BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231108T150000
DTEND;TZID=America/New_York:20231108T160000
DTSTAMP:20260404T101550
CREATED:20230908T192022Z
LAST-MODIFIED:20230908T192022Z
UID:10007678-1699455600-1699459200@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP SFI: Margaret Coad\, University of Notre Dame\, "Soft and Continuum Robots for Unstructured Environments"
DESCRIPTION:This is a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nSoft and continuum robots have immense potential to assist humans with tasks that require navigation and manipulation in unstructured environments. In this talk\, I present my group’s research on the design\, modeling\, and control of a variety of soft and continuum robots. I begin by discussing soft vine-inspired robots\, which move through their environment by extending from their tip and are well suited for navigation and manipulation within confined spaces. In particular\, I discuss our research on vine robot field deployment\, shape sensing\, force sensing\, and collapse modeling. I then present our research on two other bioinspired robots: spider monkey tail-inspired robots for grasping objects\, and amoeba-inspired robots for navigation in confined spaces. Finally\, I discuss our research on soft wearable robots for replacing or assisting the motion of the upper limbs. This research helps make robots more capable of assisting humans in the unstructured environments of everyday life.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-sfi-margaret-coad/
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:20231109T110000
DTEND;TZID=America/New_York:20231109T120000
DTSTAMP:20260404T101550
CREATED:20230829T201346Z
LAST-MODIFIED:20230829T201346Z
UID:10007657-1699527600-1699531200@seasevents.nmsdev7.com
SUMMARY:ESE Fall Seminar - "Approximate symmetries in machine learning"
DESCRIPTION:In this talk\, we explain different roles that symmetries and approximate symmetries can play in machine learning models. We define approximately equivariant graph neural networks and we show a bias-variance tradeoff when selecting the symmetries to enforce. We explain how to see equivariant functions as gradients of invariant functions\, and we show how to use these ideas in self-supervised learning.
URL:https://seasevents.nmsdev7.com/event/ese-fall-seminar-title-tbd-7/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut 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:20231109T143000
DTEND;TZID=America/New_York:20231109T163000
DTSTAMP:20260404T101550
CREATED:20231019T160806Z
LAST-MODIFIED:20231019T160806Z
UID:10007738-1699540200-1699547400@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Mapping variable host gene expression states to viral infection" (Sam Reffsin)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Arjun Raj are pleased to announce the Doctoral Dissertation Defense of Sam Reffsin.\n\nTitle: Mapping variable host gene expression states to viral infection\nDate: November 9\, 2023\nTime: 2:30pm-4:30pm\nLocation: Smilow 11-146AB\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-mapping-variable-host-gene-expression-states-to-viral-infection-sam-reffsin/
LOCATION:Smilow Center for Translational Research in SCTR 11-146AB
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:20231109T153000
DTEND;TZID=America/New_York:20231109T163000
DTSTAMP:20260404T101550
CREATED:20231018T183158Z
LAST-MODIFIED:20231018T183158Z
UID:10007736-1699543800-1699547400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Intrinsic images\, lighting and relighting without any labelling"
DESCRIPTION:Intrinsic images are maps of surface properties. A classical problem is to recover an intrinsic image\, typically a map of surface lightness\,\nfrom an image.   The topic has mostly dropped from view\, likely for three reasons: training data is mostly synthetic; evaluation is somewhat\nuncertain; and clear applications for the resulting albedo are missing.  The decline of this topic has a consequence – mostly\, we don’t understand and can’t mitigate the effects of lighting.\n\nI will show the results of simple experiments that suggest that very good modern depth and normal predictors are strongly sensitive to lighting — if\nyou relight a scene in a reasonable way\, the reported depth will change. This is intolerable. To fix this problem\, we need to be able to produce\nmany different lightings of the same scene.   I will describe a method to do so.  First\, one learns a method to estimate albedo from images without any labelled training data (which turns out to perform well under traditional evaluations).  Then\, one forces an image generator to produce many different images that have the same albedo — with care\, these are relightings of the same scene.  Finally\, a GAN inverter allows us to apply the process to real images.  I will show some interim results suggesting that learned relightings might genuinely improve estimates of depth\, normal and albedo.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-intrinsic-images-lighting-and-relighting-without-any-labelling/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231109T153000
DTEND;TZID=America/New_York:20231109T163000
DTSTAMP:20260404T101550
CREATED:20231106T142758Z
LAST-MODIFIED:20231106T142758Z
UID:10007756-1699543800-1699547400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Intrinsic images\, lighting and relighting without any labeling"
DESCRIPTION:I will show the results of simple experiments that suggest that very good modern depth and normal predictors are strongly sensitive to lighting – if you relight a scene in a reasonable way\, the reported depth will change. This is intolerable. To fix this problem\, we need to be able to produce many different lightings of the same scene.   I will describe a method to do so.  First\, one learns a method to estimate albedo from images without any labelled training data (which turns out to perform well under traditional evaluations).  Then\, one forces an image generator to produce many different images that have the same albedo — with care\, these are relightings of the same scene.  Finally\, a GAN inverter allows us to apply the process to real images.  I will show some interim results suggesting that learned relightings might genuinely improve estimates of depth\, normal and albedo.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-intrinsic-images-lighting-and-relighting-without-any-labeling/
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:20231110T100000
DTEND;TZID=America/New_York:20231110T110000
DTSTAMP:20260404T101550
CREATED:20231105T175238Z
LAST-MODIFIED:20231105T175238Z
UID:10007754-1699610400-1699614000@seasevents.nmsdev7.com
SUMMARY:PRECISE Seminar: Evaluation and calibration of AI models with uncertain ground truth
