retrieve:
Return the details about the given Event id.

list:
List all Event objects.

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Content-Type: application/json
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            "title": "Project Management [CAS Management in Life Sciences 2026]",
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            "description": "<strong>Module 7: Project Management </strong><br>\r\n<br>\r\nDevice and drug development is a long, complex, and demanding process. In this module we examine how a project management approach, with thorough planning, identification of milestones, stakeholder management and the development of precise objectives all contribute to project success.<br>\r\n<br>\r\n*************<br>\r\n<br>\r\n<strong><u>About the CAS Managament in Life Sciences:</u><br>\r\nLeading multi-disciplinary projects in BioTech, MedTech and Pharma</strong><br>\r\n<br>\r\nThe world of therapeutic development is becoming increasingly complex. Competition is diversifying and innovating across industries, just as new regulations and multi-stakeholder engagements disrupt the competitive landscape. Challenge or opportunity? It is up to you!<br>\r\n<br>\r\nThis program explores the entire development process of therapeutic interventions, from initial planning all the way to commercialization, allowing our participants to deepen their expertise. They also learn the leadership qualities and management tools required to lead multi-disciplinary projects in Biotech, Medtech and Pharma ventures.<br>\r\n<br>\r\nThis Certificate of Advanced Studies (CAS) runs every year, from January to June at the EPFL Campus in Lausanne.\r\n<ul>\r\n\t<li>7 modules</li>\r\n\t<li>Flexible format</li>\r\n\t<li>Part-time</li>\r\n</ul>",
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            "id": 71650,
            "title": "Approximation Complexity of QMA-hard Optimization Problems",
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            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Nicolas Macris<br>\r\nThesis advisor: Prof. Thomas Vidick<br>\r\nCo-examiner: Prof. Yihui Quek<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u>\r\n<ul>\r\n\t<li>Relations between average case complexity and approximation complexity (<a href=\"https://dl.acm.org/doi/abs/10.1145/509907.509985\">https://dl.acm.org/doi/abs/10.1145/509907.509985</a>)</li>\r\n\t<li>Efficient algorithm for a quantum analogue of 2-SAT (<a href=\"https://arxiv.org/abs/quant-ph/0602108\">https://arxiv.org/abs/quant-ph/0602108</a>) </li>\r\n\t<li>An Approximation Algorithm for the MAX-2-Local Hamiltonian Problem (<a href=\"https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2020.59\">https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2020.59</a>)</li>\r\n</ul>",
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            "description": "<p>Le self-leadership est un processus qui permet à une personne d’être plus à l’aise avec qui elle est, et qui l’amène à développer son potentiel et à construire une fondation solide à partir de laquelle toute décision – tant au niveau professionnel que personnel – peut être prise sereinement. Un bon niveau de self-leadership permet de s’épanouir à la fois dans sa propre personnalité et dans ses relations avec les autres, d’atteindre ses objectifs, et finalement, d’être un meilleur leader pour les autres.<br>\r\n<br>\r\nComment cet atelier peut vous aider: Les 3 piliers du self-leadership seront approfondis : la conscience de soi, la confiance en soi et la gestion de soi. En parallèle, ce séminaire encourage un espace de réflexion et de partage, dans lequel idées et stratégies sont échangées avec d’autres participant·e·s sur comment faire face et réussir dans des situations professionnelles souvent complexes et difficiles.<br>\r\n<br>\r\nJours 1 et 2 : 9h00 - 17h30<br>\r\nJour 3: 9h00 - 12h30</p>",
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            "title": "Complex Fluids at Interfaces: Structure, Stability, and Molecular Effects",
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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/complex-fluids-at-interfaces-structure-stability-and-molecular-effects-1492\">https://www.cecam.org/workshop-details/complex-fluids-at-interfaces-structure-stability-and-molecular-effects-1492</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\nComplex fluids are ubiquitous in biology, geophysics, and industry [1]. These materials are challenging to characterize and predict [1–4], particularly when they incorporate multiple interfaces, as in colloidal suspensions [4], foams [5–7], or nanoporous membranes [8–10]. Many of these interfaces are micro- or nano-scale and evolve over short times, which can obscure them to observation and pose challenges to experimentalists [2–5, 11, 12]. This opens exciting opportunities for a strong partnership between the development of novel theoretical, computational, and experimental techniques.