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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T120000
DTEND;TZID=America/New_York:20220314T130000
DTSTAMP:20260406T052129
CREATED:20220207T143502Z
LAST-MODIFIED:20220207T143502Z
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SUMMARY:PSOC@Penn Seminar: Christina Hueschen
DESCRIPTION:Physical Sciences in Oncology Center PSOC@Penn \nSpring 2022 Hybrid-Seminar Series \nTowne 225 / Raisler Lounge @ Noon (EST) \nFor Zoom link \, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-christina-hueschen/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Postdoctoral
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T140000
DTEND;TZID=America/New_York:20220314T160000
DTSTAMP:20260406T052129
CREATED:20220309T192949Z
LAST-MODIFIED:20220309T192949Z
UID:10007115-1647266400-1647273600@seasevents.nmsdev7.com
SUMMARY:CBE PhD Dissertation Defense | "Surface Modification of Solid Oxide Cell Electrodes to Improve the Electrochemical Performance"
DESCRIPTION:Abstract: \n“Solid Oxide Fuel Cells are high temperature\, solid-state\, electrochemical devices that can convert fuels into electricity or produce fuels from excess electricity. Oxygen is reduced at the cathode to oxygen ions which move through the ceramic to the anode. These oxygen ions are used to oxidize fuels at the anode compartment\, producing heat and electrons that will move through an external circuit to produce power.\nAt the cathode the sluggish oxygen reduction kinetics impede the performance of the electrode. A common approach to enhance the cathode performance is infiltration. Often the performance of a cathode is enhanced after the addition of a variety of metal-oxide materials. The common claim is that the infiltrated materials enhance catalytic activity or conductivity. With infiltration however\, it is impossible to control for changes in surface area or conductivity. Atomic Layer Deposition (ALD) was employed to change the surface chemistry of the electrode\, without changing the conductivity\, or surface area of the electrode.\nPerovskite anodes are of interest due to their resistance to many of the issues that plague Ni-cermet (ceramic metal) anode. Their catalytic activity is often lacking\, and as such a variety of methods are employed to enhance this. The most efficient approach is surface modification which allows for increases in activity with minimal metal loadings. ALD was employed to deposit highly disperse oxidation catalysts in order to minimize the metal loadings while maximizing performance. \n\nAt the Ni-cermet anode\, undesirable reactions\, such as carbon fiber formation and Ni oxidation to NiO\, limit the lifetime of the electrode. Surface modification approaches are often employed to protect the Ni surface against these processes. We investigated the use of CeO2 ALD to overcome these challenges. \n\nPerovskites with exclusively 2 + cations (Ba and Sr) in the A-site and Fe in the B-site have recently exhibited great performance as SOFC anodes. The reasoning behind the high catalytic activity of these anodes has not been thoroughly studied. To elucidate the origin of the high activity of these anodes\, the performance and thermodynamics of Ba0.5Sr0.5FeO3 (BSF) anodes was investigated.”
URL:https://seasevents.nmsdev7.com/event/cbe-phd-dissertation-defense-surface-modification-of-solid-oxide-cell-electrodes-to-improve-the-electrochemical-performance/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T153000
DTEND;TZID=America/New_York:20220314T163000
DTSTAMP:20260406T052129
CREATED:20220219T204302Z
LAST-MODIFIED:20220219T204302Z
UID:10007091-1647271800-1647275400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Unleashing the Potential of In-Network Computing"
DESCRIPTION:Recent advances in programmable networking hardware create a new computing paradigm called in-network computing. This new paradigm allows functionality that has been served by commodity servers\, ranging from network middleboxes to components of distributed systems\, to be performed in the network. I argue that to fully unleash its potential\, we need resource elasticity and fault resiliency via higher-level abstractions.\n\nIn this talk\, I demonstrate that in-network computing can be elastic and resilient by designing high-level abstractions and runtime systems that enable us to leverage compute and memory resources available outside of a single type of device — e.g.\, programmable switches — while hiding the complexities of dealing with device heterogeneity. I begin by introducing TEA\, a framework that provides elastic memory by enabling memory-intensive in-switch applications\, such as cloud-scale load balancers\, to leverage DRAM on remote servers via virtual table abstraction. Then I present ExoPlane and RedPlane\, frameworks that support evolving in-network computing workloads and requirements — i.e.\, serving multiple concurrent applications and making them fault-tolerant — via infinite switch resource and one big fault-tolerant switch abstractions. Several systems in the industry are now adopting some of the technologies presented in this talk.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-unleashing-the-potential-of-in-network-computing/