DESCRIPTION:For safety\, AI systems in health undergo thorough evaluations before deployment\, validating their predictions against a ground truth that is assumed certain. However\, this is actually not the case and the ground truth may be uncertain. Unfortunately\, this is largely ignored in standard evaluation of AI models but can have severe consequences such as overestimating the future performance. To avoid this\, we measure the effects of ground truth uncertainty\, which we assume decomposes into two main components: annotation uncertainty which stems from the lack of reliable annotations\, and inherent uncertainty due to limited observational information. This ground truth uncertainty is ignored when estimating the ground truth by deterministically aggregating annotations\, e.g.\, by majority voting or averaging. In contrast\, we propose a framework where aggregation is done using a statistical model. Specifically\, we frame aggregation of annotations as posterior inference of so-called plausibilities\, representing distributions over classes in a classification setting\, subject to a hyper-parameter encoding annotator reliability. Based on this model\, we propose a metric for measuring annotation uncertainty and provide uncertainty-adjusted metrics for performance evaluation. We present a case study applying our framework to skin condition classification from images where annotations are provided in the form of differential diagnoses. The deterministic adjudication process called inverse rank normalization (IRN) from previous work ignores ground truth uncertainty in evaluation. Instead\, we present two alternative statistical models: a probabilistic version of IRN and a Plackett-Luce-based model. We find that a large portion of the dataset exhibits significant ground truth uncertainty and standard IRN-based evaluation severely over-estimates performance without providing uncertainty estimates. \nLinks: https://arxiv.org/abs/2307.09302 https://arxiv.org/abs/2307.02191 \n 
URL:https://seasevents.nmsdev7.com/event/precise-seminar-evaluation-and-calibration-of-ai-models-with-uncertain-ground-truth/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="PRECISE":MAILTO:wng@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231110T103000
DTEND;TZID=America/New_York:20231110T114500
DTSTAMP:20260404T101550
CREATED:20231102T151151Z
LAST-MODIFIED:20231102T151151Z
UID:10007750-1699612200-1699616700@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP on Robotics: Sunil Agrawal\, Columbia University\, "Rehabilitation Robotics: Improving Everyday Human Functions"
DESCRIPTION:This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nNeural disorders\, old age\, and traumatic injuries limit the ability of humans to perform activities of daily living. Robotics can be used to characterize and retrain human neuromuscular responses. Columbia University Robotics and Rehabilitation (ROAR) Laboratory designs innovative robots and performs scientific studies to improve everyday human functions such as standing\, walking\, stairclimbing\, reaching\, head turning\, and others. Human experiments have targeted individuals with stroke\, cerebral palsy\, Parkinson’s disease\, ALS\, and elderly subjects. The talk will provide an overview of some of these robotic technologies and scientific studies performed with them to show the potential of rehabilitation robotics to improve quality of life of people around the world.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-on-robotics-sunil-agrawal-columbia-university-rehabilitation-robotics-improving-everyday-human-functions/
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:20231110T140000
DTEND;TZID=America/New_York:20231110T150000
DTSTAMP:20260404T101550
CREATED:20231103T204842Z
LAST-MODIFIED:20231103T204842Z
UID:10007753-1699624800-1699628400@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "MFEM: Accelerating Efficient Solution of PDEs at Exascale"
DESCRIPTION:Upcoming exascale architectures require rethinking of the numerical algorithms used in large-scale PDE-based applications. These architectures favor algorithms\, such as high-order finite elements\, that expose fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. \nIn this talk we present an overview of MFEM [1]\, a scalable library for high-order finite element discretization of PDEs on general unstructured grids. We also report on recent work in the Center for Efficient Exascale Discretizations [2]\, a co-design center in the US Exascale Computing Project focused on next-generation discretization software and algorithms. \nOur approach to efficient operator evaluation is based on a “matrix-free” representation of the finite element operator\, that factors a bilinear form into a series of sparse and dense components corresponding to the parallelism\, mesh topology\, basis\, geometry\, and pointwise physics in the problem. The operator decomposition exposes several layers of parallelism\, enables the use of batched dgemss and tensor contractions\, and only requires quadrature point values to be assembled for computing the action. This “partial assembly” formulation is a natural fit for modern HPC hardware\, because it results both in less (nearly optimal) computation and less (optimal) data movement compared to assembling a global sparse matrix\, therefore increasing performance and reducing time to solution. \nIn addition to discussing efficient operator evaluation\, we will provide an overview of the MFEM capabilities and applications to compressible hydrodynamics and electromagnetics. We will also review our work on performance optimizations for GPU architectures\, high-order benchmarks and miniapps\, scalable unstructured adaptive mesh refinement\, high-order mesh optimization and matrix-free preconditioning. \n[1] MFEM: Modular finite element library\, http://mfem.org. \n[2] Center for Efficient Exascale Discretizations\, http://ceed.exascaleproject.org.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium/
LOCATION:https://upenn.zoom.us/j/96715197752
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2023/11/EMCaward_kolevTzanio_2019-2-new-1-1-scaled-1.jpg
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231113T130000
DTEND;TZID=America/New_York:20231113T140000
DTSTAMP:20260404T101550
CREATED:20231016T001354Z
LAST-MODIFIED:20231016T001354Z
UID:10007730-1699880400-1699884000@seasevents.nmsdev7.com
SUMMARY:PRECISE Seminar: Wearable Acoustic and Vibration Sensing and Machine Learning for Human Health and Performance
DESCRIPTION:Abstract\n\nRecent advances in digital health technologies are enabling biomedical researchers to reframe health optimization and disease treatment in a patient-specific\, personalized manner. This talk will focus on my group’s research in two areas of relevance to digital health: (1) cardiogenic vibration sensing and analytics; and (2) musculoskeletal sensing with joint acoustic emissions and bioimpedance. Our group has extensively studied the timings and characteristics of cardiogenic vibration signals such as the ballistocardiogram and seismocardiogram\, and applied these signals for quantifying filling pressures and volume status in the context of heart failure (volume overload) and hemorrhage (volume depletion). We have also leveraged miniature contact microphones to measure the sounds emitted by joints\, such as the knees\, during movement\, and have examined how these acoustic characteristics are altered by musculoskeletal injuries and disorders (e.g.\, arthritis). We envision that these technologies can all contribute to improving patient care with lower cost and better outcomes.