<br>\r\nProbing interfaces presents unique challenges compared to probing complex fluids in the bulk. The interfacial structure and constitutive behavior then depend on the composition of two fluids as well as the interfacial configuration [13, 14]. Translating this increased complexity to a computational framework involves developing reliable models describing molecular interactions near fluid-fluid or fluid-solid interfaces [15–17], as well as models for continuum stresses [18]. Molecular modeling is necessary to reveal the physics of chemically-complex structures [17], but is computationally expensive, and it can be challenging to identify the relevant physics to include [19]. Yet the interface also provides unique opportunities for control: in liquid crystals, for example, interfacial stresses can be transmitted through the bulk, leading to novel pattern formation [20] and optical materials exploiting interfacial control [21]. Finally, interfaces are prone to instabilities, which can make flows unpredictable, but opens opportunities to exploit unstable growth for spontaneous patterning.<br>\r\nTo underscore the present challenges, even for a “simple” Newtonian fluid, the presence of an interface may hinder understanding of flow mechanics. For example, mechanisms for contact during drop impact are still debated [22]: molecular dynamics (MD) simulations can clarify which effects dominate among interfacial instabilities, electrostatic charge, gas-kinetic effects, and other driving forces [22–26], in addition to liquid/surface chemistry [27, 28]. Diffusive processes at interfaces [29] and nanoscale membrane flows, where osmotic and phoretic effects are significant [11, 30], also require further development in MD or coarse-grained models.<br>\r\n <br>\r\n<strong>This workshop aims to foster exchanges around the following </strong><strong>broad questions:</strong>\r\n</p><ul>\r\n\t<li>How do <strong>molecular phenomena</strong><strong> </strong>determine the <strong>structural properties and interfacial dynamics </strong>of complex fluid interfaces?</li>\r\n\t<li>How do we approach <strong>a rigorous, robust, and predictive upscaling </strong>between non-continuum computational approaches (e.g. MD, coarse-grained models), which are computationally costly, and large-scale systems? Can we extract universal quantities or concepts from MD to be used in a continuum model? Are these potential quantities intrinsic properties or do they depend on the flow configuration and hence require an ad hoc calibration for each flow situation?</li>\r\n\t<li><strong>How can emerging experimental and computational techniques inform our understanding of </strong><strong>interfacial instabilities in complex fluids? </strong>Can we account for instabilities arising from molecular and meso-scales in a macroscopic stability analysis?</li>\r\n\t<li>Is it possible to <strong>incorporate microscopic effects into macroscopic models </strong>which 'go beyond' the conventional Navier-Stokes-Fourier paradigm? For example, can effective viscosities adequately account for molecular effects, or can noise terms incorporate thermal fluctuations? Can these models be captured by extending existing computational approaches, or do they require entirely new frameworks?</li>\r\n</ul>\r\n<strong>The list of confirmed speakers will be announced in February. </strong>In addition, a limited number of abstracts may be submitted for the poster session – submissions will open in February.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1021/acs.langmuir.3c03727\" target=\"_blank\">[1] L. Veldscholte, J. Snoeijer, W. den Otter, S. de Beer, Langmuir, <strong>40</strong>, 4401-4409 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1017/jfm.2023.659\" target=\"_blank\">[2] G. Zampogna, P. Ledda, K. Wittkowski, F. Gallaire, J. Fluid Mech., <strong>970</strong>, A39 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.134.054001\" target=\"_blank\">[3] A. Carbonaro, G. Savorana, L. Cipelletti, R. Govindarajan, D. Truzzolillo, Phys. Rev. Lett., <strong>134</strong>, 054001 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1002/adma.202502173\" target=\"_blank\">[4] L. Buonaiuto, S. Reuvekamp, B. Shakhayeva, E. Liu, F. Neuhaus, B. Braunschweig, S. de Beer, F. Mugele, Advanced Materials, <strong>37</strong>, (2025)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpcb.4c02513\" target=\"_blank\">[5] J. Sun, L. Li, R. Zhang, H. Jing, R. Hao, Z. Li, Q. Xiao, L. Zhang, J. Phys. Chem. B, <strong>128</strong>, 7871-7881 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1063/5.0205314\" target=\"_blank\">[6] H. Liu, J. Zhang, Physics of Fluids, <strong>36</strong>, (2024)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.131.164001\" target=\"_blank\">[7] S. Perumanath, M. Chubynsky, R. Pillai, M. Borg, J. Sprittles, Phys. Rev. Lett., <strong>131</strong>, 164001 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.134.134001\" target=\"_blank\">[8] F. Yu, A. Ratschow, R. Tao, X. Li, Y. Jin, J. Wang, Z. Wang, Phys. Rev. Lett., <strong>134</strong>, 