LOCATION:Room 307\, 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:20220315T153000
DTEND;TZID=America/New_York:20220315T163000
DTSTAMP:20260406T052129
CREATED:20220219T205447Z
LAST-MODIFIED:20220219T205447Z
UID:10007092-1647358200-1647361800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Towards Scalable Representation Learning for Visual Recognition"
DESCRIPTION:A powerful biological and cognitive representation is essential for humans’ remarkable visual recognition abilities. Deep learning has achieved unprecedented success in a variety of domains over the last decade. One major driving force is representation learning\, which is concerned with learning efficient\, accurate\, and robust representations from raw data that are useful for a downstream classifier or predictor. \nA modern deep learning system is composed of two core and often intertwined components: 1) neural network architectures and 2) representation learning algorithms. In this talk\, we will present several studies in both directions. On the neural network modeling side\, we will examine modern network design principles and how they affect the scaling behavior of ConvNets and recent Vision Transformers. Additionally\, we will demonstrate how we can acquire a better understanding of neural network connectivity patterns through the lens of random graphs. In terms of representation learning algorithms\, we will discuss our recent efforts to move beyond the traditional supervised learning paradigm and demonstrate how self-supervised visual representation learning\, which does not require human annotated labels\, can outperform its supervised learning counterpart across a variety of visual recognition tasks. The talk will encompass a variety of vision application domains and modalities (e.g. 2D images and 3D scenes). The goal is to show existing connections between the techniques specialized for different input modalities and provide some insights about diverse challenges that each modality presents. Finally\, we will discuss several pressing challenges and opportunities that the “big model era’’ raises for computer vision research.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-towards-scalable-representation-learning-for-visual-recognition/
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:20220316T110000
DTEND;TZID=America/New_York:20220316T120000
DTSTAMP:20260406T052129
CREATED:20220110T152626Z
LAST-MODIFIED:20220110T152626Z
UID:10007002-1647428400-1647432000@seasevents.nmsdev7.com
SUMMARY:CEMB Future Leaders: "Multiscale computational modeling of vascular adaptation and homeostasis"
DESCRIPTION:Launched in May 2021\, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields\, backgrounds\, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages\, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole. \nRegister HERE for access to the Zoom link and visit the CEMB website for more information.
URL:https://seasevents.nmsdev7.com/event/cemb-future-leaders-multiscale-computational-modeling-of-vascular-adaptation-and-homeostasis/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="Center for Engineering MechanoBiology (CEMB)":MAILTO:annjeong@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220316T110000
DTEND;TZID=America/New_York:20220316T120000
DTSTAMP:20260406T052129
CREATED:20220219T213104Z
LAST-MODIFIED:20220219T213104Z
UID:10007093-1647428400-1647432000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Statistical Machine learning for genetics and health: multi-modality\, interpretability\, mechanism"
DESCRIPTION:Genomic and medical data are available at unprecedented scales. This is due\, in part\, to improvements and developments in data collection\, high throughput sequencing\, and imaging technologies. How can we extract lower dimensional representations from these high dimensional data in a way that retains fundamental biological properties across different scales? Three main challenges arise in this context: how to aggregate information across different experimental modalities\, how to enforce that such representations are interpretable\, and how to leverage prior dynamical knowledge to provide new insight into mechanism. I will present my work on developing statistical machine learning models and algorithms to answer this question and address these challenges. First\, I will present a generative model for learning representations that jointly model information from gene expression and tissue morphology in a population setting. Then\, I will describe a method for making multi-modal representations interpretable using a label-aware compressive classification approach for gene panel selection in single cell data. Finally\, I will discuss inference methods for models which encode mechanistic assumptions\, a need that arises naturally in gene regulatory networks\, predator-prey systems\, and electronic health care records. Throughout this work\, recent advances in machine learning and statistics are harnessed to bridge two worlds — the world of real\, messy biological data and that of methodology and computation. This talk describes the importance of domain knowledge and data-centric modeling in motivating new statistical venues and introduces new ideas that touch upon improving experimental design in biomedical contexts.
