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DTSTART;TZID=America/New_York:20231107T100000
DTEND;TZID=America/New_York:20231107T113000
DTSTAMP:20260404T020514
CREATED:20231010T191936Z
LAST-MODIFIED:20231010T191936Z
UID:10007723-1699351200-1699356600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Advancing the Versatility of Legged Robots and Assistive Devices"
DESCRIPTION:Recent years have witnessed tremendous growth in the capabilities of legged robots\, with quadrupeds and humanoids demonstrating athletic behaviors that even five years ago were out of reach. Likewise\, actively powered lower-limb assistive devices have made great strides in their maturity\, with hardware such as the Open-Source Leg broadening access for future breakthroughs. \nDespite this progress\, the wide variability of real-world environments and users remains a pressing challenge to practical applications. It is fundamentally impossible to train our robots in the lab for anything they may encounter in an open world! As steps toward addressing this challenge\, the talk will first discuss recent work on the control of the MIT Mini Cheetah\, which considers new computational methods for the robot to reason through its actions on the fly in complex environments. The second part of the talk will then present ongoing research on improving user interfaces for lower-extremity prosthetic limbs to make human/robot interaction more fluid. Collectively\, this work expands the ability of these systems to tailor their motions to new environments and users\, paving the way for broader adoption in the “wild.”
URL:https://seasevents.nmsdev7.com/event/meam-seminar-advancing-the-versatility-of-legged-robots-and-assistive-devices/
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:20231107T100000
DTEND;TZID=America/New_York:20231107T120000
DTSTAMP:20260404T020514
CREATED:20231023T140841Z
LAST-MODIFIED:20231023T140841Z
UID:10007741-1699351200-1699358400@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Physiologically Induced High Gaussian Curvature Drives Nuclear Lamina Rupture and Cytoskeletal Displacement—Contributing to Downstream Dysfunction" (Michael Tobin)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Dennis Discher are pleased to announce the Doctoral Dissertation Defense of Michael Tobin.\n\nTitle: Physiologically Induced High Gaussian Curvature Drives Nuclear Lamina Rupture and Cytoskeletal Displacement—Contributing to Downstream Dysfunction\n \nDate: Tuesday\, November 7\, 2023\nTime: 10AM\nLocation: Glandt Forum at the Singh Center.\n\nThere is a zoom option for virtual listeners.\n\nTopic: Michael Tobin Thesis Defense\nTime: Nov 7\, 2023 10:00 AM Eastern Time (US and Canada) \n\nJoin Zoom Meeting\nhttps://upenn.zoom.us/j/93613731189?pwd=TUtCZnprZVBLM3pweXRkR3FnTm5IQT09 \nMeeting ID: 936 1373 1189\nPasscode: 262280 \n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-physiologically-induced-high-gaussian-curvature-drives-nuclear-lamina-rupture-and-cytoskeletal-displacement-contributing-to-downstream-dysfunction-michae/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231107T133000
DTEND;TZID=America/New_York:20231107T143000
DTSTAMP:20260404T020514
CREATED:20231103T125456Z
LAST-MODIFIED:20231103T125456Z
UID:10007751-1699363800-1699367400@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Reversing Engineering the Anesthetic State: Insights from Behavior and CNS Circuit Cracking" (Andrzej Wasilczuk)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Max Kelz are pleased to announce the Doctoral Dissertation Defense of Andrzej Wasilczuk \nReversing Engineering the Anesthetic State: Insights from Behavior and CNS Circuit Cracking \nNovember 7th\, 1:30-2:30pm \nJordan Medical Education Center\, Room 505EW\n3400 Civic Center Blvd \nPhiladelphia\, PA 19104 \nA hybrid option is available using this link: \nhttps://pennmedicine.zoom.us/j/94632129951?pwd=NkFDRnZuejBNbGlBalR2K2d3cGY3Zz09 \nMeeting ID: 946 3212 9951 \nPasscode: 447098
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-reversing-engineering-the-anesthetic-state-insights-from-behavior-and-cns-circuit-cracking-andrzej-wasilczuk/
LOCATION:Jordan Medical Education Center\, Room 505EW\, 3400 Civic Center Blvd
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:20231108T120000
DTEND;TZID=America/New_York:20231108T131500
DTSTAMP:20260404T020514
CREATED:20230928T141745Z
LAST-MODIFIED:20230928T141745Z
UID:10007708-1699444800-1699449300@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "The Future of Algorithm Auditing is Sociotechnical" (Danaë Metaxa\, Penn)
DESCRIPTION:ABSTRACT:  \nAlgorithm audits are powerful tools for studying black-box systems without direct knowledge of those systems’ inner workings. While they have been effectively deployed to identify harms and biases in algorithmic content\, algorithm audits’ narrow focus on technical components stop short of considering users themselves as integral and dynamic parts of the system\, to be audited alongside its algorithmic components. \nAfter an overview of the state of the art in algorithm auditing\, this talk will introduce sociotechnical auditing: evaluating algorithmic systems at the sociotechnical level\, focusing on the interplay between algorithms and users as each impacts the other over time. I will also present Intervenr\, a platform we developed to conduct browser-based\, longitudinal sociotechnical audits\, and a case study in which we deployed Intervenr to investigate the central claim of online targeted advertising systems: that targeted ads perform better with users. Finally\, I will conclude by discussing some of my group’s current work\, expanding the auditing method to novices and youth\, and developing post-auditing tools for collective action.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-danae-metaxa-penn/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231108T150000
DTEND;TZID=America/New_York:20231108T160000
DTSTAMP:20260404T020514
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:20260404T020514
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:20260404T020514
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:20260404T020514
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:20260404T020514
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:20260404T020514
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:20260404T020514
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:20260404T020514
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
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