retrieve:
Return the details about the given Memento id.

list:
List all Memento objects.

GET /api/v1/mementos/27/events/?format=api&offset=30&ordering=is_active
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "description": "<strong>// NEW DATE // This event has been rescheduled from 17 March to 9 June 2026!</strong><br>\r\n<br>\r\nHow can AI tutors be designed to support learning rather than shortcutting it?<br>\r\n<br>\r\nIn this presentation, Jérôme Brender (EPFL) will examine how undergraduate students learn with AI tutors in robotics and computer science courses.<br>\r\n<br>\r\nAcross multiple design iterations, he investigated how features such as course-grounded retrieval (RAG), Socratic questioning, and real-time prompt feedback, and debate chatbot, shape students’ engagement, prompting behavior, and learning outcomes.<br>\r\n<br>\r\nHis work focuses on how AI tutors can help students better understand course concepts and become more reflective and effective users of AI tools. The findings provide insights into designing AI tutors that foster critical thinking and support sustainable learning practices.",
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            "id": 71884,
            "title": "Inverse Rendering: From Surfaces to Continuous Formulations",
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            "description": "<p>Thesis Director: Prof. W. A. Jakob,<br>\r\nComputer and Communication Sciences doctoral program<br>\r\nThesis Nr. 11469<br>\r\n<br>\r\nTo take part in the public defense, please contact directly the speaker</p>",
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            "spoken_languages": [],
            "speaker": "Petra Arabadjieva ",
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        {
            "id": 71932,
            "title": "Failure-Aware LLM Serving for Agentic Workloads",
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            "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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        {
            "id": 71750,
            "title": "Efficiency Datalog Engine for Formal Research",
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            "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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            "id": 70949,
            "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": 71929,
            "title": "Workshop series “Responsible AI skills for education”",
            "slug": "workshop-series-responsible-ai-skills-for-educat-4",
            "event_url": "https://memento.epfl.ch/event/workshop-series-responsible-ai-skills-for-educat-4",
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            "description": "<p>Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.<br>\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.<br>\r\n<br>\r\n<strong>Teaching critical analysis:</strong><br>\r\nIn this 1-hour workshop, we will focus on how to help students develop critical analysis skills for reviewing LLM outputs in the context of learning tasks. The workshop will combine theoretical inputs and hands-on activities, drawing on your disciplinary expertise and fact-checking strategies.<br>\r\n </p>",
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