URL:https://seasevents.nmsdev7.com/event/precise-seminar-wearable-acoustic-and-vibration-sensing-and-machine-learning-for-human-health-and-performance/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="PRECISE":MAILTO:wng@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231114T100000
DTEND;TZID=America/New_York:20231114T113000
DTSTAMP:20260404T101550
CREATED:20231101T185501Z
LAST-MODIFIED:20231101T185501Z
UID:10007749-1699956000-1699961400@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Magnetic Fluid Hyperthermia with Magnetic Iron Oxide Nanoparticles: A Case Study in Multi-disciplinary Translational Biomedical Research"
DESCRIPTION:Magnetic nanoparticles that are responsive to clinically safe magnetic fields offer multi-modal nanomedicine capabilities. To succeed\, complexities of physics and engineering must be addressed to match physical and magnetic properties of magnetic nanoparticles with devices used to activate them. This requires thoughtful design and fabrication of both nanoparticles and devices\, with appropriate testing in relevant biological models that faithfully represent intended end use. Hyperthermia is a heat-based cancer therapy that improves treatment outcomes and patient survival when controlled energy delivery is combined with accurate thermometry. To date\, few technologies have achieved the needed evolution for the demands of the clinic. Magnetic fluid hyperthermia (MFH) offers this potential\, but to be successful it requires particle-imaging technology that provides real-time thermometry. Presently\, the only technology having the potential to meet these requirements is magnetic particle imaging (MPI)\, for which a proof-of-principle demonstration with MFH has been achieved. Successful clinical translation and adoption of integrated MPI/MFH technology demands successful integration of imaging data processing with robust computational heat-transfer modeling and adaptive temperature control algorithms into a theranostic device platform.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-magnetic-fluid-hyperthermia-with-magnetic-iron-oxide-nanoparticles-a-case-study-in-multi-disciplinary-translational-biomedical-research/
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:20231114T153000
DTEND;TZID=America/New_York:20231114T163000
DTSTAMP:20260404T101550
CREATED:20231109T164556Z
LAST-MODIFIED:20231109T164556Z
UID:10007757-1699975800-1699979400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Edge-Weighted Online Bipartite Matching"
DESCRIPTION:Online bipartite matching is one of the most fundamental problems in the online algorithms literature. Karp\, Vazirani\, and Vazirani (STOC 1990) gave an elegant algorithm for unweighted bipartite matching that achieves an optimal competitive ratio 1-1/e. Aggarwal et al. (SODA 2011) later generalized their algorithm and analysis to the vertex-weighted case. Little is known\, however\, about the most general edge-weighted problem aside from the trivial 1/2-competitive greedy algorithm. In this talk\, we present the first online algorithm that breaks the long-standing 1/2 barrier and achieves a competitive ratio of at least 0.5086. \nThe main ingredient in our online matching algorithm is a novel subroutine called online correlated selection (OCS)\, which takes a sequence of pairs of vertices as input and selects one vertex from each pair. Instead of using a fresh random bit to choose a vertex from each pair\, the OCS negatively correlates decisions across different pairs and provides a quantitative measure of the level of correlation. The OCS technique is of independent interest and has already found further applications in other online optimization problems.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-edge-weighted-online-bipartite-matching/
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:20231115T100000
DTEND;TZID=America/New_York:20231115T110000
DTSTAMP:20260404T101550
CREATED:20231113T161656Z
LAST-MODIFIED:20231113T161656Z
UID:10007760-1700042400-1700046000@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP Seminar: Vladimir Kucera\, Czech Technical University\, “Czech Technical University in Prague”
DESCRIPTION:*This seminar will be held in-person ONLY in Levine 307. The seminar will NOT be recorded. \nABSTRACT\nThe talk aims to present the Czech Technical University in Prague as a polytechnic school with a rich history and a lively present. The main milestones of its development\, current faculties and institutes\, human and financial resources\, study programs\, and research focus will be presented. The next part will be more personal: my role in the development of the university and a detailed presentation of its newest part\, the Czech Institute of Informatics\, Robotics\, and Cybernetics.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-seminar-vladimir-kucera-czech-technical-university-czech-technical-university-in-prague/
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:20231115T120000
DTEND;TZID=America/New_York:20231115T131500
DTSTAMP:20260404T101550
CREATED:20230928T141840Z
LAST-MODIFIED:20230928T141840Z
UID:10007709-1700049600-1700054100@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "What Constitutes a Good Explanation?" (Lyle Ungar\, Penn)
DESCRIPTION:ABSTRACT:  \nShapley values and similar methods are widely used to explain the importance of features in model predictions. Clarity in the semantics of these feature importances is subtle\, but crucial: What do these explanations actually mean? And how are they useful? We illustrate using explanations of predictions in three domains: (a) medical outcomes\, (b) image content\, and (c) first impressions of people—specifically their warmth and competence—derived from video recordings and transcripts. In each scenario\, the presence of intermediate-level features enhances the clarity and usefulness of\nexplanations.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-lyle-ungar-penn/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231115T150000
DTEND;TZID=America/New_York:20231115T160000
DTSTAMP:20260404T101550
CREATED:20231018T153316Z
LAST-MODIFIED:20231018T153316Z
UID:10007733-1700060400-1700064000@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP SFI: Samuel Sokota\, Carnegie Mellon University\, “Reinforcement Learning in Two-Player Zero-Sum Games”
DESCRIPTION:This is a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nI’ll discuss reinforcement learning in two-player zero-sum games. Historically\, this area has lacked algorithms that perform well in large settings with imperfect information. I’ll describe a resolution for making self-play RL performant.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-sfi-samuel-sokota/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231115T153000
DTEND;TZID=America/New_York:20231115T163000
DTSTAMP:20260404T101550
CREATED:20230825T200921Z
LAST-MODIFIED:20230825T200921Z
