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DTSTART;TZID=America/New_York:20241104T140000
DTEND;TZID=America/New_York:20241104T160000
DTSTAMP:20260403T162544
CREATED:20241007T183136Z
LAST-MODIFIED:20241007T183136Z
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SUMMARY:BE Doctoral Dissertation Defense: "Spectral CT thermometry for real-time\, non-invasive temperature monitoring of thermal ablation" (Leening Liu)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Peter Noel are pleased to announce the Doctoral Dissertation Defense of Leening Liu.\n\n\nTitle: Spectral CT thermometry for real-time\, non-invasive temperature monitoring of thermal ablation\n\nDate: November 4\, 2024\nTime: 2:00 PM\nLocation:  Reunion Auditorium\, John Morgan Building\n\nZoom info:\nTopic: Leening Liu’s Dissertation Defense\nTime: November 4\, 2024 2:00 PM Eastern Time (US and Canada) \nJoin Zoom Meeting\nhttps://upenn.zoom.us/j/9712621454?omn=99923084242.\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-spectral-ct-thermometry-for-real-time-non-invasive-temperature-monitoring-of-thermal-ablation-leening-liu/
LOCATION:JMB Reunion Auditorium\, 3620 Hamilton Walk\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241104T101500
DTEND;TZID=America/New_York:20241104T111500
DTSTAMP:20260403T162544
CREATED:20241023T154238Z
LAST-MODIFIED:20241023T154238Z
UID:10008144-1730715300-1730718900@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Digital Twin Development using Physics-Informed Neural Operators"
DESCRIPTION:Digital twins are virtual models of physical systems that allow for more computationally cost-effective evaluation and optimization. Building digital twins often involves machine learning techniques that integrate data with underlying physical laws. In this seminar\, I’ll explore two such techniques: Physics-Informed Neural Networks (PINNs) and operator learning. First\, I’ll discuss the formulation of PINNs and how they can be utilized for solving forward and inverse problems. I’ll particularly highlight an application of PINNs for solving non-trivial parameter inference problems in viscoelastic fluids. Next\, I’ll introduce operator learning which aim to learn mappings between function spaces. I’ll explore effective architecture choices for building powerful operator learning methods and present some applications and advantages of operator learning in solving partial differential equations.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-digital-twin-development-using-physics-informed-neural-operators/
LOCATION:Towne 307\, 220 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241101T103000
DTEND;TZID=America/New_York:20241101T114500
DTSTAMP:20260403T162544
CREATED:20240909T153102Z
LAST-MODIFIED:20240909T153102Z
UID:10008091-1730457000-1730461500@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP on Robotics: Tess Smidt\, Massachusetts Institute of Technology\, "Recent applications of Euclidean neural networks to understand and design atomistic systems"
DESCRIPTION:This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nAtomic systems (molecules\, crystals\, proteins\, etc.) are naturally represented by a set of coordinates in 3D space labeled by atom type. This poses a challenge for machine learning due to the sensitivity of coordinates to 3D rotations\, translations\, and inversions (the symmetries of 3D Euclidean space). Euclidean symmetry-equivariant Neural Networks (E(3)NNs) are specifically designed to address this issue. They faithfully capture the symmetries of physical systems\, handle 3D geometry\, and operate on the scalar\, vector\, and tensor fields that characterize these systems. \nE(3)NNs have demonstrated state-of-the-art performance on diverse atomistic benchmarks\, such as small molecule properties\, protein-ligand binding\, and force prediction for heterogeneous catalysis. These networks combine neural network operations with insights from group representation theory. Their success stems from a rigorous foundation\, making them more robust\, data-efficient\, and capable of generalization compared to invariant or non-equivariant neural networks. \nIn this talk\, I will provide an overview of recent applications of E(3)NNs in understanding and designing materials. I will also discuss the expansion of these methods’ applicability to new domains and data modalities. Finally\, I will explore open questions regarding the expressivity\, data-efficiency\, and trainability of methods that leverage invariance and equivariance.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-on-robotics-tess-smidt-massachusetts-institute-of-technology-recent-applications-of-euclidean-neural-networks-to-understand-and-design-atomistic-systems/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241031T103000
DTEND;TZID=America/New_York:20241031T120000
DTSTAMP:20260403T162544
CREATED:20241027T153136Z
LAST-MODIFIED:20241027T153136Z
UID:10008149-1730370600-1730376000@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Quantum Materials: A View from the Lattice"
DESCRIPTION:Connecting theoretical models for exotic quantum states to real materials is a key goal in quantum materials science.  The structure of the crystalline lattice plays a foundational role in this pursuit in the subfield of quantum material synthesis.  We here revisit this long-standing perspective in the context low dimensional emergent electronic phases of matter\, including the realization of model two-dimensional topological and correlated electronic phenomena.  Along the way\, we discuss how to define a quantum material\, and how this definition has evolved in recent years. Finally\, we comment on the perspective for realizing further two-dimensional model systems in complex material structures and connections to new paradigms for programmable quantum matter. \n 
URL:https://seasevents.nmsdev7.com/event/mse-seminar-quantum-materials-a-view-from-the-lattice/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241030T150000
DTEND;TZID=America/New_York:20241030T160000
DTSTAMP:20260403T162544
CREATED:20241024T162108Z
LAST-MODIFIED:20241024T162108Z
