What happens when science meets illustration, journalism, writing, and visual communication?
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\r\nJoin us for the next Biotech Chats on Science Communication, organized by BSNL (BioScience Network Lausanne), and learn what career opportunities exist beyond the lab bench!
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\r\nEvent details:\r\n
What if robots didn’t replace humans, but collaborated with us?
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\r\nOn the occasion of the exhibition Do Robots Dream of Construction Sites?, on view at Archizoom from 9 September to 5 December 2026, we invite you to explore a selection of scientific and popular science books, as well as science fiction novels dedicated to human-robot interactions, a theme at the heart of the exhibition.
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\r\nThis selection offers different perspectives on robotics, automation, work, and the future forms of collaboration between humans and machines.
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\r\nAll documents can be borrowed according to the Library’s standard borrowing conditions.
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\r\nDiscover the selection at the Espace Découverte from 5 October to 7 December 2026, as well as online.
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\r\nBrowse the Library's online reading selection: go.epfl.ch/library-robots
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\r\nLearn more about the Archizoom exhibition: memento.epfl.ch/event/do-robots-dream-of-construction-sites-archizoom
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You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/from-data-to-dynamics-machine-learning-in-statistical-mechanics-and-molecular-simulations-1487.
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\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 CECAM Event Manager if you have any question.
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\r\nDescription
\r\nSince its introduction in the 1970s, molecular dynamics (MD) has become an indispensable computational microscope for studying complex biological systems at atomic resolution. It has enabled detailed investigations into protein folding, conformational dynamics, and ligand binding and unbinding. Over the past decade, increasing computational power has made microsecond-scale simulations routine, producing massive datasets that demand sophisticated analysis strategies [1]. Despite these advances, conventional MD simulations still face a fundamental limitation: many biologically relevant events occur over milliseconds to seconds—timescales largely inaccessible to standard MD.
\r\nTo bridge this gap, researchers increasingly turn to enhanced sampling techniques—such as metadynamics and umbrella sampling [2,3]—and coarse-grained (CG) modeling approaches [4]. These methods enable more comprehensive exploration of the system’s free energy landscape, yet their success critically depends on the selection of appropriate reaction coordinates or collective variables (CVs). CVs must capture the slowest, most functionally relevant motions to accurately reflect thermodynamic and kinetic behavior. However, identifying suitable CVs remains one of the field’s most challenging tasks, typically requiring domain expertise and iterative refinement [5, 6].
\r\nThis complexity has fueled growing interest in machine learning (ML) techniques, which are now transforming how MD simulations are analyzed, interpreted, and even conducted. ML methods have been applied to automate CV discovery, perform dimensionality reduction, build thermodynamic and kinetic models, and enhance sampling efficiency [7]. These models often employ artificial neural networks or graph neural networks to map high-dimensional molecular configurations—such as Cartesian coordinates or molecular descriptors—into low-dimensional representations suitable for analysis [8].
\r\nDepending on the structure and type of data, ML algorithms can be broadly categorized into supervised, unsupervised, and reinforcement learning paradigms [9]. Supervised learning uses labeled input-output pairs to predict properties such as molecular energies or binding affinities [10], while unsupervised learning enables the identification of latent features, such as CVs, directly from data [11].
\r\nA cornerstone of modern ML-driven simulation is the development of symmetry-aware molecular representations. The predictive power of ML models hinges on encoding physical symmetries—like rotation and translation—directly into the model. E(3)-equivariant neural networks have emerged as powerful tools for this purpose, significantly improving data efficiency and generalization in learning potential energy surfaces [12]. Ongoing research continues to explore the optimal balance between enforcing strict symmetry and retaining model flexibility.
\r\nMeanwhile, breakthroughs in structural prediction—most notably the advent of AlphaFold 3—have revolutionized how researchers obtain initial molecular configurations. AlphaFold now provides remarkably accurate models of not only proteins but also their complexes with nucleic acids, ions, and small-molecule ligands [13]. However, these are static snapshots. They cannot capture dynamic behaviors, allosteric transitions, or binding kinetics—areas where physics-based simulations remain indispensable. Initial benchmarks suggest that even state-of-the-art predictors still fall short in modeling protein dynamics and ranking ligand binding affinities, further emphasizing the role of MD [14].
