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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221107T130000
DTEND;TZID=America/New_York:20221107T140000
DTSTAMP:20260405T142249
CREATED:20220901T141104Z
LAST-MODIFIED:20220901T141104Z
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SUMMARY:PSOC Seminar: “Bioengineered human brain microvascular network to model brain tumor and mechanobiology of glioma invasion" (Guohao Dai\, Northeastern University)
DESCRIPTION:Fall 2022 Hybrid-Seminar Series  \nMondays 1.00-2.00 pm (EST)  \nTowne 225 / Raisler Lounge   \nFor Zoom link\, please contact <manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psoc-seminar-bioengineered-human-brain-microvascular-network-to-model-brain-tumor-and-mechanobiology-of-glioma-invasion-guohao-dai-northeastern-university/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221107T153000
DTEND;TZID=America/New_York:20221107T163000
DTSTAMP:20260405T142249
CREATED:20221027T124316Z
LAST-MODIFIED:20221027T124316Z
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SUMMARY:ESE Fall Colloquium - "On the Principles of Parsimony and Self-Consistency: Structured Compressive Closed-Loop Transcription"
DESCRIPTION:Ten years into the revival of deep networks and artificial intelligence\, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of intelligence in general. We introduce two fundamental principles\, Parsimony and Self-consistency\, that address two fundamental questions regarding Intelligence: what to learn and how to learn\, respectively. We argue that these two principles can be realized in entirely measurable and computable ways for an important family of structures and models\, known as a linear discriminative representation (LDR). The two principles naturally lead to an effective and efficient computational framework\, known as a compressive closed-loop transcription\, that unifies and explains the evolution of modern deep networks and modern practices of artificial intelligence. Within this framework\, we will see how fundamental ideas in information theory\, control theory\, game theory\, sparse coding\, and optimization are closely integrated in such a closed-loop system\, all as necessary ingredients to learn autonomously and correctly. We demonstrate the power of this framework for learning discriminative\, generative\, and autoencoding models for large-scale real-world visual data\, with entirely white-box deep networks\, under all settings (supervised\, incremental\, and unsupervised). We believe that these two principles are the cornerstones for the emergence of intelligence\, artificial or natural\, and the compressive closed-loop transcription is a universal learning engine that serves as the basic learning units for all autonomous intelligent systems\, including the brain. \nRelated papers can be found at: https://arxiv.org/abs/2207.04630 and https://www.mdpi.com/1099-4300/24/4/456/htm
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-on-the-principles-of-parsimony-and-self-consistency-structured-compressive-closed-loop-transcription/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 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:20221108T100000
DTEND;TZID=America/New_York:20221108T113000
DTSTAMP:20260405T142249
CREATED:20221019T133310Z
LAST-MODIFIED:20221019T133310Z
UID:10007337-1667901600-1667907000@seasevents.nmsdev7.com
SUMMARY:Tedori-Callinan Lecture: "Mixing of Granular Materials\, Inertial Suspensions\, and Cement"
DESCRIPTION:Flows of particulate materials are ubiquitous in nature and industry. Predictions of flow rates and mixing times rely on an understanding of the rheological properties of the materials\, which can differ considerably from that associated with a single-phase fluid. This presentation highlights some unique features of granular materials and inertial suspensions and includes recent experimental results. In addition\, the seminar overviews new work related to the mixing and gaseous diffusion in cement. Cement production releases significant amount of carbon dioxide; carbon dioxide can be partially reabsorbed into cement by diffusion through the multiphase material. The ongoing research includes modeling of the carbon dioxide uptake and considers ways to accelerate the process\, such as mixing with the cement paste.