UID:10008146-1730300400-1730304000@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP SFI: Jonathan Michaux\, University of Michigan\, “Spheres Are All You Need: Risk-Aware Trajectory Planning in Radiance Fields”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nSafe and efficient motion planning is crucial for robots operating in dynamic and unstructured environments. To accomplish this\, one must address key challenges. First\, robots must understand the scene geometry to prevent collisions that could harm humans or damage any nearby objects. Second\, motion plans must be generated in real-time to ensure that the robot can adapt to sudden changes in its environment. This talk presents a novel approach to trajectory optimization that leverages reachability analysis and 3D Gaussian Splatting for real-time planning in radiance fields. This talk first describes a novel spherical representation that overapproximates a robot’s parameterized reachable set. Next\, a method is derived that rigorously upper-bounds the probability of collision between the robot’s reachable set and a normalized Gaussian Splatting model. Finally\, this probability bound is formulated as a chance constraint in a nonlinear optimization problem. This approach\, which generates probabilistically-safe behaviors in real-time\, is demonstrated in simulation and on a real-world serial robot manipulator.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-sfi-jonathan-michaux/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241030T120000
DTEND;TZID=America/New_York:20241030T131500
DTSTAMP:20260403T162544
CREATED:20240709T174026Z
LAST-MODIFIED:20240709T174026Z
UID:10008012-1730289600-1730294100@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "Advancing Diffusion Models for Text Generation"
DESCRIPTION:Abstract: \nTransformer-based language models have undoubtedly become the dominant and favorite architecture for language generation of our time. However\, although they provide impressive text quality\, they tend to be hard to control. In the domain of image synthesis\, on the other hand\, Denoising Diffusion Models (DDM) are the dominant approach\, shining with unprecedented quality and control. The application of DDMs to discrete domains like language remains a challenging open problem. This talk addresses this challenge head-on. First\, we introduce Latent Diffusion for Language Generation that enables DDMs for text generation in the latent space of text auto-encoders\, enabling the generation of fluent text through latent diffusion. Further\, we utilize diffusion models to generate semantic proposals that guide autoregressive text decoders. The latter approach combines the fluency of autoregression with the plug-and-play control of diffusion. Through these works\, we demonstrate how diffusion models can be adapted to language\, opening new avenues for flexible and controllable language generation systems. \nZoom Link (if unable to attend in-person): https://upenn.zoom.us/j/93913926936
URL:https://seasevents.nmsdev7.com/event/asset-seminar-kilian-weinberger-cornell-university/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241029T153000
DTEND;TZID=America/New_York:20241029T163000
DTSTAMP:20260403T162544
CREATED:20241023T154904Z
LAST-MODIFIED:20241023T154904Z
UID:10008145-1730215800-1730219400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Scaling Machine-Checkable Systems Verification in Coq"
DESCRIPTION:System software like operating systems and hypervisors forms the critical backbone of our computing infrastructure. However\, due to their size and complexity\, these systems often contain vulnerabilities that can compromise security. Formal verification offers a solution by mathematically proving software correctness\, but its adoption is hindered by the substantial effort required to create these proofs.\n\nIn this talk\, I will introduce Spoq\, a highly automated verification framework designed to dramatically reduce the proof effort in verifying system software. Spoq leverages LLVM to automatically translate C code—including full C semantics like macros\, inline assembly\, and compiler directives—into Coq\, a proof assistant for formal verification. This automation eliminates the need for manual modification of source code prior to verification. Spoq leverages a layering proof strategy and introduces novel Coq tactics and transformation rules to automatically generate layer specifications and refinement proofs to simplify verification of concurrent system software. Spoq also supports easy integration of manually written layer specifications and refinement proofs. We applied Spoq to verify a multiprocessor KVM hypervisor implementation. Verification using Spoq required 70% less proof effort than the manually written specifications and proofs to verify an older implementation. Furthermore\, the proofs using Spoq hold for the unmodified implementation that is directly compiled and executed.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-scaling-machine-checkable-systems-verification-in-coq/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241029T110000
DTEND;TZID=America/New_York:20241029T120000
DTSTAMP:20260403T162544
CREATED:20240821T142755Z
LAST-MODIFIED:20240821T142755Z
UID:10008069-1730199600-1730203200@seasevents.nmsdev7.com
SUMMARY:ESE Fall Seminar - "Power Electronics is Cool. Trends and Opportunities for the Coming Decades"
DESCRIPTION:For the past two decades\, power management and delivery has been a bottleneck\, limiting the size and performance of a range of applications from performance computing to mobile phones and wearables. In the coming decades\, power electronics will become the ‘glue’ of the modern energy system network. With electronics embedded deeply into this network\, well beyond the ‘grid edge\,’ there will be new opportunities for control\, management\, diagnostics\, and system integration.  This talk will motivate the need for 2+ decades of power electronic research to solve key application challenges\, circuit and passive component limitations. There is a need to explore architectures well beyond conventional ‘buck’ and ‘boost’ converters; more specifically\, topologies that leverage next-generation higher-energy-density passives including capacitors and piezoelectric resonators. We will discuss past efforts that have broken previous barriers in performance and size as well as future trends and opportunities to continue breaking these barriers.