URL:https://seasevents.nmsdev7.com/event/6397/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220316T150000
DTEND;TZID=America/New_York:20220316T160000
DTSTAMP:20260406T052129
CREATED:20220225T175024Z
LAST-MODIFIED:20220225T175024Z
UID:10007103-1647442800-1647446400@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Shuran Song\, Columbia University\, “The Reasonable Effectiveness of Dynamic Manipulation for Deformable Objects”
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nFrom unfurling a blanket to swinging a rope; high-velocity dynamic actions play a crucial role in how people interact with deformable objects. In this talk\, I will discuss how we can get robots to learn to dynamically manipulate deformable objects\, where we embrace high-velocity dynamics rather than avoid them (e.g.\, exclusively using slow pick and place actions). With robots that can fling\, swing\, or blow with air\, our experiments show that these interactions are surprisingly effective for many classically hard manipulation problems and enable new robot capabilities.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-shuran-song-columbia-university-the-reasonable-effectiveness-of-dynamic-manipulation-for-deformable-objects/
LOCATION:Levine 512
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:20220317T110000
DTEND;TZID=America/New_York:20220317T120000
DTSTAMP:20260406T052129
CREATED:20220311T213813Z
LAST-MODIFIED:20220311T213813Z
UID:10007118-1647514800-1647518400@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Surpassing Fundamental Limits through Time Varying Electromagnetics"
DESCRIPTION:Surpassing the fundamental limits that govern all electromagnetic structures\, such as reciprocity and the delay-bandwidth-size limit\, will have a transformative impact on all applications based on electromagnetic circuits and systems. For instance\, violating principles of reciprocity enables non-reciprocal components such as isolators and circulators\, which find application in full-duplex wireless radios\, radar\, bio-medical imaging\, and quantum computing systems. Overcoming the delay-bandwidth-size limit enables ultra-broadband yet extremely-compact devices whose size is not fundamentally related to the wavelength at the operating frequency. \nThe focus of my talk will be on using time-variance as a new toolbox to overcome these fundamental limits and re-imagine circuit design. Specifically\, I will focus on CMOS-integrated time-varying circuits and systems that have enabled: (i) integrated non-reciprocal components operating across frequencies ranging from RF to millimeter waves with multi-watt power handling\, (ii) reconfigurable microwave passive components with 100-1000× form-factor reduction\, (iii) integrated full-duplex wireless radios with wideband self-interference cancellation\, and (iv) the first non-reciprocal Floquet electromagnetic topological insulator with an ultra-wide bandgap. Our prototypes achieve the stringent performance envelopes that are required by practical wireless applications\, thus bringing the fields of integrated non-reciprocity and synthetic topological insulators to real-world applications. \nI will also briefly cover my future research plans on harmonic-tuned\, higher-order N-path filters and cross-disciplinary collaborative research on using time-varying circuits and CMOS based ICs in cryogenic quantum computing applications.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-surpassing-fundamental-limits-through-time-varying-electromagnetics/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220317T123000
DTEND;TZID=America/New_York:20220317T133000
DTSTAMP:20260406T052129
CREATED:20220311T142141Z
LAST-MODIFIED:20220311T142141Z
UID:10007117-1647520200-1647523800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Forward and Inverse Causal Inference in a Tensor Framework"
DESCRIPTION:Developing causal explanations for correct results or for failures from mathematical equations and data is important in developing a trustworthy artificial intelligence\, and retaining public trust.  Causal explanations are germane to the “right to an explanation” statute\, i.e.\, to data-driven decisions\, such as those that rely on images.  Computer graphics and computer vision problems\, also known as forward and inverse imaging problems\, have been cast as causal inference questions consistent with Donald Rubin’s quantitative definition of causality\, where “A causes B” means “the effect of A is B”\, a measurable and experimentally repeatable quantity. Computer graphics may be viewed as addressing analogous questions to forward causal inference that addresses the “what if” question\, and estimates a change in effects given a delta change in a causal factor. Computer vision may be viewed as addressing analogous questions to inverse causal inference that addresses the “why” question which we define as the estimation of causes given a forward causal model\, and a set of observations that constrain the solution set.  Tensor factor ananlysis also known as structural equations with multimode latent variables is a suitable and transparent framework for modeling the mechanism that generates observed data.  Tensor factor analysis has been employed in representing the causal factor structure of data formation in econometrics\, psychometric\, and chemometrics since the 1960s.  More recently\, tensor factor analysis has been successfully employed to represent cause-and-effect in computer vision\, and computer graphics\, or for prediction and dimensionality reduction in machine learning tasks.   