134001 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevfluids.8.103602\" target=\"_blank\">[9] R. Kaviani, J. Kolinski, Phys. Rev. Fluids, <strong>8</strong>, 103602 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-fluid-121021-021121\" target=\"_blank\">[10] J. Sprittles, Annu. Rev. Fluid Mech., <strong>56</strong>, 91-118 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41377-022-00930-5\" target=\"_blank\">[11] L. Ma, C. Li, J. Pan, Y. Ji, C. Jiang, R. Zheng, Z. Wang, Y. Wang, B. Li, Y. Lu, Light. Sci. Appl., <strong>11</strong>, 270 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-023-43978-6\" target=\"_blank\">[12] Q. Zhang, W. Wang, S. Zhou, R. Zhang, I. Bischofberger, Nat. Commun., <strong>15</strong>, 7 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1039/d4cc01557f\" target=\"_blank\">[13] R. Ishraaq, S. Das, Chem. Commun., <strong>60</strong>, 6093-6129 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-fluid-122316-045034\" target=\"_blank\">[14] S. Popinet, Annu. Rev. Fluid Mech., <strong>50</strong>, 49-75 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1039/d4cp02128b\" target=\"_blank\">[15] L. Smook, R. Ishraaq, T. Akash, S. de Beer, S. Das, Phys. Chem. Chem. Phys., <strong>26</strong>, 25557-25566 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-fluid-031821-104935\" target=\"_blank\">[16] R. Ewoldt, C. Saengow, Annu. Rev. Fluid Mech., <strong>54</strong>, 413-441 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1021/acsmacrolett.7b00812\" target=\"_blank\">[17] H. Liang, Z. Cao, Z. Wang, A. Dobrynin, ACS Macro Lett., <strong>7</strong>, 116-121 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-017-00636-y\" target=\"_blank\">[18] Q. Xu, K. Jensen, R. Boltyanskiy, R. Sarfati, R. Style, E. Dufresne, Nat. Commun., <strong>8</strong>, 555 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1103/physreve.111.055103\" target=\"_blank\">[19] A. Fukushima, S. Oyagi, T. Tokumasu, Phys. Rev. E, <strong>111</strong>, 055103 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1088/1361-6501/ad66f9\" target=\"_blank\">[20] K. Jorissen, L. Veldscholte, M. Odijk, S. de Beer, Meas. Sci. Technol., <strong>35</strong>, 115501 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1073/pnas.2221304120\" target=\"_blank\">[21] A. Allemand, M. Zhao, O. Vincent, R. Fulcrand, L. Joly, C. Ybert, A. Biance, Proc. Natl. Acad. Sci. U.S.A., <strong>120</strong>, (2023)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-fluid-071320-095958\" target=\"_blank\">[22] N. Kavokine, R. Netz, L. Bocquet, Annu. Rev. Fluid Mech., <strong>53</strong>, 377-410 (2021)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41563-020-0625-8\" target=\"_blank\">[23] L. Bocquet, Nat. Mater., <strong>19</strong>, 254-256 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1126/science.aan2438\" target=\"_blank\">[24] R. Tunuguntla, R. Henley, Y. Yao, T. Pham, M. Wanunu, A. Noy, Science, <strong>357</strong>, 792-796 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1073/pnas.1705181114\" target=\"_blank\">[25] P. Beltramo, M. Gupta, A. Alicke, I. Liascukiene, D. Gunes, C. Baroud, J. Vermant, Proc. Natl. Acad. Sci. U.S.A., <strong>114</strong>, 10373-10378 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.133.088202\" target=\"_blank\">[26] C. Guidolin, E. Rio, R. Cerbino, F. Giavazzi, A. Salonen, Phys. Rev. Lett., <strong>133</strong>, 088202 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1017/jfm.2021.529\" target=\"_blank\">[27] A. Bussonnière, I. Cantat, J. Fluid Mech., <strong>922</strong>, A25 (2021)</a><br>\r\n<a href=\"https://doi.org/10.1103/physreve.95.030602\" target=\"_blank\">[28] L. Oyarte Gálvez, S. de Beer, D. van der Meer, A. Pons, Phys. Rev. E, <strong>95</strong>, 030602 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.macromol.4c01604\" target=\"_blank\">[29] V. Calabrese, A. Shen, S. Haward, Macromolecules, <strong>57</strong>, 9668-9676 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1073/pnas.2211347120\" target=\"_blank\">[30] M. Kumar, J. Guasto, A. Ardekani, Proc. Natl. Acad. Sci. U.S.A., <strong>120</strong>, (2023)</a><br>\r\n ",
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        {
            "id": 71174,
            "title": "Schneggenburger & Herzog Labs",
            "slug": "schneggenburger-herzog-labs",
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            "description": "<em>Hybrid - By invitation only</em><br>\r\n<br>\r\nSchneggenburger Lab: Elena Mombelli<br>\r\nTitle: TBD<br>\r\n&amp;<br>\r\nHerzog Lab: Martina Morea<br>\r\nTitle: Seeing Comes After Grouping: How the Brain Builds Visual Perception",