URL:https://seasevents.nmsdev7.com/event/ese-fall-seminar-title-tbd-21/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241029T101500
DTEND;TZID=America/New_York:20241029T111500
DTSTAMP:20260403T162544
CREATED:20241007T181131Z
LAST-MODIFIED:20241007T181131Z
UID:10008124-1730196900-1730200500@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Engineering Innovation in Maternal and Fetal Health: The Biomechanics of High-Risk Pregnancies"
DESCRIPTION:The reproductive soft tissues that support the fetus undergo some of the most dramatic and unique growth and remodeling events in the human body. The uterus and fetal membrane must grow and stretch during pregnancy to accommodate the fetus. Simultaneously\, the cervix must remodel and be a mechanical barrier to keep the fetus within the uterus. All three tissues must withstand mechanical forces to protect\, support\, and maintain an optimal growth environment for the developing baby. Then\, in a reversal of roles\, ideally nearing term\, the uterus begins to contract and the cervix deforms to allow for a safe delivery. The magnitude of biomechanical stress and stretch of these soft tissues supporting the fetus is thought to control physiologic processes that regulate tissue growth\, remodeling\, contractility\, and rupture\, and it is generally hypothesized that these mechanical signals are clinical cues for normal labor and preterm birth\, a major long-lasting public health problem with heavy emotional and financial consequences. In this talk I will reveal what we know about the soft tissue mechanics of pregnancy. I will present computational models of pregnancy based on ultrasonic anatomical measurements and cervical stiffness measurements from a novel aspirator clinical tool. I will examine the mechanical environment of pregnancy by comparing biomechanical models of patients clinically considered at low- and high-risk of preterm birth. The high-risk cohort is a subset of patients who participated in the TOPS clinical trial at Columbia University Irving Medical Center\, an NIH-funded clinical trial to examine the efficacy of the pessary in reducing preterm birth in singleton pregnancies. Through this experimental and modeling effort I aim to hypothesize which factor or combination of factors may be responsible for clinically-observed mechanical dysfunction in pregnancy.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-engineering-innovation-in-maternal-and-fetal-health-the-biomechanics-of-high-risk-pregnancies/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241025T140000
DTEND;TZID=America/New_York:20241025T150000
DTSTAMP:20260403T162544
CREATED:20241021T140143Z
LAST-MODIFIED:20241021T140143Z
UID:10008141-1729864800-1729868400@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium with Daniel Tartakovsky: Information Theory of Multiscale Simulations
DESCRIPTION:We present an information-theoretic approach for integration of multi-resolution data into multiscale simulations.  Fine-scale information can comprise observational data and/or simulation results related to both system states and system parameters. It is aggregated into its coarse-scale representation by setting a probabilistic equivalence between the two scales\, with parameters that are determined via minimization of observables error and mutual information across scales. The same quantities facilitate the use of coarse-scale data to constrain compatible fine-scale distributions. In the second part of this talk\, we leverage the information-geometric properties of the statistical manifold to reduce predictive uncertainty via data assimilation. Specifically\, we exploit the information-geometric structures induced by two discrepancy metrics\, the Kullback-Leibler divergence and the Wasserstein distance\, which explicitly yield natural gradient descent. The use of a deep neural network as a surrogate model for MD enables automatic differentiation\, further accelerating optimization. The manifold’s geometry is quantified without sampling\, yielding an accurate approximation of the gradient descent direction. Our numerical experiments demonstrate that accounting for the manifold’s geometry significantly reduces the computational cost of data assimilation by both facilitating the calculation of gradients and reducing the number of required iterations.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-with-daniel-tartakovsky-information-theory-of-multiscale-simulations/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241025T103000
DTEND;TZID=America/New_York:20241025T114500
DTSTAMP:20260403T162544
CREATED:20241011T191325Z
LAST-MODIFIED:20241011T191325Z
UID:10008133-1729852200-1729856700@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP on Robotics: Ruslan Salakhutdinov\, Carnegie Mellon University\, "Multimodal AI Agents"
DESCRIPTION:This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nIn recent years\, the rise of Large Language Models (LLMs) with advanced general capabilities has paved the way towards building language-guided agents that can perform complex\, multi-step tasks on behalf of users\, much like human assistants. Building agents that can perceive\, plan\, and act autonomously has long been a central goal of artificial intelligence research. In this talk I will introduce Multimodal AI agents capable of planning\, reasoning\, and executing actions on the web\, that can not only comprehend textual information but also effectively navigate and interact with visual settings I will next present an inference-time search algorithm for agents to explicitly perform exploration and multi-step planning in interactive web environments. Our approach is a form of best-first tree search that operates within the actual environment space\, and is complementary with most existing state-of-the-art agents. Finally\, I will introduce VisualWebArena\, a novel framework for evaluating multimodal autonomous language agents\, and offer insights towards building stronger autonomous agents for both digital and physical environments.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-on-robotics-ruslan-salakhutdinov-carnegie-mellon-university-multimodal-ai-agents/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241024T153000
DTEND;TZID=America/New_York:20241024T163000
DTSTAMP:20260403T162544
CREATED:20241014T144539Z
LAST-MODIFIED:20241014T144539Z
UID:10008134-1729783800-1729787400@seasevents.nmsdev7.com
SUMMARY:CIS Grace Hopper Distinguished Lecture: "OLMo: Accelerating the Science of Language Modeling"
DESCRIPTION:Language models (LMs) have become ubiquitous in both AI research and commercial product offerings. As their commercial importance has surged\, the most powerful models have become closed off\, gated behind proprietary interfaces\, with important details of their training data\, architectures\, and development undisclosed. Given the significance of these details in scientifically studying these models\, including their biases and potential risks\, I argue that it is essential for the research community to have access to powerful\, truly open LMs.  In this talk\, I present our OLMo project aimed at building strong language models and making them fully accessible to researchers along with open-source code for data\, training\, and inference. I describe our efforts in building language modeling from scratch\, expanding their scope to make them applicable and useful for real-world applications\, and investigating a new generation of LMs that address fundamental challenges inherent in current models.
URL:https://seasevents.nmsdev7.com/event/cis-grace-hopper-distinguished-lecture-olmo-accelerating-the-science-of-language-modeling/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241024T120000
DTEND;TZID=America/New_York:20241024T130000
DTSTAMP:20260403T162544
CREATED:20241017T134335Z
LAST-MODIFIED:20241017T134335Z
UID:10008138-1729771200-1729774800@seasevents.nmsdev7.com
SUMMARY:ESE PhD Seminar: "Learning Local Control Barrier Functions for Safety-Critical Hybrid Systems"
DESCRIPTION:Safety-critical control is one of the fundamental problems in autonomous systems. A special class of autonomous systems is the class of hybrid dynamical systems\, which involves both continuous dynamic flow and discrete dynamical mode jumps for state evolution. I will introduce how to synthesize safe controllers for hybrid dynamical systems based on local control barrier functions (CBFs)\, and such a framework enjoys flexibility\, non-conservativeness\, and computational advantage compared with existing safety-critical methods. Then\, I will show how to learn local CBFs for hybrid systems through self-supervision techniques. Finally\, I will briefly share some ideas on learning safe and adaptive controllers in multi-agents systems.
