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Engineering Leadership in a World of Accelerating Change Engineering bridges science and technology, driving innovation for the benefit of people and society. Today we live in an increasingly technology-dependent world shaped by engineers — and the pace of change is increasing exponentially. This calls for a reexamination of how we educate and empower engineers to […] |
2 events,
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Phase change concentrates the action into a narrow region near the moving interface, where composition, transport, and interfacial disorder evolve rapidly and determine macroscopic outcomes. In this talk, I will show how controlling that transient interfacial environment shapes two disparate problems: how ice adheres to solids and how emulsions form and persist. I will begin […]
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Capturing path- and rate-dependent behaviors of solids, such as creeping, plastic deformation, damage, and fracture, often requires interpreting and quantifying relationships among the histories of variables, such as dislocation density and porosity. This relational information is then represented by mathematical models composed of differentiable functions. In this talk, we explore (1) how these relationships can […] |
4 events,
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Spectral gradient methods, such as the recently popularized Muon algorithm, are a promising alternative to standard Euclidean gradient descent for training deep neural networks and transformers, but it is still unclear in which regimes they are expected to perform better. In this talk, I’ll argue that spectral gradient methods perform well because they are less […]
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This dissertation explores non-Hermitian control as a unified framework for photonic switching and reconfigurable light routing. First, by harnessing gain–loss modulation and parity–time symmetry breaking in hybrid III–V/silicon platforms, a non-blocking photonic switching architecture is proposed and experimentally demonstrated. The resulting devices exhibit ultrafast switching dynamics, compact footprints, and broadband operation, addressing key limitations of […]
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Recent advances in generative AI have demonstrated the power of scaling: large language and vision models trained on internet-scale data now exhibit remarkable capabilities in perception, generation, and reasoning. These successes have inspired growing interest in bringing […] |
3 events,
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Zoom link: https://upenn.zoom.us/j/98220304722 Learning in dynamical systems is a fundamental challenge underlying modern sequence modeling. Despite extensive study, efficient algorithms with formal guarantees for general nonlinear systems have remained elusive. This talk presents a provably efficient framework for learning in any bounded and Lipschitz nonlinear dynamical system, establishing the first sublinear regret guarantees in a dimension-free setting. Our […]
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Membranes play a vital role in a variety of physiological processes. Recreating these processes outside of the cell will allow us to better understand them as well as design an entirely new class of materials that can sense, transport, or target important biological signals and molecules. In this talk, I will present our recent work […] |
3 events,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT A hallmark of human vision is the ability to reason about the physics of the world: we can infer the shape of the object, how light reflects off the object, and how the object deforms under force. Yet today’s AI systems still lack […]
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Diamond is a promising semiconductor‑industry material due to its exceptional wear resistance, chemical inertness, and thermal conductivity. However, using polycrystalline diamond as a contact coating for nanometer‑precision positioning introduces challenges rooted in its fundamental crystal properties. This ASML‑linked research investigates how friction, wear, and surface morphology of polished microcrystalline diamond coatings influence their suitability for […]
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Abstract: Data-driven reduced-order models often struggle with high-dimensional nonlinear systems sensitive to low-variance coordinates, which are typically truncated. To address this, we use ideas from balanced truncation and active subspaces to identify low-dimensional coordinate systems that balance adjoint-based sensitivity information with state variance along trajectories. Our method, analogous to balanced truncation, replaces system Gramians with […] |
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Ascending thoracic aortic aneurysm (ATAA), an enlargement of the aorta near its exit from the heart, is largely harmless unless a vessel wall failure event occurs. A failure event, however, is life-threatening and would best be prevented by surgical intervention before the tissue fails. Surgical intervention, while effective, is also costly and dangerous, so the […] |
5 events,