URL:https://seasevents.nmsdev7.com/event/cis-seminar-forward-and-inverse-causal-inference-in-a-tensor-framework/
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:20220317T153000
DTEND;TZID=America/New_York:20220317T163000
DTSTAMP:20260406T052129
CREATED:20220221T185704Z
LAST-MODIFIED:20220221T185704Z
UID:10007094-1647531000-1647534600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Optimizing CPU Efficiency and Tail Latency in Datacenters"
DESCRIPTION:The slowing of Moore’s Law and increased concerns about the environmental impacts of computing are exerting pressure on datacenter operators to use resources such as CPUs and memory more efficiently. However\, it is difficult to improve efficiency without degrading the performance of applications. \nIn this talk\, I will focus on CPU efficiency and how we can increase efficiency while maintaining low tail latency for applications. The key innovation is to reallocate cores between applications on the same server very quickly\, every few microseconds. First I will describe Shenango\, a system design that makes such frequent core reallocations possible. Then I will show how policy choices for core reallocation and load balancing impact CPU efficiency and tail latency\, and present the policies that yield the best combination of both.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-optimizing-cpu-efficiency-and-tail-latency-in-datacenters/
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:20220318T103000
DTEND;TZID=America/New_York:20220318T114500
DTSTAMP:20260406T052129
CREATED:20220304T180229Z
LAST-MODIFIED:20220304T180229Z
UID:10007112-1647599400-1647603900@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Gregory Hager\, Johns Hopkins University\, “Observing\, Learning and Executing Fine-Grained Manipulation Activities”
DESCRIPTION:This seminar will be held in person in Wu and Chen Auditorium as well as virtually via Zoom. \nIn the domain of image and video analysis\, much of the deep learning revolution has been focused on narrow\, high-level classification tasks that are defined through carefully curated\, retrospective data sets. However\, most real-world applications – particularly those involving complex\, multi-step manipulation activities — occur “in the wild” where there is a combinatorial long tail of unique situations that are never seen during training. These systems demand a richer\, fine-grained task representation that is informed by the application context and which supports quantitative analysis and compositional synthesis. As a result\, the challenges inherent in both high-accuracy\, fine-grained analysis and performance of perception-based activities are manifold\, spanning representation\, recognition\, and task and motion planning. \n  \nThis talk will summarize our work addressing these challenges. I’ll first describe DASZL\, our approach to interpretable\, attribute-based activity detection. DASZL operates in both pre-trained and zero shot settings\, and it has been applied to a variety of applications ranging from surveillance to surgery. I will then describe our recent work on “Good Robot”\, a method for end-to-end training of a robot manipulation system. Good Robot achieves state-of-the-art performance in complex\, multi-step manipulation tasks\, and we show it can be refactored to support both demonstration-driven and language-guided manipulation. I’ll close with a summary of some directions related to these technologies that we are currently exploring.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-gregory-hager-johns-hopkins-university-observing-learning-and-executing-fine-grained-manipulation-activities/
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:20220318T140000
DTEND;TZID=America/New_York:20220318T150000
DTSTAMP:20260406T052129
CREATED:20220214T192105Z
LAST-MODIFIED:20220214T192105Z
UID:10007086-1647612000-1647615600@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Computational Image Analysis For Individualized Surgical Treatment Planning of Bicuspid Aortic Valves"
DESCRIPTION:Abstract: \nThe bicuspid aortic valve (BAV) is a congenital heart defect in which the aortic valve has two cusps rather than three. Moderate to severe aortic regurgitation is the most common complication in young adult BAV patients and requires major\, and often repeated\, surgical intervention. BAV repair is an evolving surgical treatment for aortic regurgitation that preserves native valve tissue and circumvents risks and quality of life concerns associated with conventional aortic valve replacement in young adults. Despite promising clinical studies\, however\, BAV repair remains underutilized and there is substantial variability in surgical planning across institutions. In this talk\, we discuss 3D and 4D computational image analysis methodologies that we are developing to gain new insights into valvular regurgitation and surgical treatment of the disease. These methodologies enable pre-operative visualization of valve morphology and motion\, as well as automated quantification of metrics that are used to decide which surgical strategy is optimal for a patient’s valve. We will discuss how the advancement of image analysis\, applied to modalities such as echocardiography and computed tomography\, provides unique opportunities to standardize the surgical planning process and increase the utilization of repair as an alternative to valve replacement in young adults. \n 
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-computational-image-analysis-for-individualized-surgical-treatment-planning-of-bicuspid-aortic-valves/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
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