לוח שנה משולב

The discovery of the cholesteric ushered in the study of liquid crystalline phases and phenomena.  As a structure periodic on the micron length scale, the cholesteric acts as a diffraction grating, affording a labradorescent splendor to the casual observer. While these discoveries were being made, Maxwell developed the theory of canal surfaces; surfaces swept out by a sphere of varying radius moving along an arbitrary path.  I will use a new observation of cholesteric droplets to explain the connection between canal surfaces, focal conic domains, and Apollonian packing. The power of geometric thinking will be highlighted.

At most how many edge-disjoint Hamilton cycles does a given directed graph contain? It is easy to see that one cannot pack more than the minimum in-degree or the minimum out-degree of the digraph. We show that in the random directed graph D(n,p) one can pack precisely this many edge-disjoint Hamilton cycles, with high probability, given that p is at least the Hamiltonicity threshold, up to a polylog factor. Based on a joint work with Asaf Ferber.

Abstract: Given a countable field K and a set E in K^2, we prove that Delta(E) = { xy | (x,y) in E-E } is equal to K provided that E has positive density. To achieve that we study K^*-invariant couplings between the Pontryagin duals of the fields K and L, under assumption that the multiplicative group of L is isomorphic to K^*. We show that the actions are disjoint unless the multiplicative groups isomorphism extends (possibly after a finite twist) to a field isomorphism. Other applications of our main dynamical result include Furstenberg-Sarkozy type result for Laurent polynomials and the equidistribution for Folner-Kloosterman sums. Based on a joint work with Michael Bjorklund (Chalmers).

From rough sketches that spark ideas to polished illustrations that explain complex concepts, visual communication is central to how humans think, create, and share knowledge. Yet despite major advances in generative AI, we are still far from models that can reason and communicate through visual forms.

I will present my work on bridging generative models and visual communication, focusing on three complementary domains: (1) algorithms for generating and understanding sketches, (2) systems that support exploratory visual creation beyond one-shot generation, and (3) methods for producing editable, parametric images for design applications.

These domains pose unique challenges: they are inherently data-scarce and rely on representations that go beyond pixel-based images commonly used in standard models. I will show how the rich priors of vision-language models can be leveraged to address these challenges through novel optimization objectives and regularization techniques that connect their learned features with the specialized representations required for visual communication.

Looking ahead, this research lays the foundation for general-purpose visual communication technologies: intelligent systems that collaborate with humans in visual domains, enhancing how we design, learn, and exchange knowledge.

Bio:

Yael Vinker is a Postdoctoral Associate at MIT CSAIL, working with Prof. Antonio Torralba. She received her Ph.D. in Computer Science from Tel Aviv University, advised by Profs. Daniel Cohen-Or and Ariel Shamir. Her research spans computer graphics, computer vision, and machine learning, with a focus on generative models for visual communication. Her work has been recognized with two Best Paper Awards (SIGGRAPH 2022, SIGGRAPH Asia 2023) and a Best Paper Honorable Mention (SIGGRAPH 2023). She was selected as an MIT EECS Rising Star (2024) and received the Blavatnik Prize for Outstanding Israeli Doctoral Students in Computer Science (2024) as well as the VATAT Ph.D. Fellowship.

Rivers play a central role in shaping the Earth's surface and ecosystems through physical, chemical, and biological interactions. The intensity, time, and location of these interactions change as rivers continuously migrate across the landscape. In recent decades, human activity and climate change have altered river hydrology and sediment fluxes, leading to changes in river positions. Climate warming, increasing flood extremes, and human-induced land use changes have slowed river migration rates in some river reaches while accelerating them in others. However, a comprehensive, spatially continuous, large-scale perspective on and understanding of these recent changes in the rate of river position shifts is lacking.To address this knowledge gap, we created a continuous global dataset of yearly river positions and migration rates over the past four decades. The continuous annual river positions were detected using Landsat-derived surface-water datasets and processed in Google Earth Engine, a cloud-based parallel-computation platform. The resulting river extents and centerlines reflect their yearly permanent positions, corresponding to the river locations during base flow. This approach improves the representation of position changes derived from geomorphological rather than hydrological processes. To analyze river position changes across different patterns and complexities at large scales, we developed and applied a global reach-based quantification method for river mobility rates.Results show that while some alluvial rivers maintain a stable annual pace of mobility, others exhibit trends in migration rates. For instance, the Amazon Basin, which has experienced significant deforestation and hydrological modifications, has shown increased rates of river position change in recent decades, impacting floodplain forests and communities. In this talk, we will discuss the advantages, limitations, and applications of the detected yearly river positions and mobility rates, offer insights into the forcings driving changes in river positions and their environmental outcomes, and highlight current and future impacts on one of Earth’s most vulnerable hydrologic systems.

Repetitive stress is a pervasive feature of modern life and a major risk factor for psychiatric and sensory disorders, yet how it alters sensory processing remains poorly understood. In this talk, I will present evidence that chronic stress concurrently remodels auditory cortical activity and noradrenergic signaling, leading to measurable changes in perception in adult mice. Combining repeated-stress paradigms with longitudinal two-photon imaging of neuronal activity and norepinephrine dynamics, alongside auditory-guided behavior, we find that stress increases spontaneous activity in auditory cortex while weakening sound-evoked responses in pyramidal neurons and parvalbumin interneurons. In contrast, somatostatin interneurons become more sound-responsive, suggesting a shift in inhibitory balance that can suppress pyramidal and PV output. These circuit changes are accompanied by behavioral consequences, most prominently a reduction in perceived loudness. Together, our results identify a cell-type-specific mechanism by which chronic stress reshapes sensory coding and link dysregulated internal-state signals to perceptual abnormalities associated with psychiatric disease.