We study the geometric mechanics of origami assemblages and investigate how geometry affects behavior and properties. Understanding origami from a structural standpoint allows for conceptualizing and designing feasible applications across scales and disciplines of engineering. We review the basic mathematical rules of origami and use 3D-printed origami legos to illustrate those concepts. We then present […]
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Recent advances in engineering science have led to new classes of medical devices with emergent mechanical, electrical, and thermal properties that offer new opportunities for interfacing with living cells. I will discuss conceptual advances in microfabrication, device physics, power transfer and microscale transport phenomena that enable novel biosensors and cell delivery systems, with an emphasis […]
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ABSTRACT: Flow matching models learn a (possibly stochastic) mapping between source and target distributions. Common paradigms include diffusion models, score matching models, and continuous normalizing flows. In this talk I will first present methods for improved training of flow matching models using ideas from optimal transport. I will then show how these improved methods can […] |
4 events,
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ABSTRACT: Artificial Intelligence is being increasingly relied on in safety-critical domains. But the predictive models underlying these systems are notoriously brittle, and trustworthy deployment remains a significant challenge. In this talk, I give an overview of my work towards a rigorous foundation for robust machine learning (ML). Using a case study of invariant prediction, we […]
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This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Why has autonomous driving, a task demanding significant intelligence, not met the high expectations set by many? Which hurdles have turned out to be more formidable than expected, and how can we refine our testing methodologies for […]
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Although machine intelligence is taking over the world, its current digital electronic platform is very inefficient in terms of energy consumption. Switching to analogue computation, which function more like human brains than digital computers, will allow enhancing the energy efficiency by several orders of magnitude. Optics presents a particularly promising platform for analogue AI; however, […] |
3 events,
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Much is known about oxygen interaction with metal surfaces and about the macroscopic growth of thermodynamically stable oxides. At present, however, the transient stages of oxidation - from nucleation of the metal oxide to formation of the thermodynamically stable oxide - represent a scientifically challenging and technologically important terra incognito. These issues can only be […]
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The rich set of mechanoreceptors found in human skin offers a versatile engineering interface for transmitting information and eliciting perceptions, potentially serving a broad range of applications in patient care and other important industries. Targeted multisensory engagement of these afferent units, however, faces persistent challenges, especially for wearable, programmable systems that need to operate adaptively […]
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Note that this seminar will be held in Wu & Chen Auditorium (Levine 101). Humans and animals exhibit a range of interesting behaviors in complex environments, and it is unclear how the brain reformats dense sensory information to enable these behaviors. To gain traction on this problem, new recording paradigms now facilitate the ability to […] |
2 events,
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Many relevant engineering fluid dynamics problems, such as turbulent flow over an airplane or transport processes in geophysical flows, contain wall-bounded regions that form boundary layers. Oftentimes, numerical and experimental studies are simplified by using smooth surfaces. This simplification has allowed us to gain a greater understanding of near-wall processes for many flows of interest, […]
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This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT After 39 years as a faculty member with continuous NSF support, the speaker has graduated his last PhD students, closed his lab, and turned 100% to teaching. From June 2016 through June 2021, he led Michigan’s Robotics […] |
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"Can a cell learn?" Ever since the genetic code was deciphered, we have increasingly come to view cellular control through the lens of genetic determinism. In this paradigm, a cell's fate is already written into its DNA, which is in turn shaped by Darwinian evolution over the course of many generations. At the same time, […] |
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6 events,
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ABSTRACT: "Trustworthy Machine Learning" has become a buzz-word in recent years. But what exactly are the semantics of the promise that we are supposed to trust? In this talk we will make a proposal, through the lens of downstream decision makers using machine learning predictions of payoff relevant states: Predictions are "Trustworthy" if it is in the interests of the downstream decision […]
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Accurate prediction of high-Reynolds-number wall-bounded turbulent flows is essential for the understanding and flow control of many engineering applications such as aircraft, turbomachinery, and marine vehicles. Additionally, most practical flows exhibit nonequilibrium effects such as pressure gradient, flow separation, and mean three-dimensionality. However, the direct numerical simulation (DNS) of high-Reynolds-number wall-bounded turbulent flows is not […]
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: Generative priors are effective countermeasures to combat the curse of dimensionality, and enable efficient learning and inversion that otherwise are ill-posed, in data science. This talk begins with the classical low-rank prior, and introduces scaled gradient descent (ScaledGD), a simple iterative approach to directly recover the low-rank factors for a wide range of matrix […] |
1 event,
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Air conditioning accounts for nearly 20% of the total electricity used in buildings globally and cooling energy demand is predicted to significantly increase over the next decades due to urbanization, population growth, and global warming. Heat stress is a major environmental justice concern, disproportionally impacting disadvantaged communities. What are the paths to reduce the massive energy […] |
5 events,
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Many natural materials achieve excellent combinations of mechanical properties through their micro- and nano-scale structures, which leverage a level of complexity currently unmatched in engineering design. Recent advances in digital manufacturing have enabled the introduction of these fine-scale architectures to improve the mechanical properties of materials, but their intricacy still lags far behind that of […]