URL:https://seasevents.nmsdev7.com/event/ese-phd-seminar-learning-local-control-barrier-functions-for-safety-critical-hybrid-systems/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241024T103000
DTEND;TZID=America/New_York:20241024T120000
DTSTAMP:20260403T162544
CREATED:20240917T183106Z
LAST-MODIFIED:20240917T183106Z
UID:10008100-1729765800-1729771200@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Kagome Metals and Their Unusual Electronic Properties"
DESCRIPTION:In this talk\, I will discuss new inroads in the study of electronic order within classes of metals built from kagome lattices or networks of corner sharing triangles.  The electronic band structures of these compounds are known to host a series of features such as Dirac crossings\, saddle points\, and flat bands at select carrier fillings.  Tuning the electron filing about these features has the potential to stabilize a variety of exotic electronic states such as orbital magnetism\, bond density wave order\, and unconventional superconductivity; however experimental realization of these states has been a historical challenge.  Recently\, a number of new compounds built from kagome lattices with band fillings near each of these features have been discovered\, and I will provide an overview of progress in studying their anomalous properties.  Particular focus will be given to electronic instabilities realized in kagome metals with their Fermi levels close to the saddle points in their band structures.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-kagome-metals-and-their-unusual-electronic-properties/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241023T153000
DTEND;TZID=America/New_York:20241023T163000
DTSTAMP:20260403T162544
CREATED:20240816T203114Z
LAST-MODIFIED:20240816T203114Z
UID:10008054-1729697400-1729701000@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Backbone Modifications in Peptide Natural Products" (James Link\, Princeton University)
DESCRIPTION:Abstract: \nThe posttranslational modifications (PTMs) in RiPPs (ribosomally synthesized and post-translationally modified peptides) dictate their 3D structure and their bioactivity. An underlying structural feature of many RiPPs is macrocyclization\, installed by a growing number of different enzymatic strategies. Another common class of PTM in RiPPs is backbone modification\, such as the formation of thiazol(in)es and oxazol(in)es. Our group has recently been interested in aspartimidylation\, a backbone modification occurring at Asp residues that installs a metastable succinimide moiety into several different RiPPs. This talk will focus on recent work on the O-methyltransferase enzymes that install aspartimide in lasso peptides\, graspetides\, and a new class of peptides\, the imiditides. The surprising stability of these aspartimide moieties will also be discussed within a kinetic framework. Finally\, the talk will discuss potential chemical and biological ramifications of the aspartimide moiety in RiPPs.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-backbone-modifications-in-peptide-natural-products-james-link-princeton-university/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241023T150000
DTEND;TZID=America/New_York:20241023T160000
DTSTAMP:20260403T162544
CREATED:20241017T192738Z
LAST-MODIFIED:20241017T192738Z
UID:10008140-1729695600-1729699200@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP SFI: Carl Vondrick\, Columbia University\, “Making Sense of the Multimodal World”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nPeople experience the world through modalities of sight\, sound\, words\, touch\, and more. By leveraging their natural relationships and developing multimodal learning methods\, my research creates artificial perception systems with diverse skills\, including spatial\, physical\, logical\, and cognitive abilities\, for flexibly analyzing visual data. This multimodal approach provides versatile representations for tasks like 3D reconstruction\, visual question answering\, and object recognition\, while offering inherent explainability and excellent zero-shot generalization across tasks. By closely integrating diverse modalities\, we can overcome key challenges in machine learning and enable new capabilities for computer vision\, especially for the many upcoming applications where physical interaction are required.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-sfi-carl-vondrick/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241023T120000
DTEND;TZID=America/New_York:20241023T131500
DTSTAMP:20260403T162544
CREATED:20240815T174048Z
LAST-MODIFIED:20240815T174048Z
UID:10008044-1729684800-1729689300@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "Towards Sustainable Artificial Intelligence and Datacenters"
DESCRIPTION:Abstract: \nAs the impact of artificial intelligence (AI) continues to proliferate\, computer architects must assess and mitigate its environmental impact. This talk will survey strategies for reducing the carbon footprint of AI computation and datacenter infrastructure\, drawing on data and experiences from industrial\, hyperscale systems. First\, we analyze the embodied and operational carbon implications of super-linear AI growth. Second\, we re-think datacenter infrastructure and define a solution space for carbon-free computation with renewable energy\, utility-scale batteries\, and job scheduling. Finally\, we develop strategies for datacenter demand response\, incentivizing both batch and real-time workloads to modulate power usage in ways that reflect their performance costs. In summary\, the talk provides a broad perspective on sustainable computing and outlines the many remaining directions for future work. \nZoom Link (if unable to attend in-person): https://upenn.zoom.us/j/92591691189
URL:https://seasevents.nmsdev7.com/event/asset-seminar-benjamin-lee-university-of-pennsylvania/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241022T153000
DTEND;TZID=America/New_York:20241022T163000
DTSTAMP:20260403T162544
CREATED:20241016T141812Z
