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July 01, 2016
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Date:22ThursdayJanuary 2026Colloquia
Physics Colloquium
More information Time 11:15 - 12:30Title Atomic tweezer arrays coupled to lightLocation Physics Weissman AuditoriumLecturer Prof. Julian Leonard Organizer Department of Condensed Matter PhysicsAbstract Show full text abstract about Recent years have seen a growing interest in developing cohe...» Recent years have seen a growing interest in developing coherent atom-light interfaces due to their relevance for cavity QED and quantum networks. The focus has been on systems with collectively coupled ensembles, and with strongly coupled single atoms. However, combining strong atom-light coupling with single-atom control remains challenging. We report on experiments with an atomic tweezer array that is strongly coupled to an optical fiber cavity. The setup integrates three ingredients: single atom control for arbitrary quantum logical operations, a tweezer-cavity system for cavity QED, and a direct fiber interface for real-time measurements and networking. This opens a path for programmable interactions within an atomic tweezer array, for non-destructive readout protocols, and for implementing quantum network protocols. -
Date:22ThursdayJanuary 2026Lecture
Vision and AI
More information Time 12:15 - 13:15Title Addressing the Unexpected - Anomaly Detection and AI SafetyLocation Jacob Ziskind Building
Room 1 - 1 חדרLecturer Niv Cohen
NYUOrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about While AI models are becoming an ever-increasing part of our ...» While AI models are becoming an ever-increasing part of our lives, our understanding of their behavior in unexpected situations is drifting even further out of reach. This gap poses significant risks to users, model owners, and society at large.
In the first part of the talk, I will overview my research on detecting unexpected phenomena with and within deep learning models. Specifically, detecting (i) anomalous samples, (ii) unexpected model behavior, and (iii) unexpected security threats. In the second part of the talk, I will dive into my recent research on a specific type of unexpected security threat: attacks on image watermarks. I will review such attacks and present my recent work toward addressing them. I will conclude with a discussion of future research directions.
Bio:
Niv Cohen is a postdoctoral researcher at the school of Computer Science & Engineering at New York University. He received his Ph.D. in Computer Science from the Hebrew University in 2024. His research interests include representation learning, computer vision, and AI safety. He is a recipient of the VATAT Scholarship for Outstanding Postdoctoral Fellows in Data Science and the 2024 Blavatnik Prize for Outstanding Israeli Doctoral Students in Computer Science. -
Date:22ThursdayJanuary 2026Lecture
Geometric Functional Analysis and Probability Seminar
More information Time 13:30 - 14:30Title Local laws of sample covariance matrices beyond the separable caseLocation Jacob Ziskind Building
Room 155 - חדר 155Lecturer Elliot Paquette
McGillOrganizer Department of MathematicsContact Abstract Show full text abstract about Sample covariance matrices are among the most fundamental ob...» Sample covariance matrices are among the most fundamental objects in random matrix theory and statistics. In this talk, I'll discuss recent work identifying the assumptions on random vectors that allow local laws to hold for their sample covariance matrices — these are matrices with iid rows sampled from a fixed distribution.
A local law says that the empirical eigenvalue distribution converges to its deterministic limit—in this case the deformed Marchenko–Pastur law—not just globally, but on short intervals which still contain a power of dimension many eigenvalues. This fine-grained control is essential for many applications, including universality for the local eigenvalue distributions.
The classical approach assumes the data vectors take a separable form g=Xw where w has independent entries—but this excludes many natural examples. We ask: what assumptions on g are really needed? It turns out that concentration of quadratic forms suffices for an optimal averaged local law, while a structural condition on cumulant tensors—interpolating between independence and generic dependence—suffices for the full anisotropic local law.
I'll discuss key examples where our assumptions can be verified: sign-invariant vectors, the 'random features model’ from machine learning, and some examples of spin-glass type. I'll also give a short overview of the proof, which introduces a tensor network framework for fluctuation averaging in the presence of higher-order cumulant structure.