UID:10007647-1700062200-1700065800@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: Britton Chance Distinguished Lecture\, "A Language Whose Characters are Triangles" (Phillips\, California Institute of Technology)
DESCRIPTION:One of the most intriguing outcomes of casting our thinking about the world around us in mathematical terms is that phenomena that were thought to be quite distinct are instead revealed as being the “same.” Thinkers as long ago as Pliny the Elder made observations on active matter noting: “It is a peculiarity of the starling to fly in troops\, as it were\, and then to wheel round in a globular mass like a ball\, the central troop acting as a pivot for the rest.’’ In this talk I will introduce field theory and the emergence of the modern theory of active matter as formulated by Toner and Tu to describe the collective motions of animals such as the giant herds of wildebeest on the plains of the Serengeti. We will then use active matter theory at a billion fold smaller scale to describe the motion of “flocks’’ of actin that power the movement of the single-celled parasites that cause malaria and toxoplasmosis. Our theoretical analysis will be used as a tool to interpret single-cell/single-molecule experiments on the dynamics of these fascinating parasitic organisms. All of these topics will serve as an invitation to a broader discussion of how the study of the living world is enriched by adopting the mindset that led Galileo to his assertion that the language of the natural world is mathematical.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-britton-chance-distinguished-lecture-a-language-whose-characters-are-triangles-phillips-california-institute-of-technology/
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:20231115T160000
DTEND;TZID=America/New_York:20231115T170000
DTSTAMP:20260404T101550
CREATED:20231101T180451Z
LAST-MODIFIED:20231101T180451Z
UID:10007747-1700064000-1700067600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Rheological Evaluation of Complex Fluids for Fluid Mechanics Studies"
DESCRIPTION:Recent development of computational fluid mechanics allows to simulate wide range of fluid mechanics problems\, but it requires appropriate constitutive equations and rheological properties to represent behavior of complex fluid flows. Standard torque-type rheometer\, which is conventional rheometer with assuming ideal constant shear profiles in a thin test fluid layer\, however\, essential problems on the methodology for the complex fluids. We recently established velocity-profiling-assisted rheometry\, which resolves the problem to determine local shear rate by velocity profiling\, and the rheometry also has advantages of instantaneous evaluations of the properties. In my talk\, I will explain idea of the rheometry\, and practical algorithms to realize the evaluation\, and introduce some applications of the rheological evaluations\, for example\, polymer solutions\, particle suspensions\, and fluid foods.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-rheological-evaluation-of-complex-fluids-for-fluid-mechanics-studies/
LOCATION:Towne 315\, 220 S. 33rd 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:20231116T103000
DTEND;TZID=America/New_York:20231116T120000
DTSTAMP:20260404T101550
CREATED:20230908T144023Z
LAST-MODIFIED:20230908T144023Z
UID:10007676-1700130600-1700136000@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Turbo-charging Silicon: Do we have the materials and devices?" (Deep Jariwala) University of Pennsylvania
DESCRIPTION:Silicon has been the dominant material for electronic computing for decades and very likely will stay dominant for the foreseeable future. However\, it is well-known that Moore’s law that propelled Silicon into this dominant position is long dead.  Therefore\, a fervent search for (i) new semiconductors that could directly replace silicon or (ii) new architectures with novel materials/devices added onto silicon or (iii) new physics/state-variables or a combination of above has been the subject of much of the electronic materials and devices research of the past 2 decades. The above problem is further complicated by the changing paradigm of computing from arithmetic centric to data centric in the age of billions of internet-connected devices and artificial intelligence. Therefore\, there is a pressing need for complementing and supplementing Silicon to operate with greater efficiency\, speed and handle greater amounts of data. This is further necessary since a completely novel and paradigm changing computing platform (e.g. all optical computing or quantum computing) remains out of reach for now.\nThe above is however not possible without fundamental innovation in new electronic materials and devices. Therefore\, in this talk\, I will try to make the case of how novel layered two-dimensional (2D) chalcogenide materials and three-dimensional (3D) nitride materials might present interesting avenues to overcome some of the limitations being faced by Silicon hardware. I will start by presenting our ongoing and recent work on integration of 2D chalcogenide semiconductors with silicon 1\, 2 to realize low-power tunnelling field effect transistors. In particular I will focus on In-Se based 2D semiconductors 1 for this application and extend discussion on them to phase-pure\, epitaxial thin-film growth over wafer scales\, 3 at temperatures low-enough to be compatible with back end of line (BEOL) processing in Silicon fabs.\nI will then switch gears to discuss memory devices from 2D materials when integrated with emerging wurtzite structure ferroelectric nitride materials 4 namely aluminium scandium nitride (AlScN). First\, I will present on Ferroelectric Field Effect Transistors (FE-FETs) made from 2D materials when integrated with AlScN and make the case for 2D semiconductors in this application. 5\, 6 Next I will introduce our work on Ferroelectric Diode (FeD) devices also based on thin AlScN. 7 In addition\, I will also present how FeDs provide a unique advantage in compute-in-memory (CIM) architectures for efficient storage\, search as well as hardware implementation of neural networks. Finally\, I will present ongoing work and opportunities to extend the application of AlScN memory devices into extreme environments.\nI will end the talk with a broad perspective on the role of novel materials that could turbo- charge silicon and other pervasive semiconductor technologies for electronic computing. \nReferences:\n1. Miao\, J.; et al. Jariwala\, D.\, Nature Electronics 2022\, 5 (11)\, 744-751.\n2. Miao\, J.; et al. Jariwala\, D.\, Nano Letters 2020\, 20 (4)\, 2907-2915.\n3. Song\, S.; et al. Stach\, E. A.; Olsson\, R. H.; Jariwala\, D.\, Matter 2023\n(online).\n4. Kim\, K.-H.; Karpov\, I.; Olsson\, R. H.; Jariwala\, D.\, Nature Nanotechnology\n2023\, 18 (5)\, 422-441.\n5. Liu\, X.; et al. Stach\, E. A.; Olsson\, R. H.; Jariwala\, D.\, Nano Letters 2021\, 21\n(9)\, 3753-3761.\n6. Kim\, K.-H.; Stach\, E. A.; Olsson\, R. H.; Jariwala\, D.\, Nature Nanotechnology\n2023.\n7. Liu\, X.; et al. Stach\, E. A.; Olsson III\, R.; Jariwala\, D.\, Applied Physics Letters\n2021\, 118 (20)\, 202901. \n8. Liu\, X.; et al. Stach\, E. A.; Olsson\, R. H.; Jariwala\, D.\, Nano Letters 2022\, 22\n(18)\, 7690–7698.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-turbo-charging-silicon-do-we-have-the-materials-and-devices-deep-jariwala-university-of-pennsylvania/
