Integrated Calendar

Lior will relate her PhD study on the global biomass of birds. The thrushes are a passerine bird family, Turdidae, with a worldwide distribution. The family was once much larger before biologists reclassified the former subfamily Saxicolinae, which includes the chats and European robins, as Old World flycatchers. Thrushes are small to medium-sized ground living birds that feed on insects, other invertebrates, and fruit. Some unrelated species around the world have been named after thrushes due to their similarity to birds in this family.

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Over the past decade, deep learning algorithms have achieved—and in some cases surpassed—human-level performance in face recognition. This remarkable success raises a fundamental question: to what extent do these artificial systems capture the mechanisms that underlie human face recognition? In this talk, I will explore the convergences and divergences between deep learning models and the human face recognition system. I will first show how deep convolutional neural networks (DCNNs)
reproduce key phenomena observed in human face perception. Yet, despite these similarities, important differences remain in how humans and deep learning algorithms learn and represent faces. To bridge these gaps, we employ models that learn continually and integrate visual and language-based models, to capture both perceptual and conceptual aspects of face recognition. Together, these findings demonstrate how deep learning algorithms can advance our understanding of human face recognition.

BIO:
Galit Yovel is a professor in the School of Psychological Sciences and Sagol School of Neuroscience at Tel Aviv University. She earned her PhD in Psychology from the University of Chicago and completed her Post-Doctoral studies in the Department of Brain and Cognitive Sciences at MIT. In her research she combines methods from experimental psychology, neuroimaging and AI to unravel the neural and cognitive mechanisms of human face recognition. Her work extends beyond faces to examine how the body, voice, motion, and semantic information contribute to person recognition. She was the head of Strauss MRI Center at Tel Aviv University (2015-2017), the head of the School of Psychological Sciences (2017-2021) and the head of the AI and Data Science major for students in life science/social sciences and law (2022-2025). She is the recipient of the Bruno award (2017), and a six-time recipient
of the Tel Aviv University Rector award for excellence in teaching.

Cells, tissues and organs can rotate spontaneously in vivo and in vitro. These motions are remarkable for their robustness and for their potential functions. However, physical mechanisms coordinating these dynamics are poorly understood. Active matter formalisms are required to understand these out-of-equilibrium phenomena with quantitative comparisons between theory and experiments.I will present two examples of spontaneous rotation with experiments synergized with theory (1, 2). In a first study (1), we report that rings of epithelial cells can undergo spontaneous rotation below a threshold perimeter. We demonstrate that the tug-of-war between cell polarities together with the ring boundaries determine the onset to coherent motion. The principal features of these dynamics are recapitulated with a numerical simulation (Vicsek model). In a second study (2), we show that cell doublets rotate in a 3D matrix and we identify mesoscopic structures leading the movement. Our theoretical framework integrates consistently cell polarity, cell motion, and interface deformation with equations capturing the physics of cortical cell layers. We also report that the Curie principle is verified in these cellular doublets with its symmetry relations between causes and effects. Altogether both examples could set generic rules to quantify and predict generic motion of tissues and organs as well as active synthetic materials.1- S. Lo Vecchio et al. Nature Physics 20:322–331(2024).2- L. Lu et al. Nature Physics 20:1194–1203 (2024).

Symplectic capacities are invariants that quantify the size of symplectic manifolds using themes from Hamiltonian dynamics and symplectic topology. While convexity is not preserved under symplectomorphisms, convex domains nevertheless exhibit notable behavior with respect to these capacities. Viterbo's volume-capacity conjecture (2000) suggests that, among convex domains of equal volume, the ball has maximal capacity. By capturing the interplay between convex and symplectic geometries, this simply formulated conjecture has become highly influential in the study of symplectic capacities, prompting extensive research. One result in this direction shows that smooth domains which are symplectic Zoll—a dynamical property—are local maximizers. In this talk, I will present a counterexample to Viterbo’s conjecture developed jointly with Yaron Ostrover and discuss follow-up questions. One implication is that a capacity maximizer cannot be smooth and strictly convex, raising the question of characterizing nonsmooth dynamical properties that detect local maximizers. I will propose a dynamical extension of the Zoll property to nonsmooth domains and discuss its equivalence with certain topological properties.

Nonreciprocal interactions in which the influence of A on B differs from that of B on A are abundant in physical, chemical, biological, and ecological systems, and are known to give rise to oscillatory states. Yet, it remains unclear whether these states represent true phases of matter: Can they maintain long-range order in spatially extended, noisy environments in the thermodynamic limit? And what kinds of phase transitions do they exhibit? To address these questions, we introduce a minimal generalization of the Ising model with two species having opposing goals. We demonstrate that oscillatory phases are stable in three dimensions but not in two, and that nonreciprocity changes the critical exponents from those of the Ising model to those of the XY model. We further extend this framework to a nonreciprocal XY model and develop a Harris-like criterion that determines when nonreciprocity fundamentally alters universal behavior. Finally, we apply these insights to a recent model of biomolecular condensates, predicting exotic dynamical phases and suggesting experimental tests.

perovskites are among the most promising materials for next-generation solar cells, offering exceptionalefficiency gains and driving major investment in large-scale production. Yet, as the technology moves toward realworlddeployment, corrosion has emerged as a critical but often overlooked challenge. It arises not only fromenvironmental exposure but also from the intrinsic reactivity of the perovskite itself, which can attack metalelectrodes such as gold through complex chemical pathways.This show highlights why corrosion in perovskite devices is both subtle and important. Light and heat can triggerchemical changes that produce reactive species, either directly corroding metals or transforming the perovskite intoa more aggressive state. By connecting principles from corrosion science and semiconductor physics, we revealhow these reactions originate and what must be done to control them at their source.