\r\nTo address the dimensionality and sampling bottlenecks, unsupervised ML approaches such as time-lagged autoencoders have reframed CV identification as a data-driven task. More recently, generative models—including diffusion models and variational autoencoders—have emerged as a new frontier. These models can learn the full conformational landscape of biomolecules and enable enhanced sampling, in some cases eliminating the need for predefined CVs altogether [15].
\r\nOnce accurate structural models and CVs are established, ML can significantly improve the estimation of thermodynamic and kinetic properties. In drug discovery, for instance, predicting protein–ligand binding affinity remains a central challenge. ML potentials trained on quantum mechanical data can be combined with enhanced sampling to yield highly accurate free energy landscapes and binding kinetics—results previously unattainable due to computational limitations [16]. However, challenges in data quality, model interpretability, and transferability remain critical areas of ongoing investigation [17].
\r\nFinally, ML is driving a renaissance in CG modeling. Deep neural networks can now learn many-body CG potentials directly from all-atom simulations, capturing emergent properties and enhancing transferability [18]. These models open the door to longer, larger-scale simulations with greater physical accuracy.
\r\nIn this rapidly evolving context, it becomes imperative to critically assess both the promise and limitations of ML in biomolecular simulation. The excitement surrounding these developments must be tempered by careful validation and benchmarking. This workshop thus serves as a timely opportunity—especially for early-career researchers—to explore these cutting-edge methods, engage in constructive dialogue, and chart new directions in the application of machine learning to molecular dynamics and drug discovery.
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\r\nReferences
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\r\n[1] J. Behler, M. Parrinello, Phys. Rev. Lett., 98, 146401 (2007)
\r\n[2] P. Sahrmann, G. Voth, Current Opinion in Structural Biology, 90, 102972 (2025)
\r\n[3] K. Kříž, L. Schmidt, A. Andersson, M. Walz, D. van der Spoel, J. Chem. Inf. Model., 63, 412-431 (2023)
\r\n[4] K. Ahmad, A. Rizzi, R. Capelli, D. Mandelli, W. Lyu, P. Carloni, Front. Mol. Biosci., 9, (2022)
\r\n[5] S. Mehdi, Z. Smith, L. Herron, Z. Zou, P. Tiwary, Annual Review of Physical Chemistry, 75, 347-370 (2024)
\r\n[6] H. Zheng, H. Lin, A. Alade, J. Chen, E. Monroy, M. Zhang, J. Wang, AlphaFold3 in Drug Discovery: A Comprehensive Assessment of Capabilities, Limitations, and Applications, 2025
\r\n[7] J. Abramson, J. Adler, J. Dunger, R. Evans, T. Green, A. Pritzel, O. Ronneberger, L. Willmore, A. Ballard, J. Bambrick, S. Bodenstein, D. Evans, C. Hung, M. O’Neill, D. Reiman, K. Tunyasuvunakool, Z. Wu, A. Žemgulytė, E. Arvaniti, C. Beattie, O. Bertolli, A. Bridgland, A. Cherepanov, M. Congreve, A. Cowen-Rivers, A. Cowie, M. Figurnov, F. Fuchs, H. Gladman, R. Jain, Y. Khan, C. Low, K. Perlin, A. Potapenko, P. Savy, S. Singh, A. Stecula, A. Thillaisundaram, C. Tong, S. Yakneen, E. Zhong, M. Zielinski, A. Žídek, V. Bapst, P. Kohli, M. Jaderberg, D. Hassabis, J. Jumper, Nature, 630, 493-500 (2024)
\r\n[8] Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling, NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing Systems, Article No.: 166, Pages 1970 - 1981 (2020)
\r\n[9] H. Sidky, W. Chen, A. Ferguson, Molecular Physics, 118, (2020)
\r\n[10] Y. Wang, J. Lamim Ribeiro, P. Tiwary, Current Opinion in Structural Biology, 61, 139-145 (2020)
\r\n[11] K. Butler, D. Davies, H. Cartwright, O. Isayev, A. Walsh, Nature, 559, 547-555 (2018)
\r\n[12] F. Noé, A. Tkatchenko, K. Müller, C. Clementi, Annu. Rev. Phys. Chem., 71, 361-390 (2020)
\r\n[13] S. Kaptan, I. Vattulainen, Advances in Physics: X, 7, (2022)
\r\n[14] V. Limongelli, WIREs. Comput. Mol. Sci., 10, (2020)
\r\n[15] A. Glielmo, B. Husic, A. Rodriguez, C. Clementi, F. Noé, A. Laio, Chem. Rev., 121, 9722-9758 (2021)
\r\n[16] A. Pak, G. Voth, Current Opinion in Structural Biology, 52, 119-126 (2018)
\r\n[17] M. Lelimousin, V. Limongelli, M. Sansom, J. Am. Chem. Soc., 138, 10611-10622 (2016)
\r\n[18] C. Abrams, G. Bussi, Entropy, 16, 163-199 (2013)\r\n
You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/g-protein-coupled-receptors-functional-dynamics-revealed-by-experimental-and-computational-structural-data-1488.