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:20231116T130000
DTEND;TZID=America/New_York:20231116T140000
DTSTAMP:20260404T101550
CREATED:20231103T132032Z
LAST-MODIFIED:20231103T132032Z
UID:10007752-1700139600-1700143200@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "No Watts Wasted: Spines and Tails for Agile Legged Locomotion"
DESCRIPTION:Despite considerable advancements in recent years\, legged robots still fall short in terms of agility when compared to their animal counterparts. This thesis takes a two pronged approach to creating more agile behaviors by pursuing the intuition that agile legged machines should use much of their available power during agile behaviors. \nThe first approach leverages hybrid averaging analysis of SLIP like robots to devise a hip-energized control strategy. This controller takes a previously underutilized actuator and applies it to energize the robot. The resulting analysis provides new insight into the role of the hip actuator and symmetry in SLIP-like machines. The second approach seeks to design high power robots with few actuators\, which minimizes the framing cost while also making it easier to design behaviors which utilize the available power. \nThis thesis contributes support for the hypothesis that moving actuators from the legs to a tail or spine provides more opportunities to deploy them for spatial mobility. That support is manifest in the design and control of Jerboa 3.0\, a tailed biped featuring a high powered 2 degree of freedom tail whose lavish tail actuation budget comes at the expense of assigning only one motor to each of its springy legs. Jerboa 3.0 is capable of sustained spatial hopping\, starting and stopping on command\, and getting up again after falling. Lastly this thesis contains a speculative look as to what a simple model for the use of spines and tails for energization might look like. The resulting double-spring double-mass model enables both tail-energized hopping in a tailed robot and spine-energized bounding in a spined quadruped. More broadly the thesis serves as a case study in the creation of more agile legged machines that might one day rival animals.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-no-watts-wasted-spines-and-tails-for-agile-legged-locomotion/
LOCATION:Levine 307\, 3330 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:20231116T153000
DTEND;TZID=America/New_York:20231116T163000
DTSTAMP:20260404T101550
CREATED:20231023T133806Z
LAST-MODIFIED:20231023T133806Z
UID:10007740-1700148600-1700152200@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Synthetic Genome Regulation for Cell and Tissue Engineering" (Timothy Downing\, UC Irvine)
DESCRIPTION:Molecular heterogeneity is emerging as a critical feature of multicellular life. While single-cell analyses have revealed the existence of cell-to-cell variation in the levels and activities of the molecules responsible for gene regulation\, the source of such variation is still poorly understood. The Downing Lab studies how genome replication contributes to epigenetic heterogeneity across stem cell populations. We recently developed a new sequencing method (Repli-Bisulfite Sequencing) that enables analysis of DNA methylation within newly replicated strands of DNA over time. Using this method\, we discovered that much of the methylation heterogeneity observed within human embryonic stem cells (hESCs) is temporal in nature and associated with DNA replication. Here\, we employ bioinformatic analyses to explore how properties of post-replication DNA methylation dynamics relate to well-established features of the genome and the broader chromatin landscape. Our findings reveal that unique patterns of methylome replication associate with distal regulatory regions throughout the genome\, enrich for cytosine residues dynamically methylated across cell types\, and coincide with the location of stem cell-specific transcription factor binding and chromatin architectures. We also find correlations between sub-cell cycle kinetics in DNA methylation and the divergence of bulk methylation patterns observed during multiple cell generations and natural aging. Taken together\, our studies suggest that (epi)genome replication may act as an important source of (temporal) regulatory variation in hESCs while\, simultaneously\, conferring susceptibility to epigenetic drift throughout the human lifespan. Our lab is also interested in understanding how the chemical and biophysical microenvironment influences adult cell behavior and phenotype through epigenetic gene regulatory mechanisms. We hope to use this information in the design of next-generation biomaterials. The second part of this presentation will describe how focal adhesions and cell-mediated forces contribute to fate transitions during the acquisition of stemness from somatic cell states.
URL:https://seasevents.nmsdev7.com/event/be-seminar-timothy-downing-uc-irvine/
LOCATION:216 Moore Building
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231117T100000
DTEND;TZID=America/New_York:20231117T110000
DTSTAMP:20260404T101550
CREATED:20231012T002153Z
LAST-MODIFIED:20231012T002153Z
UID:10007727-1700215200-1700218800@seasevents.nmsdev7.com
SUMMARY:PRECISE Seminar: What can we learn about AI and data science from the vision field?
DESCRIPTION:Abstract\n\nRemarkable advances in imaging\, computation\, and technology are rapidly moving us into an era where biomedical knowledge discovery is increasingly limited only by creativity. This has resulted in unprecedented opportunities to improve the diagnosis and treatment of disease. The vision field has been at the forefront of these advances in AI for healthcare because of the easy accessibility of images and clinical data. \nThis talk will discuss challenges and opportunities involving artificial intelligence and data science in ophthalmology research and applications to clinical care. Specific examples will be given from the speaker’s perspective as an investigator in this field and as Director of the National Eye Institute (NEI)\, which directs and funds vision research in the United States. This will include discussion of challenges in the accuracy and process of ophthalmic diagnosis\, insights and gaps in knowledge regarding AI research in ophthalmology\, and ways in which these challenges and opportunities are generalizable to other medical fields. It will conclude with discussion of current NEI priorities including data sharing\, data harmonization\, data generation\, medical education in informatics and data science\, methodological innovation\, and population health.
