Thesis Director: Prof. B. E. Ferreira De Sousa Correia,
\r\nChemistry and Chemical Engineering doctoral program
\r\nThesis Nr. 11408
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\r\nTo take part in the public defense, please contact directly the speaker
You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/toward-intelligent-behavior-in-macroscopic-active-matter-1481.
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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\nActive matter has emerged as a central framework for understanding systems composed of self-driven units across scales, ranging from molecular motors and cytoskeletal filaments to animal groups and robotic swarms. Initially, many foundational models focused on macroscopic agents – such as flocks, swarms, and driven granular particles – where simple interaction rules give rise to rich collective phenomena. However, over the past two decades, much of the focus has shifted toward microscopic and mesoscopic active systems, especially in soft and biological matter, supported by the technological development of high-resolution imaging, force measurement, and microfabrication. These advances have driven a more refined theoretical understanding, connecting microscopic dynamics with hydrodynamic and continuum-scale descriptions, and have found applications in biophysics, material science, and cellular biology.
\r\nIn parallel, yet often semi-independently, active matter concepts have flourished in ecological and robotic systems. In these domains, the agents – be they insects, birds, autonomous vehicles, or soft robots – not only self-propel and interact, but also sense their environments, make decisions, and adapt their behavior. These systems extend the classical framework of active matter by incorporating elements of intelligence, information processing, and environmental feedback. Notably, such systems can operate far from equilibrium and exhibit coordinated behavior that seems tuned for functional outcomes – navigation, foraging, or collective decision-making.
\r\nThese trends point toward a convergence: macroscopic active matter systems capable of intelligent, adaptive, or programmable behavior. This includes both natural systems (e.g., flocking insects, social insects, animal herds) and artificial systems (e.g., modular robots, programmable matter, active granular agents). The interplay of self-propulsion, interaction rules, information exchange, learning or memory, and system-level feedback opens exciting new directions for both fundamental science and applications. Recent efforts in this space combine techniques from statistical physics, nonlinear dynamics, robotics, and machine learning.
\r\nHowever, the communities working on these different aspects of active matter – soft matter physicists, ecologists, roboticists, and complexity scientists – remain fragmented, with limited opportunity for sustained dialogue. Bridging these communities is essential to develop a shared language, identify unifying principles, and guide the development of new experimental platforms and theoretical frameworks.
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\r\nReferences
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\r\n[1] F. Gu, B. Guiselin, N. Bain, I. Zuriguel, D. Bartolo, Nature, 638, 112-119 (2025)
\r\n[2] A. Rafsanjani, K. Bertoldi, A. Studart, Sci. Robot., 4, (2019)
\r\n[3] J. Tirado, A. Parvaresh, B. Seyidoğlu, D. Bedford, J. Jørgensen, A. Rafsanjani, Cyborg. Bionic. Syst., 6, (2025)
\r\n[4] J. O’Byrne, Y. Kafri, J. Tailleur, F. van Wijland, Nat. Rev. Phys., 4, 167-183 (2022)
\r\n[5] P. Baconnier, D. Shohat, C. López, C. Coulais, V. Démery, G. Düring, O. Dauchot, Nat. Phys., 18, 1234-1239 (2022)
\r\n[6] A. Cavagna, L. Di Carlo, I. Giardina, T. Grigera, S. Melillo, L. Parisi, G. Pisegna, M. Scandolo, Nat. Phys., 19, 1043-1049 (2023)
\r\n[7] M. Bischof, E. Del Giudice, Molecular Biology International, 2013, 1-19 (2013)
\r\n[8] A. Deutsch, P. Friedl, L. Preziosi, G. Theraulaz, Phil. Trans. R. Soc. B, 375, 20190377 (2020)
\r\n[9] N. Kumar, H. Soni, S. Ramaswamy, A. Sood, Nat. Commun., 5, 4688 (2014)
\r\n[10] M. Moussaid, S. Garnier, G. Theraulaz, D. Helbing, Topics in Cognitive Science, 1, 469-497 (2009)
\r\n[11] R. Bebon, J. Robinson, T. Speck, Phys. Rev. X, 15, 021050 (2025)
\r\n[12] M. Ben Zion, J. Fersula, N. Bredeche, O. Dauchot, Sci. Robot., 8, (2023)
\r\n[13] J. Fersula, N. Bredeche, O. Dauchot, Phys. Rev. E, 110, 014606 (2024)
\r\n[14] L. Caprini, A. Ldov, R. Gupta, H. Ellenberg, R. Wittmann, H. Löwen, C. Scholz, Commun. Phys., 7, 52 (2024)
\r\n[15] T. Lengronne, D. Mlynski, S. Patalano, R. James, L. Keller, S. Sumner, Proc. R. Soc. B., 288, rspb.2021.0275 (2021)
\r\n[16] T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, O. Shochet, Phys. Rev. Lett., 75, 1226-1229 (1995)
\r\n[17] L. Ning, H. Zhu, J. Yang, Q. Zhang, P. Liu, R. Ni, N. Zheng, NSO., 3, 20240005 (2024)
\r\n[18] G. Volpe, N. Araújo, M. Guix, M. Miodownik, N. Martin, L. Alvarez, J. Simmchen, R. Leonardo, N. Pellicciotta, Q. Martinet, J. Palacci, W. Ng, D. Saxena, R. Sapienza, S. Nadine, J. Mano, R. Mahdavi, C. Beck Adiels, J. Forth, C. Santangelo, S. Palagi, J. Seok, V. Webster-Wood, S. Wang, L. Yao, A. Aghakhani, T. Barois, H. Kellay, C. Coulais, M. van Hecke, C. Pierce, T. Wang, B. Chong, D. Goldman, A. Reina, V. Trianni, G. Volpe, R. Beckett, S. Nair, R. Armstrong, J. Phys.: Condens. Matter, 37, 333501 (2025)
\r\n[19] G. Gompper, R. Winkler, T. Speck, A. Solon, C. Nardini, F. Peruani, H. Löwen, R. Golestanian, U. Kaupp, L. Alvarez, T. Kiørboe, E. Lauga, W. Poon, A. DeSimone, S. Muiños-Landin, A. Fischer, N. Söker, F. Cichos, R. Kapral, P. Gaspard, M. Ripoll, F. Sagues, A. Doostmohammadi, J. Yeomans, I. Aranson, C. Bechinger, H. Stark, C. Hemelrijk, F. Nedelec, T. Sarkar, T. Aryaksama, M. Lacroix, G. Duclos, V. Yashunsky, P. Silberzan, M. Arroyo, S. Kale, J. Phys.: Condens. Matter, 32, 193001 (2020)
\r\n[20] G. Popkin, Nature, 529, 16-18 (2016)
EPFL Architecture is pleased to invite you to visit the exhibition of the Master students' work until July 31 at the Rolex Learning Center.
\r\nThe exhibition is divided into three distinct areas: the first brings together projects focused on resources and craftsmanship, such as wood, earth, and self-construction; the second features projects exploring urban and territorial scales; and the third presents work on social or individual housing, as well as interventions in existing buildings, including transformation, rehabilitation, and renovation.
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\r\nThe final reviews for the 2026 master's projects will take place from July 8 to 15 at the Rolex Learning Center and are open to the public.
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\r\nDates
\r\nFinal reviews: July, 8 - July, 15 2026
\r\nExhibtion: July, 8 - July, 31 2026
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\r\nLocation
\r\nRolex Learning Center, EPFL Campus
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\r\nProgram
\r\nReviews schedule and exhibition map