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This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT This talk introduces dynamic game theory as a natural modeling tool for multi-agent interactions ranging from large, abstract systems such as ride-hailing networks to more concrete, physically-embodied robotic settings such as collision-avoidance in traffic. We present the […]
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Materials properties are governed by the structure and dynamics of the bonds between their constituent atoms. In addition to covalent, metallic, and ionic interactions that we typically think about, lone pair electrons can result in non-trivial directional interactions in materials. I will discuss molecular interactions involving lone pairs in materials, focusing on results from molecular […] |
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5 events,
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Multiferroic micro-electromechanical systems (MEMS) enable small, room temperature, low power magnetic sensing and wireless power transfer (WPT) in biomedical applications. Current biomagnetic sensing relies on sensitive magnetometers like superconducting quantum interference devices (SQUIDs), but their reliance on cryogenic temperatures is undesirable. This thesis presents the theory, design, microfabrication, and characterization of multiferroic MEMS magnetic […]
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The Department of Bioengineering at the University of Pennsylvania and Dr. Nat Dyment are pleased to announce the Doctoral Dissertation Defense of Tim Kamalitdinov. Title: The Origin and Factors Affecting Differentiation of Progenitor Cells in Tendon-to-Bone Integration Date: April 16, 2024 Time: 9:00 AM Location: SCTR (Smilow Center for Translational Research) 12-146AB The public is welcome […]
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Over the past few decades, significant contributions have been made by engineers to healthcare. The successful translation of fundamental engineering concepts has helped improve patient care and diagnosis. This impact has been particularly evident in the field of cardiovascular medicine where the roles of fluid and solid mechanics, and imaging are critical. In ~45 years […] |
6 events,
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Join Penn Engineering faculty to learn how to harness the power of AI for innovation. Dean Vijay Kumar will moderate a discussion with Michael Kearns, Professor and National Center Chair in Computer and Information Science (CIS); Surbhi Goel, Magerman Term Assistant Professor in CIS; and René Vidal, Rachleff University Professor, with joint appointments in Electrical […]
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ABSTRACT: The rapid progress made over the last few years in generating linguistically coherent natural language has blurred, in the mind of many, the difference between natural language generation, understanding, and the ability to reason with respect to the world. Nevertheless, robust support of high-level decisions that depend on natural language understanding, and one that […]
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The Department of Bioengineering at the University of Pennsylvania and Dr. Yong Fan are pleased to announce the Doctoral Dissertation Defense of Yuemeng Li. Title: Deep Learning for Unpaired Domain Adaptive Medical Image Segmentation Date: April 17, 2024 Time: 1:00PM-3:00PM Location: BRB Auditorium Zoom link The public is welcome to attend. |
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Even as they continue to improve, legged robots pale in comparison to their biological counterparts. This discrepancy is at least partly due to robots possessing an order of magnitude fewer degrees of freedom. In fact, most dynamically capable quadrupedal robots lack any degrees of freedom in the torso, opting instead for a simpler, single, rigid […]
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Recipient of the 2024 Benjamin Franklin Medal in Chemistry
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Soft synthetic and natural polymeric-based materials offer particular new avenues for the design and fabrication of materials and devices. Engineering the molecular and geometrical structures of the constituent materials, together with utilizing their ability to sustain large deformations enables materials and designs with novel properties and functional behavior. We begin with the development of physically-based […] |
4 events,
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This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT A fundamental element of effective operation of autonomous systems is the need for appropriate sensing and processing of measurements to enable desired system actions. Model-based methods provide a clear framework for careful proof of system capabilities but suffer […]
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Join the Graduate Association of Bioengineers (GABE) for the 2024 Graduate Research Symposium! When: April 19, 2024 from 12:30-6:00 PM Where: The Singh Center for Nanotechnology What: Keynote by Dr. David Kaplan; BE graduate student posters and presentations; food buffet and reception; BE swag and awards. Registration is free and is open to anyone affiliated […]
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Low (or ideally zero) numerical dissipation is always critical for high-fidelity scale-resolving flow simulations, as numerical dissipation prevents the physics of inviscid kinetic energy and entropy conservation, which is an essential attribute of compressible turbulence. However, contrary to the requirement, numerical schemes in compressible flow heavily rely on numerical dissipation for stable computation, preventing high-fidelity […] |
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In recent years, micro-robotic membranes have attracted increasing interest due to their unique properties and potential applications in various fields. The optical properties of these membranes have been playing a crucial role in the design and development of optical devices such as reflective displays with customizable colors. The primary challenge to understanding the mechanical-spectral interaction […] |
3 events,
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Superhydrophobic surfaces, formed by air entrapment within the cavities of hydrophobic solid substrates, offer a promising potential for hydrodynamic drag reduction. In several of the prototypical surface geometries the flows are two-dimensional, governed by Laplace’s equation in the longitudinal problem and the biharmonic equation in the transverse problem. Moreover, low-drag configurations are typically associated with […]
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Learn about sustainable products and practices your caterer can implement to reduce waste, minimize plastic and lower carbon footprint. Planet-friendly menu Plastic-alternative packaging and utensils Nutrition label for customized eating preferences Vendor engagement beyond delivery.