URL:https://seasevents.nmsdev7.com/event/precise-seminar-what-can-we-learn-about-ai-and-data-science-from-the-vision-field/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="PRECISE":MAILTO:wng@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231117T103000
DTEND;TZID=America/New_York:20231117T114500
DTSTAMP:20260404T101550
CREATED:20231025T145813Z
LAST-MODIFIED:20231025T145813Z
UID:10007744-1700217000-1700221500@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP on Robotics: Seth Hutchinson\, Georgia Institute of Technology\, “Model-Based Methods in Today’s Data-Driven Robotics Landscape”
DESCRIPTION:This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nData-driven machine learning methods are making advances in many long-standing problems in robotics\, including grasping\, legged locomotion\, perception\, and more. There are\, however\, robotics applications for which data-driven methods are less effective\, and sometime inappropriate. Data acquisition can be expensive\, time consuming\, or dangerous — to the surrounding workspace\, humans in the workspace\, or the robot itself. In such cases\, generating data via simulation might seem a natural recourse\, but simulation methods come with their own limitations\, particularly when nondeterministic effects are significant\, or when complex dynamics are at play\, requiring heavy computation and exposing the so-called sim2real gap. Another alternative is to rely on a set of demonstrations\, limiting the amount of required data by careful curation of the training examples; however\, these methods fail when confronted with problems that were not represented in the training examples (so-called out-of-distribution problems)\, and this precludes the possibility of providing provable performance guarantees. \nIn this talk\, I will describe recent work on robotics problems that do not readily admit data-driven solutions\, including flapping flight by a bat-like robot\, vision-based control of soft continuum robots\, acrobatic maneuvering by quadruped robots\, a cable-driven graffiti-painting robot\, bipedal locomotion over granular media\, and ensuring safe operation of mobile manipulators in HRI scenarios. I will describe some specific difficulties that confront data-driven methods for these problems\, and describe how model-based approaches can provide workable solutions. Along the way\, I will also discuss how judicious incorporation of data-driven machine learning tools can enhance performance of these methods.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-on-robotics-seth-hutchinson-georgia-institute-of-technology-model-based-methods-in-todays-data-driven-robotics-landscape/
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:20231117T110000
DTEND;TZID=America/New_York:20231117T120000
DTSTAMP:20260404T101550
CREATED:20230829T201813Z
LAST-MODIFIED:20230829T201813Z
UID:10007658-1700218800-1700222400@seasevents.nmsdev7.com
SUMMARY:ESE Fall Seminar - "Stochastic Geometry for Networks"
DESCRIPTION:Stochastic geometry is a branch of probability theory that deals with the study of random spatial patterns. Random point patterns\, termed point processes\, are the most basic such objects that appear in numerous applications. After presenting a brief introduction to point processes\, we will present our work on the stochastic modeling and analysis of wireless cellular networks\, which departs from the conventional approaches based on deterministic models. In addition to results related to key wireless metrics\, such as coverage and rate\, we will also discuss new results related to Poisson point processes that were inspired by this work. Building on this discussion\, we will introduce line processes\, which along with point processes\, allow us to model networks on the lines (such as transportation networks). After providing a brief historical perspective and the construction of line processes\, we will define a doubly stochastic point process by placing an independent Poisson point process on each line of the Poisson line process\, which we term the Poisson Line Cox Process. We will discuss key properties and applications of this point process to vehicular and transportation networks. We will also briefly discuss new contributions related to path distance distributions that were inspired by this work. In the last segment\, we will discuss our ongoing work on developing a new mathematical framework to study landmark-based geolocation by modeling generic landmarks (such as trees and lampposts) as point processes. In addition to presenting our early results\, we will also discuss possible connections of this approach to information and coding theory. \nIf you are interested in more details\, please refer to the following monographs. They are accessible free of cost from most university campuses. Monograph [M1] summarizes our work on cellular networks and is written to be the first introduction to this area. Monograph [M2] summarizes our work on line processes and their applications to vehicular networks. \n[M1] An Introduction to Cellular Network Analysis Using Stochastic Geometry: https://link.springer.com/book/10.1007/978-3-031-29743-4 \n[M2] Poisson Line Cox Process: Foundations and Applications to Vehicular Networks: https://link.springer.com/book/10.1007/978-3-031-02379-8
URL:https://seasevents.nmsdev7.com/event/ese-fall-seminar-title-tbd-9/
LOCATION:Berger Auditorium (Room 13)\, Skirkanich Hall\, 210 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:20231122T100000
DTEND;TZID=America/New_York:20231122T120000
DTSTAMP:20260404T101550
CREATED:20231117T211318Z
LAST-MODIFIED:20231117T211318Z
UID:10007763-1700647200-1700654400@seasevents.nmsdev7.com
SUMMARY:ESE PhD Thesis Defense: "Learning\, Privacy\, and Reliable Communication in Large Data Networks"
DESCRIPTION:This thesis explores advancements in three distinct domains: communications\, privacy\, and machine learning. Within the realm of communication\, a comprehensive study is conducted on channel coding at low capacity\, a critical aspect of Internet of Things (IoT) technology requiring reliable transmission over channels with minimal capacity. Despite existing finite-length analyses yielding inaccurate predictions and current coding schemes proving inefficient in low-capacity scenarios\, this thesis addresses these limitations. It characterizes the finite-length fundamental limits of channel coding for essential channels\, offering provably efficient code designs tailored for low-capacity environments. In the domain of privacy\, attention is directed towards a decentralized consensus problem handled in a private manner. Existing methods for classical consensus problems often involve openly exchanging private information. This thesis proposes an algorithmic framework capable of achieving the exact limit and the fastest possible convergence rate while safeguarding the privacy of users’ local values. Additionally\, a novel information-theoretic metric is introduced to effectively measure the privacy of a node concerning another node within the network. In the machine learning domain\, a rigorous mathematical framework is established to investigate the function class of Graph Neural Networks (GNNs) in relation to their initialization and internal estimators. Utilizing a unique technique for the algebraic representation of a multiset of vectors\, termed Multiset Equivalent Function (MEF)\, it is demonstrated that GNNs can generate functions satisfying a weight-equipped variant of permutation-equivariance using distinct features. The MEF technique further reveals that GNNs\, equipped with node identifiers in their initialization\, can generate any function in a fully connected and weighted graph scenario. These findings contribute to a formal understanding of the intricate relationship between GNNs and other algorithmic procedures applied to graphs\, such as min-cut value and shortest path problems\, as well as the re-derivation of the known connection between GNNs and the Weisfeiler-Lehman graph-isomorphism test.