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\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 CECAM Event Manager if you have any question.
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\r\nDescription
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\r\nG protein-coupled receptors (GPCRs) represent a vast and diverse class of transmembrane proteins that orchestrate a wide range of physiological processes by responding to both endogenous and exogenous ligands [1,2]. These receptors are essential to critical functions such as metabolism, immune regulation, neuronal signaling, and sensory perception - including vision and olfaction. Due to their physiological relevance and membrane accessibility, GPCRs are the targets of approximately 34% of all prescribed medications, accounting for nearly 27% of the global pharmaceutical market [3].
\r\nDespite their pharmaceutical importance, key aspects of GPCR function remain elusive. The canonical activation model posits that agonist binding to the extracellular orthosteric site triggers allosteric changes - most notably, the outward displacement of transmembrane helices 5 (TM5) and 6 (TM6) on the intracellular side - ultimately leading to receptor activation [2-4]. However, recent evidence suggests a more nuanced mechanism. In several GPCRs, activation appears to involve cooperative engagement between the agonist and the G protein. For example, the G protein may disrupt an \"inactivating ionic lock\" - a salt bridge between TM3 and TM6 - while the agonist stabilizes the active conformation. In some receptors, this is complemented by the formation of an “activating ionic lock” between TM5 and TM6 [5-8]. These dual contributions are considered thermodynamically essential for full activation [7].
\r\nAdding further complexity, GPCR activity is regulated by conformational microswitches and finely tuned intra-protein interaction networks. These dynamic rearrangements are difficult to capture and often elude direct correlation with functional outcomes. Moreover, allosteric ligands - which bind sites distinct from the orthosteric pocket - are being increasingly identified [9-12], along with small molecules capable of biased signaling, i.e., preferential activation of specific intracellular pathways [11-13, 16, 17]. These findings reveal a rich and underexplored conformational landscape that governs GPCR signaling. In addition, native membrane components—such as lipids and interacting proteins, including GPCR oligomers—are known to significantly modulate receptor function [11, 18-22].
\r\nTo disentangle these intricacies, computational modeling has become indispensable, offering atomistic insight into GPCR conformational dynamics and mechanistic understanding [1-2, 7, 11, 14, 16–21, 23]. Nevertheless, key questions remain - particularly regarding the structural basis of biased signaling, strategies for leveraging allosteric networks in pharmacology, and the modulatory role of the lipid environment. Addressing these gaps is crucial for both fundamental biology and the rational design of next-generation GPCR-targeting drugs with improved selectivity and safety profiles.
\r\nThese scientific challenges form the foundation of our upcoming workshop, which will focus on the latest experimental and computational approaches for studying the functional dynamics of GPCRs. Given the profound health, economic, and societal implications of modulating these receptors with precision, we aim to strengthen the interdisciplinary nature of the event by increasing the representation of experimental research and integrating cutting-edge artificial intelligence applications into the program.
\r\nBuilding upon the success of the 2022 and 2024 editions - which led to new collaborations and a landmark publication in Nature Reviews Drug Discovery [24] - our goal is to further enhance communication and collaboration between experimentalists and theoreticians. The workshop will serve as a reference point for young scientists and students, offering a platform to interact with leading international experts. We are confident that this initiative will foster insightful discussions and contribute meaningfully to advancing the field of GPCR pharmacology.