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Robots struggle to understand object properties like shape, material, and semantics due to limited prior knowledge, hindering manipulation in unstructured environments. In contrast, humans learn these properties through interactive multi-sensor exploration. This work proposes fusing visual and tactile observations into a unified Gaussian Process Distance Field (GPDF) representation for active perception of object properties. While […] |
5 events,
Featured
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Featured
Abstract The richness of liquid-liquid phase separation behavior in mixtures of oppositely-charged polyelectrolyte has been greatly illuminated recently in the polymer physics literature. Precise determinations of phase diagrams, measurements of interfacial tension, scattering measurements of chain configurations, and increasingly insightful theory are all producing a clearer understanding of these phenomena. In parallel, physics is also […]
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This talk will explore methods for accelerating numerical optimization constrained by transient problems using parallelism. Two types of transient problems will be considered. In the first case training algorithms for Neural ODEs will be discussed. Neural ODEs are a class of neural network architecture where the depth of the neural network (the layers) is modeled […]
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ABSTRACT: Language models work well, but they are far from trustworthy. Major open questions remain on high-stakes issues such as detecting benchmark contamination, identifying LM-generated text, and reliably generating factually correct outputs. Addressing these challenges will require us to build more precise, reliable algorithms and evaluations that provide guarantees that we can trust. Despite the […] |
2 events,
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Despite the recent flurry of work employing machine learning to develop surrogate models to accelerate scientific computation, the "black-box" underpinnings of current techniques fail to provide the verification and validation guarantees provided by modern finite element methods. In this talk we present a data-driven finite element exterior calculus for building accelerated reduced-order models of multiphysics […]
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Optical coherence tomography (OCT) is a technology invented in 1991 to image small critical tissue structures throughout the body with micrometer resolution. It is widely used in the management of eye and coronary heart diseases. In 2023, OCT received broad attention when its inventors received the prestigious Lasker-DeBakey Clinic Medical Research Award and the National […] |
4 events,
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This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT Foundation models, trained on vast and diverse data encompassing the human experience, are at the heart of the ongoing AI revolution influencing the way we create, problem solve, and work. These models, and the lessons learned from their […]
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Mucus, a complex fluid produced by every living organism, has multiple essential functions including acting as an effective barrier layer in various bodily processes, many of which involve important rheological (flow) and tribological (adhesive, lubricative) functions. The primary component of mucuses are mucins – highly glycosylated, linear polypeptides. Understanding how the structure and properties of […]
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Entrepreneurship Seminar Series: Pathways to Impact This session brings together a panel of current and former faculty and PhDs that have brought their technology to market and have worked in both academia and commerce. Panelists will discuss the opportunities and approaches they took to create companies, leverage experience in academia, and drive research into commercial […] |
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Due to the elevated expenditure of fossil fuels and their adverse impacts on climate change resulting from greenhouse gas emissions, it is imperative to integrate clean energy sources alongside fossil fuels. This study presents the design, simulation, and optimization of an integrated system comprising solar photovoltaics, micro-cogeneration, and electrical energy storage to achieve energy self-sufficiency […] |
2 events,
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I will discuss the collective modes that spontaneously emerge in ciliary carpets and fish schools. In both systems, the fluid medium couples the motion of individuals in the group. Flow coupling is dominated by viscous forces in cilia and by inertial interactions in fish. I will show, numerically and analytically in the continuum limit, that […]
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AI Month at Penn concludes with closing remarks by Vijay Kumar, Nemirovsky Family Dean, Penn Engineering. This will be followed by a panel discussion moderated by Susan Davidson, Weiss Professor, Computer and Information Science (CIS). Panel guests include: Zachary Ives, Adani President’s Distinguished Professor, CIS; George Pappas, UPS Foundation Professor of Transportation, Electrical and Systems […] |
1 event,
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ABSTRACT: Research in lifelong or continual machine learning has advanced rapidly over the past few years, primarily focusing on enabling learned models to acquire new tasks over time while avoiding catastrophic forgetting of previous tasks. However, autonomous systems still lack the ability to rapidly learn new generalizable skills by building upon and continually refining their […] |
1 event,
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Please register at the event webpage, where you will also find abstracts and bios for the speakers. Invited talks include: Exploring Polymer Blend Directed Self-Assembly Using Autonomous X-Ray Scattering Greg Doerk, PhD, Brookhaven National Lab Machine-Learning-Guided Discovery of New Electrochemical Reactions Andrew Zahrt, PhD, University of Pennsylvania Ask an Expert about ChatGPT Chris Callison-Burch, PhD, […] |
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