URL:https://seasevents.nmsdev7.com/event/tedori-callinan-lecture-mixing-of-granular-materials-inertial-suspensions-and-cement/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Distinguished Lecture
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221109T103000
DTEND;TZID=America/New_York:20221109T123000
DTSTAMP:20260405T142249
CREATED:20221107T133347Z
LAST-MODIFIED:20221107T133347Z
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SUMMARY:ESE Ph.D. Thesis Defense: "Design of Low-power CMOS Integrated Systems: from Biomedical Applications to Optical Links"
DESCRIPTION:Electronic and photonic microsystems realized in the form of integrated circuits (IC) has been revolutionizing numerous fields that traditionally exploit bulky implementations. The advantages stemming from device miniaturization have opened up wide and growing opportunities to design for unprecedented functionality and enhanced performance. Leveraging novel CMOS and silicon photonic IC designs\, this thesis presents four energy-efficient systems focusing on sensing and communication techniques: first\, a somatosensory feedback system\, composed of wireless body channel transceivers and implantable sensor nodes\, is proposed to restore a sense of touch to a paralyzed hand; second\, an analog SoC is implemented for neural signal recording and processing\, achieving accurate and unsupervised classification of action potentials; third\, a monolithically integrated\, power and area efficient PAM4 optical receiver is developed for a wavelength-division multiplexing (WDM) system achieving 1 Tb/s aggregate data-rate; finally\, an electronic-photonic lab-on-chip with optical power and data transmission is proposed to utilize the long-reach and low-cost fiber interconnects.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-design-of-low-power-cmos-integrated-systems-from-biomedical-applications-to-optical-links/
LOCATION:Levine 512
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:20221109T120000
DTEND;TZID=America/New_York:20221109T133000
DTSTAMP:20260405T142249
CREATED:20220909T133355Z
LAST-MODIFIED:20220909T133355Z
UID:10007265-1667995200-1668000600@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: Decision-Aware Learning for Global Health Supply Chains\, Osbert Bastani (University of Pennsylvania)
DESCRIPTION:ABSTRACT: \nMachine learning algorithms are increasingly used in conjunction with optimization to guide decision making. A key challenge is aligning the machine learning loss with the decision-making loss. Existing solutions have limited flexibility and/or scale poorly to large datasets. We propose a principled decision-aware learning algorithm that uses a Taylor expansion of the optimal decision loss to derive the machine learning loss. Importantly\, our approach only requires a simple re-weighting of the training data\, allowing it to easily and scalably be incorporated into complex modern data science pipelines while producing sizable efficiency gains. We apply our framework to optimize the distribution of essential medicines in Sierra Leone in collaboration with their National Medical Supplies Agency. Out-of-sample results demonstrate that our end-to-end approach significantly reduces unmet demand across 1000+ health facilities throughout Sierra Leone.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-tba-osbert-bastani-university-of-pennsylvania/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221109T150000
DTEND;TZID=America/New_York:20221109T160000
DTSTAMP:20260405T142249
CREATED:20221004T192423Z
LAST-MODIFIED:20221004T192423Z
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SUMMARY:Fall 2022 GRASP SFI: Roberto Calandra\, Meta AI\, "Perceiving\, Understanding\, and Interacting through Touch"
DESCRIPTION:This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom. \nABSTRACT\nTouch is a crucial sensor modality in both humans and robots. Recent advances in tactile sensing hardware have resulted — for the first time — in the availability of mass-produced\, high-resolution\, inexpensive\, and reliable tactile sensors. In this talk\, I will argue for the importance of creating a new computational field of “Touch processing” dedicated to the processing and understanding of touch\, similarly to what computer vision is for vision. This new field will present significant challenges both in terms of research and engineering. To start addressing some of these challenges\, I will introduce our open-source ecosystem dedicated to touch sensing research. Finally\, I will present some applications of touch in robotics and discuss other future applications.