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\r\nReferences
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\r\n[1] J. Smith, R. Lefkowitz, S. Rajagopal, Nat. Rev. Drug. Discov., 17, 243-260 (2018)
\r\n[2] P. Conflitti, E. Lyman, M. Sansom, P. Hildebrand, H. Gutiérrez-de-Terán, P. Carloni, T. Ansell, S. Yuan, P. Barth, A. Robinson, C. Tate, D. Gloriam, S. Grzesiek, M. Eddy, S. Prosser, V. Limongelli, Nat. Rev. Drug. Discov., 24, 251-275 (2025)
\r\n[3] L. Picard, A. Orazietti, D. Tran, A. Tucs, S. Hagimoto, Z. Qi, S. Huang, K. Tsuda, A. Kitao, A. Sljoka, R. Prosser, Nat. Chem. Biol., 21, 71-79 (2024)
\r\n[4] B. Huang, C. St. Onge, H. Ma, Y. Zhang, Drug Discovery Today, 26, 189-199 (2021)
\r\n[5] D. Di Marino, P. Conflitti, S. Motta, V. Limongelli, Nat. Commun., 14, 6439 (2023)
\r\n[6] G. Milligan, R. Ward, S. Marsango, Current Opinion in Cell Biology, 57, 40-47 (2019)
\r\n[7] S. Huang, O. Almurad, R. Pejana, Z. Morrison, A. Pandey, L. Picard, M. Nitz, A. Sljoka, R. Prosser, eLife, 11, (2022)
\r\n[8] A. Duncan, W. Song, M. Sansom, Annu. Rev. Pharmacol. Toxicol., 60, 31-50 (2020)
\r\n[9] A. Morales-Pastor, T. Miljuš, M. Dieguez-Eceolaza, T. Stępniewski, V. Ledesma-Martin, F. Heydenreich, T. Flock, B. Plouffe, C. Le Gouill, J. Duchaine, D. Sykes, C. Nicholson, E. Koers, W. Guba, A. Rufer, U. Grether, M. Bouvier, D. Veprintsev, J. Selent, Nat. Commun., 16, 5265 (2025)
\r\n[10] A. Faouzi, H. Wang, S. Zaidi, J. DiBerto, T. Che, Q. Qu, M. Robertson, M. Madasu, A. El Daibani, B. Varga, T. Zhang, C. Ruiz, S. Liu, J. Xu, K. Appourchaux, S. Slocum, S. Eans, M. Cameron, R. Al-Hasani, Y. Pan, B. Roth, J. McLaughlin, G. Skiniotis, V. Katritch, B. Kobilka, S. Majumdar, Nature, 613, 767-774 (2022)
\r\n[11] M. Wall, E. Hill, R. Huckstepp, K. Barkan, G. Deganutti, M. Leuenberger, B. Preti, I. Winfield, S. Carvalho, A. Suchankova, H. Wei, D. Safitri, X. Huang, W. Imlach, C. La Mache, E. Dean, C. Hume, S. Hayward, J. Oliver, F. Zhao, D. Spanswick, C. Reynolds, M. Lochner, G. Ladds, B. Frenguelli, Nat. Commun., 13, 4150 (2022)
\r\n[12] D. Wootten, A. Christopoulos, M. Marti-Solano, M. Babu, P. Sexton, Nat. Rev. Mol. Cell. Biol., 19, 638-653 (2018)
\r\n[13] D. Hilger, M. Masureel, B. Kobilka, Nat. Struct. Mol. Biol., 25, 4-12 (2018)
\r\n[14] D. Aranda-García, T. Stepniewski, M. Torrens-Fontanals, A. García-Recio, M. Lopez-Balastegui, B. Medel-Lacruz, A. Morales-Pastor, A. Peralta-García, M. Dieguez-Eceolaza, D. Sotillo-Nuñez, T. Ding, M. Drabek, C. Jacquemard, J. Jakowiecki, W. Jespers, M. Jiménez-Rosés, V. Jun-Yu-Lim, A. Nicoli, U. Orzel, A. Shahraki, J. Tiemann, V. Ledesma-Martin, F. Nerín-Fonz, S. Suárez-Dou, O. Canal, G. Pándy-Szekeres, J. Mao, D. Gloriam, E. Kellenberger, D. Latek, R. Guixà-González, H. Gutiérrez-de-Terán, I. Tikhonova, P. Hildebrand, M. Filizola, M. Babu, A. Di Pizio, S. Filipek, P. Kolb, A. Cordomi, T. Giorgino, M. Marti-Solano, J. Selent, Nat. Commun., 16, 2020 (2025)
\r\n[15] D. Thal, A. Glukhova, P. Sexton, A. Christopoulos, Nature, 559, 45-53 (2018)
\r\n[16] L. Slosky, M. Caron, L. Barak, Trends in Pharmacological Sciences, 42, 283-299 (2021)