LAST-MODIFIED:20241016T141812Z
UID:10008136-1729611000-1729614600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "How to Design Useful and Usable AI-Powered Applications"
DESCRIPTION:AI-powered applications are exciting because of their potential to support people in unprecedented ways but they are also particularly challenging to design right: How does one design a useful AI-enabled product if the underlying AI is occasionally wrong? How can we make these applications feel predictable even though the AI technology is complex and can appear unpredictable?  While some specialized design knowledge related to Human-AI Interaction already exists\, the production of this knowledge is not keeping up with the pace at which new AI-powered applications are invented. Consequently\, without much fanfare or deliberation (or recognition of the fact!)\, some critical knowledge gaps are getting filled with reasonable-sounding but unverified assumptions. I will present a series of experiments (related to predictive text entry and AI-supported decision making) demonstrating that several of the key assumptions\, upon which a lot of research projects and products rest\, are wrong. I will then describe recent projects that build on corrected knowledge foundations and share some early promising results. I conclude with two calls to action for our field. First\, we need to engage in critical technical practice\, i.e.\, explicitly name\, assess and correct (if necessary) the hidden assumptions of our field. Second\, with Human-AI Interaction being a relatively new field but one that many people depend on\, we need a greater investment in systematic production\, synthesis and dissemination of reliable design knowledge for Human-AI Interaction.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-how-to-design-useful-and-usable-ai-powered-applications/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241022T120000
DTEND;TZID=America/New_York:20241022T140000
DTSTAMP:20260403T162544
CREATED:20241002T153131Z
LAST-MODIFIED:20241002T153131Z
UID:10008114-1729598400-1729605600@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Data Driven Approaches for Optimizing Antiseizure Medication Management in Epilepsy" (Nina Ghosn)
DESCRIPTION:Update 10/14/24: Please note the new time and location for Nina Ghosn’s Doctoral Dissertation Defense below.\n\nThe Department of Bioengineering at the University of Pennsylvania and Dr. Brian Litt are pleased to announce the Doctoral Dissertation Defense of Nina Ghosn.\n\n\nTitle:  DATA DRIVEN APPROACHES FOR OPTIMIZING ANTISEIZURE MEDICATION MANAGEMENT IN EPILEPSY\n\nAdvisor: Brian Litt\n\nDate: October 22nd\, 2024 \n\nTIme: 12:00 PM\n\n\nLocation: Biomedical Research Building (BRB) auditorium.\n\n\nZoom link: https://upenn.zoom.us/j/98684417609 \n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-data-driven-approaches-for-optimizing-antiseizure-medication-management-in-epilepsy-nina-ghosn/
LOCATION:BRB Auditorium
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241022T101500
DTEND;TZID=America/New_York:20241022T111500
DTSTAMP:20260403T162544
CREATED:20240916T141615Z
LAST-MODIFIED:20240916T141615Z
UID:10008099-1729592100-1729595700@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Engineering Mechanics of Architected Hard-Soft Composites: Experiment\, Simulation\, and Theory"
DESCRIPTION:Enhancing the resistance of human-made brittle materials to fracture is challenging due to the limited microstructural toughening mechanisms. This seminar makes a case for engineering toughening mechanisms in brittle materials by developing purposeful architected arrangements of material inspired by natural systems. Experimental fracture mechanics in hard-soft (cementitious-elastomeric) ‘Nacre-like’ composites based on the tabulated brick-and-mortar arrangement of mollusk shells is presented. Tablet sliding and soft interlayer energy dissipation are among the nacre’s hierarchical toughening mechanisms\, leading to its significantly higher fracture toughness than its major brittle constituent (~95%\, aragonite). Here\, it is hypothesized that tablet sliding and tortuous crack propagation (crack deflection and crack bridging) are the key mechanisms that promote inelastic deformation and increase the size of the fracture process zone in brittle material. These mechanisms significantly enhance fracture toughness and ductility by an order of magnitude compared to constituent hardened cement paste. \nTo better understand crack propagation in hard-soft composites a unified large-deformation constitutive framework was developed (implemented via user-element subroutine within the finite element software Abaqus). Interfacial properties play a crucial role in the fracture process. The proposed computational framework couples the phase-field approach for bulk fracture with a potential-based cohesive zone model (CZM) to study crack propagation in multi-material (e.g.\, hard-soft\, hard-hard) containing an interface. The phase-field captures crack initiation and propagation in the bulk constituents\, and CZM (PPR) captures the role of the interface failure (e.g.\, delamination\, deflection). The framework’s validation against linear elastic fracture mechanics theory for hard-hard composites with an interface is discussed\, including the competition between crack penetration into the bulk vs. crack deflection into the interface. The framework is a numerical tool for probing or designing architected hard-soft materials with enhanced performance characteristics and mechanisms. The seminar extends the design of architected materials beyond hard-soft composites using statistical mechanics. The degree of ‘order’ in material(s) arrangement can be quantified using proposed translational or orientational order parameters (T\, Q) from perfectly ordered to disordered and ideal random. Proper quantification of disorder in contrast to other approaches (Voronoi tessellation or perturbation methods) allows for probing the disorder-property relationship. Combined with advanced manufacturing techniques (robotic additive\, laser processing\, etc.)\, disorder can be used as a new way to design engineering materials and structures.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-engineering-mechanics-of-architected-hard-soft-composites-experiment-simulation-and-theory/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241018T103000