URL:https://seasevents.nmsdev7.com/event/fall-2022-grasp-sfi-roberto-calandra/
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:20221109T153000
DTEND;TZID=America/New_York:20221109T163000
DTSTAMP:20260405T142249
CREATED:20220909T195904Z
LAST-MODIFIED:20220909T195904Z
UID:10007277-1668007800-1668011400@seasevents.nmsdev7.com
SUMMARY:CBE Seminar Series: "Targeted Delivery of Macromolecular Therapeutics" (Christopher A. Alabi\, Cornell University)
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-series-targeted-delivery-of-macromolecular-therapeutics-christopher-a-alabi-cornell-university/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221110T103000
DTEND;TZID=America/New_York:20221110T113000
DTSTAMP:20260405T142249
CREATED:20221028T133859Z
LAST-MODIFIED:20221028T133859Z
UID:10007346-1668076200-1668079800@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: “Understanding Degradation in Metal Halide Perovskite Solar Cells and Modules”
DESCRIPTION:Halide perovskite solar cells (PSCs) have been the focus of much research in recent years due to their extremely high photoconversion efficiencies and their ability to be synthesized by solution processing.  These materials crystallize in the perovskite\, AMX3 crystal structure where A is a monovalent cation (e.g. methyl ammonium\, MA\, formamidinium\, FA\, and/or Cs)\, M is the metal cation and X is the halide anion. While great strides have been made to optimize the device performance of PSCs\, there remain open questions as to the long-term field performance of these materials. While constant improvement in lab scale performance stability is being demonstrated a fundamental understanding of degradation mechanisms can still provide key insight into performance improvements. In addition\, to fundamental lab scale studies field performance will be required to de-risk this technology for commercialization. In this talk\, I will cover examples of both lab scale and field studies to improve our understanding of PSCs degradation mechanisms. First\, I will discuss an application of X-ray scattering methods to probe the nanoscale heterogeneity of PSC absorber layers and couple these results to device level stability studies to understand the role heterogeneity plays in device performance. Finally\, I will present a brief overview of an initial field demonstration of PSC modules as part of the Perovskite PV Accelerator for Commercializing Technologies\, PACT\, program. Together this work aims to improve our confidence in real world PSC module performance.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-understanding-degradation-in-metal-halide-perovskite-solar-cells-and-modules/
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:20221110T123000
DTEND;TZID=America/New_York:20221110T133000
DTSTAMP:20260405T142249
CREATED:20221101T123809Z
LAST-MODIFIED:20221101T123809Z
UID:10007348-1668083400-1668087000@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium - "Phase Transitions\, Symmetry\, and Reed-Muller Codes on BMS Channels"
DESCRIPTION:This talk will begin by discussing phase transitions in high-dimensional statistical inference problems. Some effort will be made to distinguish between problems with random structure (e.g.\, random codes and sparse PCA) and problems with deterministic structure (e.g.\, highly symmetric codes such as Reed-Muller codes). For problems with deterministic structure\, we will observe that symmetry can sometimes play a key role in characterizing their phase transitions. In particular\, I will describe my recent work with Galen Reeves that proves Reed-Muller (RM) codes achieve capacity on binary memoryless symmetric (BMS) channels with respect to bit-error rate. This result resolves a long-standing open problem that connects information theory and error-correcting codes. Our approach generalizes some elements of an earlier proof for the binary erasure channel but also derives new tools to avoid previous steps that do not generalize. The new idea is to combine a nesting property of RM codes with new information inequalities relating the derivative of the conditional entropy (as a function of the channel parameter) with minimum mean-squared error estimation.