\r\n[17] C. Zhu, X. Lan, Z. Wei, J. Yu, J. Zhang, Acta Pharmaceutica Sinica B, 14, 67-86 (2024)
\r\n[18] V. D’Amore, P. Conflitti, L. Marinelli, V. Limongelli, Chem, 10, 3678-3698 (2024)
\r\n[19] A. Mafi, S. Kim, W. Goddard, Nat. Chem., 15, 1127-1137 (2023)
\r\n[20] H. Batebi, G. Pérez-Hernández, S. Rahman, B. Lan, A. Kamprad, M. Shi, D. Speck, J. Tiemann, R. Guixà-González, F. Reinhardt, P. Stadler, M. Papasergi-Scott, G. Skiniotis, P. Scheerer, B. Kobilka, J. Mathiesen, X. Liu, P. Hildebrand, Nat. Struct. Mol. Biol., 31, 1692-1701 (2024)
\r\n[21] A. Manglik, T. Kim, M. Masureel, C. Altenbach, Z. Yang, D. Hilger, M. Lerch, T. Kobilka, F. Thian, W. Hubbell, R. Prosser, B. Kobilka, Cell, 161, 1101-1111 (2015)
\r\n[22] M. Congreve, C. de Graaf, N. Swain, C. Tate, Cell, 181, 81-91 (2020)
\r\n[23] J. Lorente, A. Sokolov, G. Ferguson, H. Schiöth, A. Hauser, D. Gloriam, Nat. Rev. Drug. Discov., 24, 458-479 (2025)
\r\n[24] M. Lopez‐Balastegui, T. Stepniewski, M. Kogut‐Günthel, A. Di Pizio, M. Rosenkilde, J. Mao, J. Selent, British. J. Pharmacology., 182, 3211-3224 (2024)\r\n
\r\nEPFL Investor Day 2026 brings together leading investors and ambitious deeptech startups from EPFL and across Western Switzerland.
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\r\nTaking place on Wednesday, 25 November 2026 at the SwissTech Convention Center, the event is structured in two parts:\r\n
This workshop is for staff and researchers working in NGOs and non-profits who aim to bring AI into their workflows with an ethical, careful approach. Join us for a hands-on morning of using and deploying the flagship model of the Swiss AI Initiative, learn first hand from the engineers and scientists working on Apertus.
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\r\nThe workshop runs from 9:30 to 12:30 at the EPFL AI Center Lounge in Lausanne. Doors open at 9:00.
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\r\nBackground: Apertus is a fully open large language model built in Switzerland, which is fully reproducible and can run on your own infrastructure. As a Foundation Model, it has already been adapted to specific contexts through post-training and fine-tuning processes. In addition to open access at all Swiss academic institutions, a growing number of Swiss and international commercial providers support Apertus for production deployment.
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\r\nThis workshop is also designed as a two-way conversation: alongside learning how to use and deploy Apertus, we want to hear how your organization is already working with AI, and where today's tools still fall short for you. We would like to hear about the languages, legal contexts, and use cases you operate in. This input will give us the opportunity to prioritize improvements for non-profit organizations on the Apertus roadmap.
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\r\nAt this workshop, you will have the chance to:\r\n
“To emphasize (...) dubious uses of risk is perverse, a dirty way of talking about a
\r\nclean scientific subject”
\r\nMary Douglas, Risk and Blame, 36.