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            "description": "<strong>Title</strong>: <br>\r\nPositive random walks and positive-semidefinite random matrices<br>\r\n<br>\r\n<strong>Abstract</strong>:<br>\r\nOn the real line, a random walk that can only move in the positive direction is very unlikely to remain close to its origin. After a fixed number of steps, the left tail has a Gaussian profile under minimal assumptions. Remarkably, a similar phenomenon occurs when we consider a positive random walk on the cone of positive-semidefinite matrices. After a fixed number of steps, the minimum eigenvalue is described by a Gaussian random matrix model.<br>\r\nThis talk introduces a new way to make this intuition rigorous. The methodology addresses an open problem in computational mathematics about sparse random embeddings. The presentation targets a general mathematical audience.<br>\r\nPreprint: <a href=\"https://arxiv.org/abs/2501.16578\" target=\"_blank\">https://arxiv.org/abs/2501.16578</a><br>\r\n<br>\r\n<strong>Please register on the following form : </strong>https://forms.gle/ppXwKo9HmTgFk3rc7",
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            "creation_date": "2026-04-01T11:03:30",
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            "id": 71586,
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            "description": "<div class=\"elementToProof\"><a href=\"https://docs.google.com/forms/d/e/1FAIpQLScPv1jP72ScE3HcMHFH_k8gQW23odk_Lk-v5K_3Hlnzj9sZ4g/viewform?usp=publish-editor\">Registration</a>\r\n<div class=\"elementToProof\">This workshop will introduce participants to the open-source Python-based viewer Napari designed for interactive visualization and analysis of large, multidimensional scientific data.</div>\r\n\r\n<div class=\"elementToProof\"> </div>\r\n\r\n<div class=\"elementToProof\">Napari enables real-time exploration and navigation of a wide range of n-dimensional, multimodal datasets (e.g 2D/3D images, time series, multichannel/hyperspectral data, as well as tracks, vectors, meshes, etc). Its plugin ecosystem and Python API make it highly extensible and well-suited for custom, reproducible analysis workflows.</div>\r\n\r\n<div class=\"elementToProof\"> </div>\r\n\r\n<div>Participants will learn how to use Napari to explore, annotate, and analyze data. The workshop begins with a brief introduction on basic concepts of 3D visualization, followed by an overview of the key features of the Napari viewer. We will then present how the viewer can be controlled programmatically as a Python object, then provide a short introduction to developing custom Napari plugins.</div>\r\n</div>",
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            "id": 71750,
            "title": "Efficiency Datalog Engine for Formal Research",
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            "start_time": "10:00:00",
            "end_time": "12:00:00",
            "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Martin Odersky<br>\r\nThesis advisor: Prof. Christoph Koch<br>\r\nCo-examiner: Prof. Viktor Kuncak<br>\r\n<br>\r\n<u>Abstract</u><br>\r\nDatalog engines are starting to show their potential in a wide range of data-intensive applications. This thesis will investigate techniques for developing a fast Datalog engines, specifically focusing on datalog program rewriting and cost-based optimization for recursive queries. Furthermore, I will explore how Datalog can be specialized for specific tasks, such as static program analysis.<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon",
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            "creation_date": "2026-04-29T09:25:41",
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            "id": 71932,
            "title": "Failure-Aware LLM Serving for Agentic Workloads",
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            "event_url": "https://memento.epfl.ch/event/failure-aware-llm-serving-for-agentic-workloads",
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            "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>",
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            "speaker": "Palak",
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            "keywords": "EDIC candidacy exam",
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        {
            "id": 70698,
            "title": "SUPER SANDWICH SEMINAR",
            "slug": "super-sandwich-seminar-361",
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            "start_date": "2026-06-18",
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            "start_time": "12:00:00",
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            "description": "<p>Triple S (Super Sandwich Seminar) will feature 3 speakers per week, each presenting for 15 minutes, followed by a 5 minutes Q&amp;A session.</p>",
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            "creation_date": "2025-12-16T15:56:43",
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            "speaker": "Yves Paychère -<em> Naef Lab; </em>Steffen Sonnentag, <em>Radtke Lab</em>; Kiruthika Kuma, <em>Antanasijevic Lab</em>",
            "organizer": "Prof. Pierre Gönczy",
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