URL:https://seasevents.nmsdev7.com/event/ese-phd-thesis-defense-learning-privacy-and-reliable-communication-in-large-data-networks/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231127T110000
DTEND;TZID=America/New_York:20231127T120000
DTSTAMP:20260404T101550
CREATED:20231114T142014Z
LAST-MODIFIED:20231114T142014Z
UID:10007761-1701082800-1701086400@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Mechanics-Informed Optimization for Enhanced Adhesion and Toughness"
DESCRIPTION:Structural design optimization has long played a crucial role in engineering\, often with the goal of creating stiff and lightweight structures for aerospace and other applications. However\, optimizing structures against failure is also crucial and has been less explored. Failure at interfaces is particularly challenging in design optimization as they involve high local stress concentrations and singular stresses. This thesis will demonstrate routes to integrate mechanics models and optimization schemes to engineer interfaces with improved adhesion and toughness. Specifically\, four distinct structural design cases are considered: adhesive fibrils\, shear lap joints\, architected adhesive joints\, and frames with locally tunable stiffness. The computational framework uses finite element analysis with multiple optimization methods\, including gradient and heuristic-based techniques\, as well as machine learning-based approaches. We show that performance can be improved by formulating optimization schemes and objective functions based on the principles of interface mechanics and failure. Optimal designs are determined via these computational schemes and validated via experiments on several different material systems. For example\, the force capacity of a lap joint was enhanced by a factor of 2.4x by optimizing the thickness profile of the joint. The versatility of the computational and optimization schemes that have been developed enables them to be extended to other scenarios where performance can be improved by optimizing geometry and structure to control stresses.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-mechanics-informed-optimization-for-enhanced-adhesion-and-toughness/
LOCATION:DRLB 3W2\, 209 S. 33rd Street\, Philadelphia\, Pennsylvania\, 19104
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:20231128T100000
DTEND;TZID=America/New_York:20231128T113000
DTSTAMP:20260404T101550
CREATED:20231016T154826Z
LAST-MODIFIED:20231016T154826Z
UID:10007732-1701165600-1701171000@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Advancing Bioadhesive Technologies with Mechanical Principles"
DESCRIPTION:Bioadhesive technologies are important in a wide range of applications\, spanning from wound management to wearable technologies. Forming and controlling tough adhesion on biological tissues has been a long-lasting challenge\, necessitating transdisciplinary approaches. In my talk\, I will share our recent progress in the design\, mechanics\, and applications of tough bioadhesives. I will first discuss the limitations of clinically used surgical glues and blood clots in terms of adhesion properties. I will then present the mechanical principles for making tough bioadhesives that exhibit superior adhesion performance on diverse tissues. Furthermore\, I will discuss our transdisciplinary approaches and underlying mechanisms for controlling tough bioadhesion through ultrasound and interfacial entanglements. Lastly\, I will showcase the applications of tough bioadhesives in wound management\, tissue repair\, and hemorrhage control. This talk will highlight the synergy of materials and mechanics in the development of new biomaterials poised to address clinical challenges.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-advancing-bioadhesive-technologies-with-mechanical-principles/
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:20231128T153000
DTEND;TZID=America/New_York:20231128T163000
DTSTAMP:20260404T101550
CREATED:20231120T181101Z
LAST-MODIFIED:20231120T181101Z
UID:10007764-1701185400-1701189000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Mitigating Technology Abuse in Intimate Partner Violence and Encrypted Messaging"
DESCRIPTION:Computer security is traditionally about the protection of technology\, whereas trust and safety efforts focus on preventing technology abuse from harming people. In this talk\, I’ll explore the interplay between security and tech abuse\, and make the case that trust and safety represents an important frontier for computer security researchers. To do so\, I’ll draw on examples from two lines of my recent work. \nFirst\, I’ll overview our work on technology abuse in the context of intimate partner violence (IPV). IPV is a widespread social ill affecting about one in four women and one in ten men at some point in their lives.  Via interviews with survivors and professionals\, online measurement studies\, and reverse engineering of malicious tools\, our research has provided the most granular view to date of technology abuse in IPV contexts. This has helped educate our efforts on intervention design\, most notably in the form of what we call clinical computer security: direct\, expert assistance to help survivors navigate technology abuse.  Our work led to establishing the Clinic to End Tech Abuse\, which has so far worked to help hundreds of survivors of IPV in New York City. \nSecond\, I’ll discuss how basic security tools like encrypted messaging need to be adapted in light of tech abuse. Here we find a fundamental tension between the desire for messaging service providers to help moderate malicious content and the confidentiality goals of encryption\, which prevent the platform from seeing content. I’ll show how we end up reconceptualizing and redesigning basic cryptographic tools to more securely support abuse mitigation. \nThe talk will include content on abuse\, including discussion of physical\, sexual\, and emotional violence.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-mitigating-technology-abuse-in-intimate-partner-violence-and-encrypted-messaging/
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:20231129T120000
DTEND;TZID=America/New_York:20231129T130000
DTSTAMP:20260404T101550
CREATED:20231127T133016Z
LAST-MODIFIED:20231127T133016Z
UID:10007773-1701259200-1701262800@seasevents.nmsdev7.com
SUMMARY:PSOC Seminar: Denise Montell\, University of California\, Santa Barbara
DESCRIPTION:PSOC@Penn Seminar\, \nWednesday Nov 29th \n  \n** New Location **\n \nDRL 2N3 \n2N3 conference/seminar room is in DRL 2nd floor towards end of hallway that parallels Walnut St\n \n-Noon – 1.00pm : PSOC  talk \nSpeaker: Denise Montell\, PhD \nDuggan Professor and Distinguished Professor\, \nMolecular\, Cellular\, and Developmental Biology\, University of California\, Santa Barbara \nhttps://www.mcdb.ucsb.edu/people/faculty/denise-montell \nhttps://denisemontell.mcdb.ucsb.edu/ \n Talk : “TBA”  \nContact manu@seas.upenn.edu with any questions.