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-phase-transitions-symmetry-and-reed-muller-codes-on-bms-channels/
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:20221110T150000
DTEND;TZID=America/New_York:20221110T163000
DTSTAMP:20260405T142249
CREATED:20221107T153150Z
LAST-MODIFIED:20221107T153150Z
UID:10007354-1668092400-1668097800@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Resilient\, Information Theoretic\, Active Exploration for Multi-Robot Teams"
DESCRIPTION:Over the past decades we have seen robots move from constrained and heavily designed industrial environments out into the world. Along with this shift there is a need for smaller\, safer\, and less expensive robots which can complete tasks autonomously in teams\, sometimes covering large areas. Multi-robot teams can expand the capabilities of a single robot\, however working with teams presents its own set of challenges. Robots must be able to reach a shared understanding of their task as well as gracefully recover from single member failures\, often while having no centralized coordination. \nIn many task assignment and coordination applications\, it is assumed that the robots begin with a shared understanding of the environment\, often in the form of a map. In small application spaces\, such maps could be made by hand\, but in the case of large or potentially hazardous environments\, it will be necessary to have the robots themselves create the map. To this end\, in this thesis we present two map representations designed specifically for autonomous mapping by robots with high-noise sensors. For each method\, we develop an information theoretic value function which can be used to autonomously maximize the information gained about the map. This is a principled approach which accounts for both information gained by exploring new areas\, as well as information gained by further inspection of the existing map to account for sensor uncertainty. \nAdditionally\, in applications where inexpensive robots are operating autonomously in large and potentially hazardous areas\, the likelihood increases that a robot on the team can become non-cooperative\, either through unintentional damage or through tampering. To be able to autonomously cooperate as a team it is important that the system can recover gracefully from such failures. Consensus algorithms are ubiquitous in distributed systems as they provide a mechanism for reaching agreement within a team using only local communications. We extend a highly distributed approach to resilient consensus for static networks to applications with multi-robot teams. This approach has been largely limited to small static networks because verification that the network is sufficiently connected is formally hard. First we develop a method which can be used for teams with time-varying range-based communication which is suitable for tasks where robots are not required to spread out in the environment. We then present a method that is well suited to mapping and coverage applications which uses a well known communication structure to guarantee successful resilient consensus. \nThe methods presented in this thesis lay the groundwork for a class of resilient active information gathering algorithms which can be used for low cost teams. Such algorithms have wide ranging applicability\, from persistent monitoring tasks such as those found in agriculture to time critical tasks such as search and rescue.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-resilient-information-theoretic-active-exploration-for-multi-robot-teams/
LOCATION:Room 313\, Singh Center for Nanotechnology\, 3205 Walnut 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:20221111T103000
DTEND;TZID=America/New_York:20221111T114500
DTSTAMP:20260405T142249
CREATED:20220830T160006Z
LAST-MODIFIED:20220830T160006Z
UID:10007239-1668162600-1668167100@seasevents.nmsdev7.com
SUMMARY:Fall 2022 GRASP on Robotics: Radhika Nagpal\, Princeton University\, "Towards Collective Artificial Intelligence"
DESCRIPTION:This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom. \nABSTRACT\nIn nature\, groups of thousands of individuals cooperate to create complex structure purely through local interactions — from cells that form complex organisms\, to social insects like termites and ants that build nests and self-assemble bridges\, to the complex and mesmerizing motion of fish schools and bird flocks. What makes these systems so fascinating to scientists and engineers alike\, is that even though each individual has limited ability\, as a collective they achieve tremendous complexity. What would it take to create our own artificial collectives of the scale and complexity that nature achieves? In this talk I will discuss several ongoing projects that use inspiration from biological self-assembly to create robotic systems: The Kilobot swarm inspired by cells\, the Termes and EcitonR robots inspired by the 3D assembly of termites and army ants\, and the BlueSwarm project inspired by fish schools. There are many challenges for both building and programming robot swarms\, and we use these systems to explore decentralized algorithms\, embodied intelligence\, and methods for synthesizing complex global behavior. Our theme is the same: can we create simple robots that cooperate to achieve collective complexity?
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-radhika-nagpal/
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:20221111T130000
DTEND;TZID=America/New_York:20221111T150000
DTSTAMP:20260405T142249
CREATED:20221107T172611Z
LAST-MODIFIED:20221107T172611Z
UID:10007356-1668171600-1668178800@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Multibreath Hyperpolarized Gas Imaging of Lung Ventilation and Gas Exchange in Humans for Diagnosis and Treatment Response Monitoring" (Hooman Hamedani)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Rahim Rizi are pleased to announce the Doctoral Dissertation Defense of Hooman Hamedani.\n\nTitle: Multibreath Hyperpolarized Gas Imaging of Lung Ventilation and Gas Exchange in Humans for Diagnosis and Treatment Response Monitoring\n\nDate: November 11th\, 2022\nTime: 1:00 PM-3:00 PM\n\nLocation: Donner – Grice Auditorium\, 2 Dulles\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-multibreath-hyperpolarized-gas-imaging-of-lung-ventilation-and-gas-exchange-in-humans-for-diagnosis-and-treatment-response-monitoring-hooman-hamedani/
LOCATION:Donner-Grice Auditorium
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
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