing resources in your project?</li>\r\n\t<li><strong>Bring a Laptop and your questions:</strong> the RCP team will be there to address your question based on your specific use case.</li>\r\n\t<li><strong>Discussion:</strong> gather to share your challenges, receive constructive feedback, and explore potential collaborations.</li>\r\n</ol>\r\n<br>\r\nDon’t miss this opportunity to learn how RCP can support your research endeavors. <br>\r\n<br>\r\nWe look forward to seeing you there!",
            "image_description": "",
            "creation_date": "2026-03-18T17:45:54",
            "last_modification_date": "2026-03-18T17:48:18",
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            "contact": "<a href=\"https://people.epfl.ch/nicolas.machado\">Nicolas Machado</a>",
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            "keywords": "Intelligence artificielle, Artificial intelligence, AI, Compute, Computation, Generative AI",
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        },
        {
            "id": 71283,
            "title": "TBA",
            "slug": "tba-128",
            "event_url": "https://memento.epfl.ch/event/tba-128",
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            "start_date": "2026-04-22",
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            "start_time": "14:15:00",
            "end_time": "15:15:00",
            "description": "<p>TBA<br>\r\n </p>",
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            "creation_date": "2026-03-03T09:23:22",
            "last_modification_date": "2026-03-25T12:25:59",
            "link_label": "",
            "link_url": "",
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            "speaker": "Annika Thiele, Humboldt-Universität zu Berlin",
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            "contact": "Maroussia Schaffner",
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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",
            "visual_url": "https://memento.epfl.ch/image/32831/200x112.jpg",
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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",
            "last_modification_date": "2026-03-30T09:47:45",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
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            "speaker": "Elena Botti, Vrije Universiteit Brussel (VUB)",
            "organizer": "Markus Kirolos",
            "contact": "Maroussia Schaffner",
            "is_internal": "False",
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        },
        {
            "id": 70717,
            "title": "Training \"Ethics in Research Data Management: Anonymization and Best Practices\"",
            "slug": "training-ethics-in-research-data-management-anon-4",
            "event_url": "https://memento.epfl.ch/event/training-ethics-in-research-data-management-anon-4",
            "visual_url": "https://memento.epfl.ch/image/32139/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-04-23",
            "end_date": "2026-04-23",
            "start_time": "15:00:00",
            "end_time": "16:30:00",
            "description": "<div class=\"all_text\"><strong>Ethical-driven practices in data management are crucial for maintaining research integrity, protecting privacy, and collaborate with research partners, and fostering trust in research outputs. This short training focuses on the practices of ethical data management and the adoption of anonymization techniques for compliance with data protection laws.</strong><br>\r\n<br>\r\nThrough interactive discussions and case studies, participants will learn to:<br>\r\n- Address ethical challenges in data collection and management in compliance with Swiss and European laws<br>\r\n- Understand how anonymization techniques and responsible data handling can protect subjects’ privacy<br>\r\n- Strengthen research integrity by applying best practices in everyday data management workflows.</div>\r\n<br>\r\nWith a dedicated Q&amp;A session featuring the EPFL Research Ethics Compliance Officer and Senior Legal Counsel for Education and Research, you will also have the occasion to discuss the ethical and related technical dimensions of managing your research data.\r\n<div class=\"all_text\"><br>\r\nWhile not mandatory, basic knowledge of Research Data Management is recommended: for an introductory training, please register for the workshop <a href=\"https://bookwhen.com/fr/epfl_library/e/ev-s22p-20260305150000\" target=\"_blank\">ABC of Research Data Management</a>.<br>\r\n<br>\r\n<a href=\"https://bookwhen.com/fr/epfl_library/e/ev-sbj8a-20260423150000\">Registration</a><br>\r\n<br>\r\nMore information about <a href=\"https://www.epfl.ch/campus/library/training/\">EPFL Library Teaching offer</a></div>",