DTEND;TZID=America/New_York:20241018T114500
DTSTAMP:20260403T162544
CREATED:20240911T191021Z
LAST-MODIFIED:20240911T191021Z
UID:10008092-1729247400-1729251900@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP on Robotics: Zak Kassas\, IEEE AESS DL & The Ohio State University\, "Ad Astra: Navigation with Megaconstellation LEO Satellites"
DESCRIPTION:This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nWe are witnessing a space renaissance. Tens of thousands of broadband low Earth orbit (LEO) satellites are expected to be launched by the end of this decade. These planned megaconstellations of LEO satellites along with existing constellations will shower the Earth with a plethora of signals of opportunity\, diverse in frequency and direction. These signals could be exploited for positioning\, navigation\, and timing (PNT) in the inevitable event that global navigation satellite system (GNSS) signals become unavailable (e.g.\, in deep urban canyons\, under dense foliage\, during unintentional interference\, and intentional jamming) or untrustworthy (e.g.\, under malicious spoofing attacks). \nThis talk will overview the challenges associated with exploiting megaconstellation LEO satellites for PNT purposes\, namely their unknown signals\, poorly known ephemerides\, loose synchronization and oscillator instability\, and propagation effects. Next\, a framework termed STAN: simultaneous tracking and navigation will be introduced to overcome these challenges. We will present an end-to-end approach\, spanning theoretical modeling and analysis\, specialized cognitive software-defined radio (SDR) design\, practical PNT algorithms\, and experimental demonstrations of STAN on the ground and aerial vehicles\, navigating with multi-constellation LEO satellite signals (Starlink\, OneWeb\, Orbcomm\, Iridium\, and NOAA) to an unprecedented level of accuracy. Insights into future research directions and engineering implementation challenges will be provided as concluding remarks.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-on-robotics-zak-kassas-ieee-aess-dl-the-ohio-state-university-ad-astra-navigation-with-megaconstellation-leo-satellites/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Distinguished Lecture
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241017T153000
DTEND;TZID=America/New_York:20241017T163000
DTSTAMP:20260403T162544
CREATED:20240627T183734Z
LAST-MODIFIED:20240627T183734Z
UID:10008000-1729179000-1729182600@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "DNA microscopy in two and three dimensions" (Joshua Weinstein\, University of Chicago)
DESCRIPTION:Lymphatic\, nervous\, and tumoral tissues\, among others\, exhibit physiology that emerges from three-dimensional interactions between genetically unique cells. Technologies capable of volumetrically imaging transcriptomes\, genotypes\, and morphologies in a single de novo measurement can provide a critical lens into the biological complexity of living systems. We present experimental and computational work to develop DNA microscopy: a modality of imaging that captures physical images of specimen genetic content using a massive distributed network of DNA molecules inside it. We demonstrate DNA microscopy in two-dimensional cell cultures and genome-wide in intact zebrafish embryos.
URL:https://seasevents.nmsdev7.com/event/be-seminar-joshua-weinstein-university-of-chicago/
LOCATION:216 Moore Building
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241017T150000
DTEND;TZID=America/New_York:20241017T190000
DTSTAMP:20260403T162544
CREATED:20240930T180608Z
LAST-MODIFIED:20240930T180608Z
UID:10008112-1729177200-1729191600@seasevents.nmsdev7.com
SUMMARY:Responsible Innovation
DESCRIPTION:Rapid advancements in healthcare\, technology\, finance and beyond present significant opportunities and challenges. As we look to develop leading-edge solutions to provide a better future for all\, Penn Engineering and Perry World House are committed to promoting responsible innovation practices. \nJoin us for an inspiring afternoon as we launch the Responsible Innovation initiative at the Penn Washington Center in Washington\, DC. This event will bring together leaders in engineering\, academia\, industry\, and policy for an engaging dialogue on responsibly shaping the future of innovation. \nAgenda: \n3:00: Guests arrive \n3:15: Opening remarks by Vijay Kumar\, Nemirovsky Family Dean\, Penn Engineering \n3:25: Remarks by Ted Schlein\, partner at Kleiner Perkins\, Executive Chairman and Founding Partner at Ballistic Ventures\, and former chairman of the National Venture Capital Association (NVCA) \n3:40: Keynote address by Michael Horowitz\, Richard Perry Professor and Director of the Perry World House at the University of Pennsylvania\, and former Deputy Assistant Secretary of Defense for Force Development and Emerging Capabilities \n4:20: Faculty panel discussion moderated by Susan Davidson\, Weiss Professor of Computer and Information Science (CIS)\, featuring: \n\nMichael Kearns\, National Center Professor of Management & Technology\, CIS\nDan Koditschek\, Alfred Fitler Moore Professor\, Electrical and Systems Engineering (ESE)\, CIS\, and Mechanical Engineering and Applied Mechanics (MEAM)\nMark Yim\, Asa Whitney Professor of Mechanical Engineering\, MEAM\, CIS\, and ESE\n\n5:00: Presentation by George Pappas\, UPS Foundation Professor of Transportation\, ESE\, CIS\, and MEAM \n5:30: Cocktail Hour \nDon’t miss this opportunity to engage with thought leaders and be part of Penn Engineering’s bold vision for advancing responsible innovation. \nPlease make sure to RSVP by Friday\, October 11\, to secure your spot.