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Flexible mechanical metamaterials are engineered structures whose unique geometries allow them to display remarkable behaviors, especially in the nonlinear regime. These systems hold promise for enabling the next generation of smart materials and devices, offering capabilities such as shape morphing, programmable nonlinear responses, and energy manipulation. By embedding programmable mechanics, shape-shifting functions, and computational abilities […]
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT |
2 events,Inefficiencies in current agriculture practices result in the overuse of scarce resources, while limiting achievable crop production. Precision agriculture systems can lead to a more judicious use of agriculture resources and enable higher crop yield. This presentation will focus on the design, development and demonstration of a radio-frequency, long-range, passive sensing platform that enables low-cost […]
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Zoom link: https://upenn.zoom.us/j/98220304722 Score-based diffusion models can be sampled efficiently by reformulating the reverse dynamics as a deterministic probability flow ODE and integrating it with high-order solvers. Since the score function is typically approximated by a neural network, the overall sampling accuracy depends on the interplay between score regularity, approximation error, and numerical integration […] |
2 events,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT There are two dominant approaches to designing intelligent robots. One, typified by language behavior models, leverages unstructured deep neural networks and learning from demonstration to generate behavior. These approaches have had several impressive successes but face scaling, trust, and explainability challenges. The second […]
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*****THIS EVENT WAS RESCHEDULED DUE TO INCLEMENT WEATHER***** Rubbery polymer networks, including elastomers and hydrogels, are increasingly employed in advanced applications such as biomedical implants, drug delivery systems, and smart sensors and actuators. Their macroscopic mechanical properties, such as stiffness, strength, and stretchability, are largely governed by network-level features, including polymer chain length distribution, crosslink […] |
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Abstract: Proteins containing intrinsically disordered regions (IDRs) can undergo multivalent interactions that promote phase separation to form mesoscale condensates that function as membraneless organelles. As subcellular compartments, condensates hold promise as reaction vessels for biochemical applications in vitro, in protocells, and in living cells. However, precise valency control and multi-phase sub-compartmentalization are still inaccessible. This […] |
4 events,For nearly two decades, low-dimensional media have promised to produce atomically-thin optical devices. However, making optical devices in the deep-subwavelength regime requires techniques to confine light for efficient light-matter interactions. One approach is to pattern a metasurface to create a cavity mode, but the effectiveness of this mode can be enhanced by a resonance within […]
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Mechanical metamaterials offer unique opportunities to focus or dissipate energy through controlled wave dynamics. I will first present experimental studies of wave localization in one-dimensional nonlinear lattices, where we observed highly concentrated rogue-wave responses that uncover new pathways for energy focusing. I will then discuss origami-inspired Resch-patterned metamaterials, which utilize multimodal deformation to adaptively bifurcate […]
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ESE Guest Seminar – “From glass to gigapixels: charting the next decade of AI in anatomic pathology”
ESE Guest Seminar – “From glass to gigapixels: charting the next decade of AI in anatomic pathology”
Pathologists have historically evaluated glass slides of excised tissue under a microscope to assess cancer and other disease. Over the last few years, the field has faced an inflection point where glass slides can be digitized, creating images greater than 10 gigapixels in size which are navigated like Google Maps. This enables pathologists to transform […] |
3 events,
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We discuss discrete diffusion models that offer a unified framework for jointly modeling categorical data such as text and images. We present a new model that we have developed for language generation called the Anchored Diffusion Language Model (ADLM). ADLM is grounded in a novel two-stage framework that first predicts distributions over important tokens via […]
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This presenter is one of the winners of the 2025 GRASP vote for internal PhD or postdoc SFI Speakers! This week's speaker will be presenting virtually. This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Building general-purpose robots remains fundamentally constrained by data scarcity and […]
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Abstract: Biological systems are inherently asymmetric, arising from chemical isomer specificity that propagates from metabolite chirality to higher-order structure and function, with profound consequences for the development of pharmaceuticals, fragrances, and agrochemicals. Yet, modern isomer analysis relies on slow and resource-intensive chromatography, limiting the deep characterization of biochemical systems. In this seminar, I will present […] |
2 events,