            "image_description": "CC-BY-NC-SA EPFL Library",
            "creation_date": "2025-12-18T15:16:03",
            "last_modification_date": "2026-03-10T15:00:24",
            "link_label": "Registration",
            "link_url": "https://bookwhen.com/epfl_library/e/ev-sbj8a-20260423150000",
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            "speaker": "EPFL Library Research Data Team",
            "organizer": "EPFL Library",
            "contact": "[email protected]",
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                "en_label": "Registration required"
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            "keywords": "",
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        },
        {
            "id": 71338,
            "title": "Probing Ultrafast Electron Motion with Attosecond X-ray Free Electron Lasers",
            "slug": "probing-ultrafast-electron-motion-with-attosecond",
            "event_url": "https://memento.epfl.ch/event/probing-ultrafast-electron-motion-with-attosecond",
            "visual_url": "https://memento.epfl.ch/image/32692/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-04-23",
            "end_date": "2026-04-23",
            "start_time": "17:15:00",
            "end_time": "18:30:00",
            "description": "<p>The ultrafast motion of electrons is a frontier problem for photochemical processes, as electron motion is a key ingredient of all chemical reactions. Electronic rearrangement is also the means by which light energy is harnessed in photochemistry. The timescale for coherent electron dynamics is set by the energetic splitting of the electronic states, which in small molecular systems, is on the scale of an electron volt (eV). This sets the natural timescale for electronic motion to be few-to-sub femtosecond (fs).<br>\r\n<br>\r\nTo approach these extreme timescales, we can use short pulses of light to excite small quantum systems. For instance, the impulsive interactions between a light field and a quantum system can induce time-dependent oscillations in the charge density. Such electronic wavepacket motion (in the absence of nuclear motion) has come to be referred to as charge migration [1]. While the initial charge dynamics following impulsive excitation (or ionization) begins as purely electronic motion, this wavepacket will couple to other degrees of freedom in the system (i.e. nuclear motion or chemical dynamics) and lead to localization of the charge.  The transfer of electronic charge across molecular bonds is fundamental to an understanding of charge transfer phenomena.<br>\r\n<br>\r\nThe study of these fundamental phenomena requires state-of-the-art light sources, such as the Linac Coherent Light Source (LCLS), an X-ray free electron laser (XFEL) facility which produces high-brightness, ultrashort pulses, with wavelength continuously tunable across the x-ray regime. Schemes to provide isolated, sub-femtosecond pulses from an FEL are being explored at facilities world-wide, and recently we have demonstrated such pulses at the LCLS [2]; opening the door for time-resolved measurements of ultrafast electron dynamics on their natural timescale. In my talk, I will highlight our recent developments in probing electronic motion in small molecular systems. We have employed sub-femtosecond pulses from the XFEL to study ultrafast charge dynamics in both core-excited [3,4,5] and low-lying cationic systems [6]. We are also developing nonlinear x-ray spectroscopies [7,8] to initiate and control electron dynamics. The control of coherent electron motion represents a significant step towards achieving charge-directed reactivity [9], a grand challenge for the field of attosecond science.<br>\r\n<br>\r\n[1] Cederbaum and Zobeley 1999 Chemical Physics Letters 307 205–210<br>\r\n[2] Duris and Li et al. 2020 Nature Photonics 14 30-36<br>\r\n[3] Li and Driver et al. 2022 Science 375 285-290<br>\r\n[4] Driver et al. 2024 Nature 632 762-767 (2024)<br>\r\n[5] Wang and Driver et al. Phys. Rev. X 15 011008 (2005)<br>\r\n[6] Driver et al. ArXiv:2411.01700<br>\r\n[7] O’Neal et al. 2020 Phys. Rev. Lett. 125 073203<br>\r\n[8] Biggs et al. 2023 Proc. Nat. Acad. Sci. 110 15597-15601<br>\r\n[9] F. Remacle, R. D. Levine, and M. A. Ratner 1998 Chem. Phys. Lett. 285, 25<br>\r\n </p>",
            "image_description": "",
            "creation_date": "2026-03-10T09:08:13",
            "last_modification_date": "2026-03-10T09:08:45",
            "link_label": "",
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            "speaker": "James Cryan, Stanford Univ. / SLAC",
            "organizer": "Christoph Bostedt",
            "contact": "Christoph Bostedt",
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