URL:https://seasevents.nmsdev7.com/event/responsible-innovation/
LOCATION:Penn Washington Center\, 101 Constitution Ave. NW\, Washington DC\, DC\, 20001\, United States
CATEGORIES:Faculty,Panel Discussion
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241017T140000
DTEND;TZID=America/New_York:20241017T150000
DTSTAMP:20260403T162544
CREATED:20241009T155327Z
LAST-MODIFIED:20241009T155327Z
UID:10008129-1729173600-1729177200@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP Seminar: Bob Collins & Yanxi Liu\, Penn State University\, “From Vision to Dynamics”
DESCRIPTION:*This seminar will be held in-person in Levine 307 as well as virtually via Zoom. \nABSTRACT\nIn the realms of health and sports\, quantitative analysis of human movement provides guidance for individualized performance characterization\, training\, and health assessment. Data collection for biomechanical analysis of human motion is typically performed using expensive\, specialized hardware that requires experiments to occur in a constrained lab setting. Computer vision algorithms using inexpensive\, off-the-shelf video cameras for data collection would enable observation in more natural environments with minimal cost. Towards this end\, this talk reports on:\n• Our effort in collecting the first publicly available Taiji-MultiModal (PSU TMM100) dataset containing 100 sequences of simplified 24-form Taiji with synchronized mocap\, video\, and foot-insole pressure maps.\n• An unsupervised learning method for training a light-weight encoder suitable for 3D body pose classification and sequence-to-sequence temporal alignment.\n• The first deep learning baseline that demonstrates reliable and repeatable mapping from either a single frame or short sequence of human pose (kinematics) into predicted foot pressure map output (dynamics)\, leading to image-based stability monitoring in natural environments.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-seminar-robert-collins-yanxi-liu-penn-state-university-from-vision-to-dynamics/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241017T110000
DTEND;TZID=America/New_York:20241017T120000
DTSTAMP:20260403T162544
CREATED:20241010T181407Z
LAST-MODIFIED:20241010T181407Z
UID:10008131-1729162800-1729166400@seasevents.nmsdev7.com
SUMMARY:IDEAS Seminar: "Equivariant Neural Inertial Odometry"
DESCRIPTION:Abstract:  \nIn this talk\, we introduce a new class of problems related to integrating inertial measurements obtained from an IMU that play a significant role in navigation combined with visual data. While there have been tremendous technological advances in the precision of instrumentation\, integrating acceleration and angular velocity still suffers from drift in the displacement estimates. Neural networks have come to the rescue in estimating displacement and the associated uncertainty covariance. However\, such networks do not consider the physical roto-reflective symmetries inherent in IMU data\, leading to the need to memorize the same priors for every possible motion direction\, which hinders generalization. In this work\, we characterize these symmetries and show that the IMU data and the resulting displacement and covariance transform equivariantly when rotated around the gravity vector and reflected with respect to arbitrary\nplanes parallel to gravity. We propose a network for predicting an equivariant gravity-aligned frame from equivariant vectors and invariant scalars derived from IMU data\, leveraging expressive linear and non-linear layers tailored to commute with the underlying symmetry transformation. Such a canonical frame can precede existing architectures that are end-to-end or filter-based. We will include an introduction to the inertial filtering problem and we will present\nresults in real-world datasets. \nZoom link: https://caltech.zoom.us/j/88141815847?pwd=ayPBbwoDE91IWysv1P4Oxp6zbamrSQ.1
URL:https://seasevents.nmsdev7.com/event/ideas-seminar-equivariant-neural-inertial-odometry/
LOCATION:Room 401B\, 3401 Walnut\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241017T103000
DTEND;TZID=America/New_York:20241017T120000
DTSTAMP:20260403T162544
CREATED:20241008T150959Z
LAST-MODIFIED:20241008T150959Z
UID:10008128-1729161000-1729166400@seasevents.nmsdev7.com
SUMMARY:MSE Seminar “Shaping a Soft Future"
DESCRIPTION:Existing devices—such as cell phones\, computers\, and robots – are made from rigid materials\, which is in direct contrast to the soft materials that compose the human body. In this talk\, I will discuss several topics related to studying and harnessing soft materials within the context of creating devices with tissue like properties. \n\nLiquid metal: Gallium-based liquid metals are often overlooked despite their remarkable properties: melting points below room temperature\, water-like viscosity\, low-toxicity\, and effectively zero vapor pressure (they do not evaporate). They also have\, by far\, the largest interfacial tension of any liquid at room temperature. Normally small volumes of liquids with large tension form spherical or hemi-spherical structures to minimize surface energy. Yet\, these liquid metals can be patterned into non-spherical shapes (cones\, wires\, antennas) due to a thin\, oxide skin that forms rapidly on its surface.\nShape reconfiguration: Perhaps the most fascinating aspect of liquid metals it the ability to use interfacial electrochemistry chemistry to remove / deposit the oxide to manipulate the surface tension of the metal over unprecedented ranges (from the largest tension of any known liquid to near zero!). This allows manipulating the shape and position of the metal for shape reconfigurable devices.\nLonogels: Soft materials that are tough (that is\, they do not readily tear or fail mechanically) are important for a number of applications\, including encapsulation of devices. Recently\, we discovered a simple way to create ultra-tough ionogels\, which are polymer networks swollen with ionic liquids. These materials are tougher than cartilage and compatible with 3D printing.\n\nThis work has implications for soft and stretchable electronics; that is\, devices with desirable mechanical properties for human-machine interfacing\, soft robotics\, and wearable electronics.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-shaping-a-soft-future/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241016T153000
DTEND;TZID=America/New_York:20241016T163000
DTSTAMP:20260403T162544
CREATED:20240816T202836Z
LAST-MODIFIED:20240816T202836Z
UID:10008053-1729092600-1729096200@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Optimizing Work and Heat flows in Sustainable Chemical Processes Using Attainable Regions" (Diane Hildebrandt\, Rutgers University)
DESCRIPTION:Abstract: \nA chemical process transforms feed materials into desired products\, necessitating the exchange of heat and work between the process and the environment. Optimizing process performance requires careful selection of chemical pathways\, process parameters\, and heat/workflows. The reversible process sets the upper-performance limit for sustainable design\, thereby setting a target for process design. We propose using a plot of enthalpy (H) against Gibbs Free Energy (G) to represent\, synthesize\, and analyze heat and workflows in chemical processes. This graphical approach is particularly useful for identifying and assessing process reversibility. We define the Thermodynamic Attainable Region (AR T ) as the set of all (delta)H and (delta)G across all possible processes that convert a given feed(s) into specified products. In this talk\, we will present a methodology for calculating the AR T . By leveraging the visual representation of the AR T \, we can systematically analyze and compare the inherent heat and workflows of different processes\, feeds\, and products. We will consider some simple examples to illustrate the impact of the selection of chemical pathways\, process parameters\, and feeds on process heat and workflows and reversibility.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-optimizing-work-and-heat-flows-in-sustainable-chemical-processes-using-attainable-regions-diane-hildebrandt-rutgers-university/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241016T150000