Joint with Jack Ma (Yale), Zhou Fan (Yale), Zhichao Wang (Berkeley) -
Date:27TuesdayJanuary 2026Lecture
Red vs. White: Failure in Red Blood Cell Recycling Drives T Cell Aging trajectory
More information Time 10:00 - 11:00Location Benoziyo Bldg. for Biological Sciences - Auditorium - Floor 1Lecturer Prof. Noga-harel Contact -
Date:27TuesdayJanuary 2026Lecture
Vesiculab: Advancing the Extracellular Vesicle Workflow
More information Time 11:00 - 12:30Location https://events.teams.microsoft.com/event/5dff50bf-ce1e-45b2-a878-fe3a396375be@3f0f7402-6ba8-43ab-9da8-356d1657dd55Organizer Department of Life Sciences Core FacilitiesContact Abstract Show full text abstract about Dear Colleagues,You are cordially invited to a scientific an...» Dear Colleagues,You are cordially invited to a scientific and application focused webinar entitled Vesiculab: Advancing the Extracellular Vesicle Workflow. This webinar will present state of the art approaches for improving reproducibility, analytical rigor, and translational relevance in extracellular vesicle research, with an emphasis on practical solutions for everyday laboratory workflows. The presentation will be delivered by Dr Dimitri Aubert, PhD, CEO of Vesiculab. Scientific topics include:Fast size exclusion chromatography for efficient EV isolation,Total EV staining strategies for in vitro and in vivo studies,Optimized EV sample preparation for analytical and functional assays,Calibration principles for nanoflow cytometry and fluorescence NTA,Best practices for EV handling, storage, and preservation. -
Date:27TuesdayJanuary 2026Lecture
Decoding the Molecular Logic of Ciliary Organization and Stability
More information Time 11:15 - 12:15Location Gerhard M.J. Schmidt Lecture HallLecturer Dr. Ron Orbach Organizer Department of Chemical and Structural Biology -
Date:27TuesdayJanuary 2026Lecture
Weizmann Ornithology monthly lecture
More information Time 14:10 - 15:30Title To be announcedLocation Benoziyo
591CLecturer Prof. Orr Spiegel Organizer Department of Plant and Environmental SciencesContact Abstract Show full text abstract about Prof. Orr Spiegel from TAU studies animal movement ...» Prof. Orr Spiegel from TAU studies animal movement -
Date:28WednesdayJanuary 2026Lecture
iSCAR Breakfast Seminar
More information Time 09:00 - 10:00Title Cellular and Molecular Trajectories of Age-associated Lymphocytes and Their Impact on Aging and Cognitive DeclineLocation Max and Lillian Candiotty Building
AuditoriumLecturer Prof. Alon Monsonego Organizer Department of Immunology and Regenerative BiologyContact -
Date:28WednesdayJanuary 2026Colloquia
Collective states in molecular lattices: A novel route for tailored 2D and 1D materials
More information Time 11:00 - 12:15Location Stone Administration Building
Zacks HallLecturer Prof. Stephanie Reich Homepage Abstract Show full text abstract about Two-dimensional materials are atomically thin crystals with ...» Two-dimensional materials are atomically thin crystals with a huge variety of physico-chemical properties. By stacking such materials into heterostructures we can combine the electrical, optical, and vibrational excitations of different materials with atomic control over their interfaces. Despite the great selection of 2D materials existing today, we desire novel routes for their preparation in addition to cleaving them from layered bulk parent compounds.In this talk I discuss a concept for novel 2D materials from organic molecules: Growing molecules into well-defined 2D and 1D lattices. We prepared 2D lattices of flat aromatic molecules using hexagonal boron nitride and graphene as atomically smooth substrates. The molecules are well separated in space and oriented side-by-side so that electrons and vibrations are confined to the individual building blocks. However, the interaction between their optical and vibrational transition dipole moments gives rise to collective states that can propagate inside the lattices. One-dimensional molecular lattices are grown by filling carbon- and boron-nitride nanotubes leading to giant J aggregates inside the tubes. We discuss how to use molecular lattices for advance molecular-2D-material heterostructures and how to manipulate their emergent optical excitations. -
Date:28WednesdayJanuary 2026Lecture
Innovatin Flash Talks
More information Time 11:00 - 13:00Title In memory of Prof. Haim GartyLocation Schmidt AuditoriumLecturer Tamir Klein, Ronny Neumann, Boris Rybtchinski, Leeat Keren
Join us for Bina Flash Talks, an exciting event where Weizmann scientists share impactful glimpses into their cutting-edge translational research, and be part of a growing innovation and applied science community in the Weizmann Institute.Contact -
Date:29ThursdayJanuary 2026Conference
Israel Algorithmic Game Theory Day
More information Time 08:00 - 08:00Title Israel Algorithmic Game Theory DayChairperson Shahar DobzinskiContact -
Date:29ThursdayJanuary 2026Lecture