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\r\nAs the baseline condition of so many territories shaped by extractive industries, administrative delay, and climatic instability, risk is prevalent. Yet ecological risk—pollution, fires, floods, heatwaves, droughts—is still presented as problems to be solved rather than conditions to be inhabited. This also speaks to an outsourcing of risk through externalized consequences of spatial injustice. Banks, developers, material supply chains, normative institutions, subcontracting hierarchies —all contend with calculated risk. This edition of Pressure Points asks us to unpack what it means to live with the risk, how it is managed, commodified, quantified, invented, politicized, instrumentalized, tamed, and to think, design, cohabitate intellectually and physically with it. The assembled guests should help us think and build literacy toward developing tools for living within uncertain territories and futures.
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\r\nSonia Seneviratne
\r\nMonday, October 26, 17:00 CET
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\r\nSonia Seneviratne is a Full Professor in Land-Climate Dynamics at ETH Zurich, with a focus on climate science and environmental physics. She conducts research on climate extremes such as droughts, land-climate processes, and human-induced climate change, based on climate modelling and data analyses. Listed among the Highly Cited Researchers of Web of Science (Clarivate) since 2014, she was a Coordinating Lead Author and Lead Author on several reports of the Intergovernmental Panel on Climate Change (IPCC), including the Special Report on Extreme Events, the Special Report on Global Warming of 1.5°C, and the Sixth Assessment Report in 2021. Seneviratne has received the Macelwane Medal of the American Geophysical Union in 2013 and the Hans-Oeschger Medal of the European Geosciences Union. Since July 2023, she serves as IPCC Working Group I Vice-Chair for the seventh assessment cycle (2023–2030). Her most recent contribution, published in June 2026, is the release of MESMER v1.0.0, an open-source climate model emulator she helped develop as part of her research group. It reproduces the spatial climate patterns of complex Earth System Models, including temperature and several climate-extreme indicators, making detailed climate information accessible to the wider research community.
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\r\nRIOT (Research and Innovation on Territory) is a laboratory engaged in pedagogy and research within the Institute of Architecture (ENAC) at the Swiss Federal Institute of Technology–EPFL, led by Charlotte Malterre-Barthes with Elif Erez, Flore Guichot, Jeremy Ratib, Summer Islam, Antoine Iweins, Kathy Kao, Nathalie Marj, Romain Dubetier-Grenier, Sylvie Clavel, and Saira Mohammed. Believing that the construction sector and design disciplines must pivot and wholeheartedly engage in the current social and climatic urgencies by rewiring themselves to face and repair the harm, RIOT utilizes tactics and strategies to decarbonize, decolonize, and depatriarchalize space production–by design.
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\r\n
“To emphasize (...) dubious uses of risk is perverse, a dirty way of talking about a
\r\nclean scientific subject”
\r\nMary Douglas, Risk and Blame, 36.
\r\n
\r\nAs the baseline condition of so many territories shaped by extractive industries, administrative delay, and climatic instability, risk is prevalent. Yet ecological risk—pollution, fires, floods, heatwaves, droughts—is still presented as problems to be solved rather than conditions to be inhabited. This also speaks to an outsourcing of risk through externalized consequences of spatial injustice. Banks, developers, material supply chains, normative institutions, subcontracting hierarchies —all contend with calculated risk. This edition of Pressure Points asks us to unpack what it means to live with the risk, how it is managed, commodified, quantified, invented, politicized, instrumentalized, tamed, and to think, design, cohabitate intellectually and physically with it. The assembled guests should help us think and build literacy toward developing tools for living within uncertain territories and futures.
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\r\nLiam Ross
\r\nTuesday, November 3, 17:00 CET
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\r\nLiam Ross is an architect and senior lecturer in Architectural Design at the University of Edinburgh, with a focus on building standardisation as a mode of architectural design, and in particular on fire-safety regulation. He also examines how those standards produce surprising side-effects as they are reinterpreted in practice. His book Pyrotechnic Cities: Architecture, Fire-Safety and Standardisation was published by Routledge in 2022, and describes the way that architectural design is an instrument of political agency.
\r\nHis work has been exhibited and published widely, including in Architectural Research Quarterly (arq), Arch+, and journalistic outlets such as Blueprint, Prospect, and Volume.