URL:https://seasevents.nmsdev7.com/event/psoc-seminar-denise-montell-university-of-california-santa-barbara/
LOCATION:DRL 2N3
CATEGORIES:Seminar
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231129T120000
DTEND;TZID=America/New_York:20231129T131500
DTSTAMP:20260404T101550
CREATED:20230928T141936Z
LAST-MODIFIED:20230928T141936Z
UID:10007710-1701259200-1701263700@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "Inherent Interpretability via Language Model Guided Bottleneck Design" (Mark Yatskar\, Penn)
DESCRIPTION:ABSTRACT: \nAs deep learning systems improve\, their applicability to critical domains is hampered because of a lack of transparency. Post-hoc explanations attempt to address this concern but they provide no guarantee of faithfulness to the model’s computations. Inherently interpretable models are an alternative but such models are often considered to be too simple to perform well. In this talk we challenge this assumption by demonstrating how to create high performance inherently interpretable models. Our methods extend concept bottlenecks\, a class of inherently interpretable models\, by casting their creation as a generation problem for large language models. This allows us to develop search routines for finding high performing bottlenecks. We specialize this general approach to image classification\, text classification\, and visual question answering. In these domains\, language model guided bottleneck models perform competitively to their uninterpretable counterparts and in low-data settings even sometimes outperform them.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-mark-yatskar/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231129T123000
DTEND;TZID=America/New_York:20231129T143000
DTSTAMP:20260404T101550
CREATED:20231122T184209Z
LAST-MODIFIED:20231122T184209Z
UID:10007769-1701261000-1701268200@seasevents.nmsdev7.com
SUMMARY:CBE Doctoral Dissertation: “A Multiscale Computational Framework for Simulating Thrombus Growth Under Flow” (Kaushik Shankar)
DESCRIPTION:Abstract:\n\nModeling thrombus growth in pathological flows allows evaluation of risk under patient-specific pharmacological\, hematological\, and hemodynamical conditions. To this end\, we have developed a 3D multiscale framework for the prediction of thrombus growth under flow on a spatially resolved surface presenting collagen and tissue factor (TF). The multiscale framework is composed of four coupled modules: a Neural Network (NN) that accounts for platelet calcium signaling\, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions\, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing soluble agonist release and transport\, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. A reduced model of the coagulation cascade was embedded into the framework to account for TF-driven thrombin production. The 3D model was first tested against in vitro microfluidics experiments of whole blood perfusion with various antiplatelet agents targeting COX-1\, P2Y1\, or the IP receptor. The model was able to accurately capture the evolution and morphology of the growing thrombus. Certain problems of 2D models for thrombus growth (artifactual dendritic growth) were naturally avoided with realistic trajectories of platelets in 3D flow. The generalizability of the 3D multiscale solver enabled simulations of important clinical situations\, such as cylindrical blood vessels and acute flow narrowing (stenosis). Enhanced platelet-platelet bonding at pathologically high shear rates (e.g.\, von Willebrand factor unfolding) was required for accurately describing thrombus growth in stenotic flows.\n\nTo enable larger computations in a reasonable amount of time\, each module within the multiscale framework was individually parallelized. Parallelization was achieved by developing in-house parallel routines for NN and LKMC\, while the open-source libraries OpenFOAM and Palabos were used for FVM and LB\, respectively. Importantly\, the parallel LKMC solver utilizes particle-based parallel decomposition allowing efficient use of cores over highly heterogeneous regions of the domain. The parallelized model was validated against a reference serial version for accuracy\, demonstrating comparable results for both microfluidic and stenotic arterial clotting conditions. Moreover\, the parallelized framework was shown to scale essentially linearly on up to 64 cores for a benchmark simulation of thrombus growth in a stenotic vessel of size ~1 mm. Overall\, the parallelized multiscale framework allows consideration of patient-specific platelet signaling and vascular geometry for the prediction of thrombotic episodes.\n\n—\nDate: Wednesday\, November 29\, 2023\nTime: 12:30 PM\nLocation: PICS Room 534\, 3401 Walnut Street \nZoom link: https://upenn.zoom.us/j/99504914980
URL:https://seasevents.nmsdev7.com/event/cbe-doctoral-dissertation-a-multiscale-computational-framework-for-simulating-thrombus-growth-under-flow-kaushik-shankar/
LOCATION:Room 534 A Wing\, 3401 Walnut\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231129T150000
DTEND;TZID=America/New_York:20231129T160000
DTSTAMP:20260404T101550
CREATED:20231122T172921Z
LAST-MODIFIED:20231122T172921Z
UID:10007767-1701270000-1701273600@seasevents.nmsdev7.com
SUMMARY:Fall 2023 GRASP SFI: Xiaolong Wang\, University of California San Diego\, "Generalizable Geometric Robot Learning"
DESCRIPTION:This is a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nRobot learning has witnessed significant progress in terms of generalization recently\, with the help of data-driven learning and image/text foundation models. While these achievements are encouraging\, most tasks conducted in this context are relatively simple (e.g.\, pick-and-place with a parallel gripper). In this talk\, I will talk about our recent efforts to learn generalizable skills focusing on tasks with rich physical contacts and geometric reasoning. Specifically\, I will discuss our research on: (i) the use of a large number of low-cost\, binary force sensors to enable Sim2Real manipulation; (ii) unifying 3D and semantic representation learning to generalize policy learning across diverse objects and scenes. I will showcase the real-world applications of our research\, including dexterous manipulation\, and legged locomotion control\, and language-driven mobile manipulation.
URL:https://seasevents.nmsdev7.com/event/fall-2023-grasp-sfi-xiaolong-wang/
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
END:VCALENDAR