Geometric Functional Analysis and Probability Seminar
More information Time 13:30 - 14:30Title Variations of the Hardy Z-function and Dyson Brownian MotionLocation Jacob Ziskind Building
Room 155 - חדר 155Lecturer Yochay Jerby
HITOrganizer Department of MathematicsContact Abstract Show full text abstract about In this talk we present a new approximate functional equatio...» In this talk we present a new approximate functional equation for the Hardy Z function with exponentially decaying error. This formula makes it possible to define a variation space for Z(t) consisting of a family of functions Z_N(t,a) with parameters a = (a1, …, aN) on a fixed window [2n, 2N + 2]. In this space the original Hardy function Z(t) is extremely well approximated in the window by the special choice a = (1, …, 1). Within this variation space we single out a natural domain RH_N in which all functions Z_N(t,a) have only real zeros in the window. We show that RH_N has striking connections with random matrix theory. In particular a Brownian motion with Skorokhod type reflection at the boundary of RH_N induces a Dyson Brownian motion in the \beta=2 case, and modern universality results then yield the expected GUE local statistics for elements of RH_N. No prior knowledge in number theory would be required. -
Date:29ThursdayJanuary 2026Lecture
Proteolysis-driven immunity: New insights into the role of proteasome-cleaved peptides in adaptive
More information Time 14:00 - 15:00Location Max and Lillian Candiotty Building
AuditoriumLecturer Prof. Yifat Merbl Organizer Dwek Institute for Cancer Therapy Research -
Date:01SundayFebruary 2026Lecture
A Reverse Engineering Approach to Diagenesis: Bone – a Case Study
More information Time 11:00 - 12:00Location Stone Administration Building
Zacks HallLecturer Prof. Steve Weiner Organizer Department of Earth and Planetary SciencesAbstract Show full text abstract about Many fossil materials have embedded signals that enable aspe...» Many fossil materials have embedded signals that enable aspects of the past to be reconstructed. These signals however can be altered or lost due to processes that take place once the fossil material is buried (diagenesis). Thus extracting reliable signals can be a major challenge. Here I present a new approach to better understanding diagenesis that I apply to bone. -
Date:01SundayFebruary 2026Lecture
The Clore Center for Biological Physics
More information Time 13:15 - 14:30Title Self-organized shape changes in elastic active gelsLocation Nella and Leon Benoziyo Physics LibraryLecturer Prof. Kinjal Dasbiswas
lunch at 12:45Contact Abstract Show full text abstract about Living systems utilize fundamental physics in the form of me...» Living systems utilize fundamental physics in the form of mechanical forces and geometric cues to move and change shape. A central question motivating our research is: how does biological matter utilize mechanical forces to form ordered structures and change shape? As a prototype of active biological materials capable of self-organized shape change, we explain experimental findings on cytoskeletal gel extracts by our collaborators at the Bernheim laboratory. Despite having identical composition of the biopolymer actin, molecular motor myosin and the crosslinker fascin, these gels contract and buckle into different shapes depending on the initial gel aspect ratio: thinner gels tend to wrinkle, while thicker gels tend to form domes. By incorporating motor-generated active stresses, alignment of active fibers, and stress-dependent myosin binding kinetics into a network-fluid (poroelastic) model, we qualitatively capture the observed trends in gel contraction dynamics measured using particle image velocimetry (PIV). We then show how a geometric elastic model for thin sheets can relate the 3D buckled shapes to strain rates predicted by the poroelastic model. Our findings have implications for shape changes during tissue morphogenesis and bio-inspired soft materials design. -
Date:02MondayFebruary 202604WednesdayFebruary 2026Academic Events
Winter STAR Workshop 2026 in honor of Lenny Makar-Limanov's 80th birthday
More information Time All dayLocation Jacob Ziskind Building
Room 1, 155Homepage -
Date:03TuesdayFebruary 2026Academic Events
Scientific Council Meeting - Steering 2026
More information Time 10:00 - 12:00Location The David Lopatie Conference Centre
KIMELContact -
Date:03TuesdayFebruary 2026Lecture
Deep Learning-Based Detection of Sinkhole-Induced Land Subsidence Along the Dead Sea
More information Time 11:30 - 12:30Location Stone Administration Building