DTEND;TZID=America/New_York:20241016T160000
DTSTAMP:20260403T162544
CREATED:20241010T152537Z
LAST-MODIFIED:20241010T152537Z
UID:10008130-1729090800-1729094400@seasevents.nmsdev7.com
SUMMARY:Fall 2024 GRASP SFI: Jun-Yan Zhu\, Carnegie Mellon University\, "Ensuring Data Ownership in Generative Visual Models"
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nLarge-scale generative visual models have made content creation as little effort as writing a short text description. However\, these models are typically trained on an enormous amount of Internet data\, often containing copyrighted material\, licensed images\, and personal photos. How can we remove these images if creators decide to opt out? How can we properly compensate them if they choose to opt in? \nIn this talk\, I will first describe an efficient method for removing copyrighted materials\, artistic styles of living artists\, and memorized images from pretrained text-to-image models. I will then discuss our data attribution algorithms for assessing the influence of each training image for a generated sample. Collectively\, we aim to enable creators to retain control over the ownership of training images.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-sfi-jun-yan-zhu/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241016T133000
DTEND;TZID=America/New_York:20241016T143000
DTSTAMP:20260403T162544
CREATED:20241004T153846Z
LAST-MODIFIED:20241004T153846Z
UID:10008121-1729085400-1729089000@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Semantics-Driven Active Perception and Navigation with Aerial Robots"
DESCRIPTION:Autonomous aerial robots today are capable of safely navigating through cluttered\, GPS-denied environments while constructing an accurate map that captures geometric features such as points\, lines\, and planes. Such maps are crucial for low-level planning and obstacle avoidance. However\, beyond offering details on the density\, layout\, and dimensions of the environment\, these maps provide limited information for semantically meaningful reasoning. For instance\, they fall short in helping the robot identify where to find specific objects during search and rescue operations\, which areas are relevant during infrastructure inspection or asset mapping\, or in distinguishing between static and dynamic entities in the environment during localization and navigation. Such reasoning capabilities are especially important for resource-constrained robots\, such as micro aerial vehicles\, deployed in large-scale environments. In such scenarios\, robots need to keep track of important\, actionable information\, while respecting their onboard computational and storage resource constraints. Sparse\, semantically meaningful maps facilitate robust state estimation and storage-efficient mapping\, while also enabling high-level reasoning that guides intelligent\, task-relevant decision-making during navigation and exploration. \nThis thesis introduces a set of novel methodologies and algorithms for semantics-driven perception and autonomy\, enabling robots to safely navigate and explore large-scale\, complex environments while actively and collaboratively constructing high-quality\, semantically meaningful maps. Specifically\, we first present a monocular-camera-based semantic mapping system that integrates deep learning\, visual tracking\, and semantic Structure from Motion (SfM) for accurate fruit detection and mapping in orchards. We then develop a semantic Simultaneous Localization and Mapping (SLAM) integrated autonomous aerial navigation system for large-scale semantic mapping in under-forest-canopy environments. This system leverages real-time semantic SLAM for accurate pose estimation and timber metric assessment. Next\, we introduce active metric-semantic SLAM systems for both urban outdoor and indoor environments. These systems use semantics to guide aerial robots to explore the environment and minimize both metric and semantic uncertainties. Lastly\, bridging all efforts together\, we propose a decentralized metric-semantic SLAM framework for autonomous navigation and exploration with heterogeneous robot teams operating across multiple environments. Extensive real-world experiments have validated the robustness and performance of the proposed methods across multiple aerial and ground robot platforms in various environments\, including multi-floor indoor spaces\, urban outdoors\, forests\, and orchards. Field deployments further showcase the system’s potential for direct application in solving important real-world problems\, such as precision agriculture\, forestry management\, climate change mitigation\, infrastructure inspection\, and factory asset management. Finally\, the proposed systems and algorithms are made available as open-source tools for public use.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-semantics-driven-active-perception-and-navigation-with-aerial-robots/
LOCATION:Room 313\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241016T120000
DTEND;TZID=America/New_York:20241016T131500
DTSTAMP:20260403T162544
CREATED:20240715T210338Z
LAST-MODIFIED:20240715T210338Z
UID:10008021-1729080000-1729084500@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "Some Displaced Vignettes on Generalized Notions of Equivariance"
DESCRIPTION:Abstract: \nThe explicit incorporation of task-specific inductive biases through symmetry has emerged as a crucial design precept in the development of high-performance machine learning models. Symmetry-aware neural networks\, such as group equivariant networks\, have achieved notable success in areas like protein and drug design\, where capturing task-specific symmetries improves generalization. Recent efforts have focused on models that relax equivariance\, balancing flexibility and equivariance to enhance performance. In the first part of the talk\, I will discuss the benefits of partial and approximate equivariance from a theoretical perspective\, presenting quantitative bounds that demonstrate how models capturing task-specific symmetries lead to improved generalization. Utilizing this quantification\, I will examine the more general question of dealing with approximate/partial symmetries and model mis-spefication\, delineating conditions under which the model equivariance is optimal for a given level of data symmetry. In the second part\, I will present a general formalism based on special structured matrices\, which generalizes classical low-displacement rank theory of Kailath and co-workers\, which can help in constructing approximately equivariant neural networks with significantly reduced parameter counts. In the last part\, I will discuss some attempts at generalizing notions of equivariance in the context of language and compositional generalization. I will also talk about some ongoing work on using such notions for the problem of inverse protein folding. \nWork done in collaboration with: Mircea Petrace (Pontificia Universidad Católica de Chile)\, Ashwin Samudre (Simon Fraser University)\, Brian D. Nord (Fermilab and University of Chicago)\, and Payel Das (IBM Research). \nZoom Link (if unable to attend in-person): https://upenn.zoom.us/j/96014696752
URL:https://seasevents.nmsdev7.com/event/asset-seminar-shubhendu-trivedi-massachusetts-institute-of-technology/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
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