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Zoom link: https://upenn.zoom.us/j/98220304722 Large language models are capable of in-context learning, the ability to perform new tasks at test time using a handful of input-output examples, without parameter updates. We develop a universal approximation theory to elucidate how transformers enable in-context learning. For a general class of functions (each representing a distinct task), we […]
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Professor Rylie Green is the Sir Leon Bagrit Chair in Bioengineering at Imperial College London. Her research focuses on polymer bioelectronics and regenerative neural interfaces, with the goal of developing materials and devices that enable seamless communication between electronic systems and the nervous system. Her group develops electroactive polymer biomaterials, biohybrid neural interfaces, and fully […] |
3 events,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT Robots in factories are still largely limited to structured environments with known object models. How can we bring robots into the more diverse, unstructured settings of our daily lives, where objects may be deformable or articulated and vary widely in shape and appearance, […]
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Tom Eliaz, Co-Founder of Bedrock Robotics (Penn Engineering Class of 2002), shares his journey and learnings from Penn and a career at IBM, multiple startups and exits, public company leadership, and now to co-founding an autonomous equipment company for construction automation. Zoom Link: https://upenn.zoom.us/j/95178768949
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Abstract: Active matter consists of particles that do work on their environment, for example by propelling themselves through a solvent. Fluids made from many interacting self-propelled particles have become popular as models of non-equilibrium matter: they are challenging for theory and computation because their steady states cannot be derived by minimizing a free energy, nor […] |
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1 event,
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Join us for an Energy Week panel featuring: Featuring Panelists: Deep Jariwala Associate Professor, Peter and Susanne Armstrong Distinguished Scholar, Electrical and Systems Engineering, Materials Science and Engineering Anthony Shoji Hall Associate Professor, Materials Science and Engineering Aleksandra Vojvodic Professor, Chemical and Biomolecular Engineering, Director of Penn Institute for Computational Science (PICS) Register Now |
2 events,
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Optimized thermochemical, thermomechanical, and thermal properties of high temperature materials are key for successful performance of propulsion systems and hypersonic leading edge systems. In this presentation fundamental studies of materials for these two aerospace applications will be described. In the first case, properties of novel rare-earth containing high temperature coatings for aero turbine engine components […]
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Nano- and microstructured layered films can serve as thermal insulators by minimizing continuous contact area, maximizing phonon scattering in the bulk, and introducing interfacial thermal resistances. Unlike commonly used insulators that consist of porous, fibrous, netted, and aerogel (nanoporous) materials and are often mechanically weak, nano- and microstructured layered films can show superior mechanical stiffness […] |
4 events,
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PCI together with SEAS is hosting a seminar by Jason Smith, Managing Partner at Longview Innovation, who will discuss the trends in startups developing emerging university technology. All Penn faculty, post-docs, students and staff are welcome, and a light lunch will be provided. Please register here!
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Deep reinforcement learning (RL) is a promising tool for control of complex physical systems such as power and energy systems, yet its deployment is often hindered by the lack of explicit stability guarantees. In this talk, I will present a stability-constrained RL framework, where we show that monotonicity in control policies implies Lyapunov stability in […]
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Robotics research is advancing at an unprecedented pace, reaching scales that were difficult to imagine just a few years ago. However, as systems grow larger and more complex, effective research and engineering increasingly depend on having the […] |
1 event,
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Zoom link: https://upenn.zoom.us/j/98220304722 Can multi-step reasoning be learned from data? We investigate this question in the context of a simple function composition task. We prove that this task is hard to learn in the Statistical Query model, but is easy to learn with transformers under various forms of curriculum learning. This is joint work […] |
1 event,
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This event will be in-person ONLY in Wu and Chen Auditorium. ABSTRACT Black box methods such as the Turing Test are no longer adequate for evaluating AI models. Quantifying the structure and similarity of high-dimensional neural representations are essential for better understanding and training of large neural network models. Statistical insights can be gained by […] |
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