Zacks HallLecturer Gali Dekel Organizer Department of Earth and Planetary SciencesAbstract Show full text abstract about The Dead Sea region has seen a rapid increase in sinkhole fo...» The Dead Sea region has seen a rapid increase in sinkhole formation, posing serious environmental and infrastructure risks. The Geological Survey of Israel monitors sinkhole-related land subsidence along the western shore using InSAR, but current detection relies on manual interpretation of interferometric phase data, which is time-consuming and error-prone.In this talk, I present an AI-based Deep Learning framework for automated detection of sinkhole-related subsidence from InSAR data. The model learns interferometric phase deformation patterns, rather than visual features, and is trained using expert-labeled subsidence maps from years of operational monitoring. I demonstrate the model’s ability to generalize across spatial and temporal settings using multiple evaluation schemes and object-level performance metrics. Results show effective detection of subsidence areas, promising generalization to unseen regions, and the ability to reconstruct large-scale subsidence trends from patch-level predictions. -
Date:03TuesdayFebruary 2026Academic Events
Seminar - What makes a life significant
More information Time 12:30 - 13:30Location Gerhard M.J. Schmidt Lecture HallLecturer Prof. Shahar Arzy Abstract Show full text abstract about Ourlivesareshapedbymeaningfulevents,relationships,andplaces—...» Ourlivesareshapedbymeaningfulevents,relationships,andplaces—elementsthatthataremakingthemworthytolive.Butwhatisthecognitivearchitectureunderlyingthiselusiveyetfoundationalconcept?Howcansignificancebedefined,measured,andmodeledwithinthehumanmind?Inthistalk,Iwillexplorethecognitiveconstructofsignificanceacrossthreecoreexperientialdimensions:time,space,andsocialrelationships.Iwillexaminewhethersignificanceisunderpinnedbydistinctcognitiveandcomputationalprinciples,howitmanifestsacrossdifferentpopulations,andwhatroleitplaysinbothhealthycognitionandvariousneuropsychiatricconditions.Drawingonbehavioralstudies,neuroimagingdata,computationalmodeling,andclinicalobservations,Iwilloutlineamultidimensionalframeworkforunderstandingsignificanceasaunifyingconstruct—onethatintegratesmemory,affect,andself-representation.Ultimately,thisinquiryaimstoshedlightonhowthebrainencodeswhatmakesalifesignificant. -
Date:04WednesdayFebruary 2026Lecture
Machine Learning and Statistics Seminar
More information Time 11:15 - 12:30Title Fundamentals of Aligning General-Purpose AILocation Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Room 108 - חדר 108Lecturer Noam Razin
PrincetonOrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about The field of artificial intelligence (AI) is undergoing a pa...» The field of artificial intelligence (AI) is undergoing a paradigm shift, moving from neural networks trained for narrowly defined tasks (e.g., image classification and machine translation) to general-purpose models such as ChatGPT. These models are trained at unprecedented scales to perform a wide range of tasks, from providing travel recommendations to solving Olympiad-level math problems. As they are increasingly adopted in society, a central challenge is to ensure the alignment of general-purpose models with human preferences. In this talk, I will present a series of works that reveal fundamental pitfalls in existing alignment methods. In particular, I will show that they can: (1) suffer from a flat objective landscape that hinders optimization, and (2) fail to reliably increase the likelihood of generating preferred outputs, sometimes even causing the model to generate outputs with an opposite meaning. Beyond characterizing these pitfalls, our theory provides quantitative measures for identifying when they occur, suggests preventative guidelines, and has led to the development of new data selection and alignment algorithms, validated at large scale in real-world settings. Our contributions address both efficiency challenges and safety risks that may arise in the alignment process. I will conclude with an outlook on future directions, toward building a practical theory in the age of general-purpose AI.
Short bio:
Noam Razin is a Postdoctoral Fellow at Princeton Language and Intelligence, Princeton University. His research focuses on the fundamentals of artificial intelligence (AI). By combining mathematical analyses with systematic experimentation, he aims to develop theories that shed light on how modern AI works, identify potential failures, and yield principled methods for improving efficiency, reliability, and performance.
Noam earned his PhD in Computer Science at Tel Aviv University, where he was advised by Nadav Cohen. Prior to that, he obtained a BSc in Computer Science (summa cum laude) at The Hebrew University of Jerusalem under the Amirim honors program. For his research, Noam received several honors and awards, including the Zuckerman Postdoctoral Scholarship, the Israeli Council for Higher Education (VATAT) Postdoctoral Scholarship, the Apple Scholars in AI/ML PhD fellowship, the Tel Aviv University Center for AI and Data Science excellence fellowship, and the Deutsch Prize for PhD candidates.