\r\nRoss has experience of practice in the UK and US, including a period of 5 years with Malcolm Fraser Architects, and maintains a relationship with professional practice as co-founder of ESALA Projects, a consultancy offering pro-bono and for-fee design services to public and third-sector clients. His most recent work, published in January 2026 in Architectural Research Quarterly, includes a co-authored article with Jon Goodbun entitled ‘Design and the extended building site: Ecologies of production and the production of ecologies’, which reframes the building site as an 'extended' socioecological system reaching across the global supply chains, material extraction, and labour that construction depends on, arguing that building is an ecological and political process rather than a purely material one.
\r\n
\r\nRIOT (Research and Innovation on Territory) is a laboratory engaged in pedagogy and research within the Institute of Architecture (ENAC) at the Swiss Federal Institute of Technology–EPFL, led by Charlotte Malterre-Barthes with Elif Erez, Flore Guichot, Jeremy Ratib, Summer Islam, Antoine Iweins, Kathy Kao, Nathalie Marj, Romain Dubetier-Grenier, Sylvie Clavel, and Saira Mohammed. Believing that the construction sector and design disciplines must pivot and wholeheartedly engage in the current social and climatic urgencies by rewiring themselves to face and repair the harm, RIOT utilizes tactics and strategies to decarbonize, decolonize, and depatriarchalize space production–by design.
\r\n
“To emphasize (...) dubious uses of risk is perverse, a dirty way of talking about a
\r\nclean scientific subject”
\r\nMary Douglas, Risk and Blame, 36.
\r\n
\r\nAs the baseline condition of so many territories shaped by extractive industries, administrative delay, and climatic instability, risk is prevalent. Yet ecological risk—pollution, fires, floods, heatwaves, droughts—is still presented as problems to be solved rather than conditions to be inhabited. This also speaks to an outsourcing of risk through externalized consequences of spatial injustice. Banks, developers, material supply chains, normative institutions, subcontracting hierarchies —all contend with calculated risk. This edition of Pressure Points asks us to unpack what it means to live with the risk, how it is managed, commodified, quantified, invented, politicized, instrumentalized, tamed, and to think, design, cohabitate intellectually and physically with it. The assembled guests should help us think and build literacy toward developing tools for living within uncertain territories and futures.
\r\n
\r\nJess Myers
\r\nMonday, November 16, 17:00 CET
\r\n
\r\nJess Myers is an urbanist whose practice includes work as an editor, writer, podcaster and curator, and is a tenure-track Assistant Professor at Syracuse University. Previously, Myers was an assistant professor of architecture at the Rhode Island School of Design. She has worked as an archivist, translator and analyst in New York and Paris. Myers served as a co-steward of the Architecture Lobby’s New York chapter and as the series editor for SEIU’s book series, Taking Freedom. Her research takes many forms, including a variety of multimedia platforms, which she uses to explore politics and residency in urban conditions. Myers’ podcast, Here There Be Dragons focuses on the intersection of identity politics and security policy in public space through the eyes of New Yorkers, Parisians and Stockholmers. Myers’ work has been published in The Architect’s Newspaper, Log, The Funambulist Magazine, Failed Architecture, Avery Review, Dwell and l’Architecture d’Aujourd’hui. Her most recent exhibition, “A Pause Is Not A Break,“ was exhibited widely, including at the Rhode Island School of Design, the University of Iowa and Carleton University.
\r\n
\r\nRIOT (Research and Innovation on Territory) is a laboratory engaged in pedagogy and research within the Institute of Architecture (ENAC) at the Swiss Federal Institute of Technology–EPFL, led by Charlotte Malterre-Barthes with Elif Erez, Flore Guichot, Jeremy Ratib, Summer Islam, Antoine Iweins, Kathy Kao, Nathalie Marj, Romain Dubetier-Grenier, Sylvie Clavel, and Saira Mohammed. Believing that the construction sector and design disciplines must pivot and wholeheartedly engage in the current social and climatic urgencies by rewiring themselves to face and repair the harm, RIOT utilizes tactics and strategies to decarbonize, decolonize, and depatriarchalize space production–by design.
\r\n