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DTSTART;TZID=America/New_York:20201026T120000
DTEND;TZID=America/New_York:20201026T130000
DTSTAMP:20260407T111440
CREATED:20200908T170416Z
LAST-MODIFIED:20200908T170416Z
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SUMMARY:PSOC Webinar: Joel Bader
DESCRIPTION:Talk title TBC \nPhysical Sciences in Oncology Center PSOC@Penn \nFall 2020 Webinar Series Mondays @ Noon (EST) \nFor webinar links\, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psoc-webinar-joel-bader/
LOCATION:PA
CATEGORIES:Seminar
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201027T103000
DTEND;TZID=America/New_York:20201027T120000
DTSTAMP:20260407T111440
CREATED:20200901T151706Z
LAST-MODIFIED:20200901T151706Z
UID:10006467-1603794600-1603800000@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Data-driven Physics Discovery and Scale Bridging in Materials"
DESCRIPTION:In this talk I will provide an overview of our recent work in data-driven methods—mainly machine learning—to enhance computational materials physics models. This body of work has proceeded along two main fronts. The first is system inference\, where we seek to identify physical mechanisms via their mathematical signatures as differential or algebraic operators. Our approach of Variational System Identification leverages the weak form of partial differential equations to identify the physics underlying pattern formation\, and the deformation mechanisms of soft materials. The framework of Variational System Identification has to address several challenges specific to experimental characterization of materials\, such as data that is noisy\, sparse\, originates from different specimens\, and spans dynamics to steady state regimes. The second front is in scale bridging\, which we approach in the context of determining free energy functions. We have developed Integrable Deep Neural Networks\, and active learning algorithms to combine data generated by Density Functional Theory calculations with cluster expansions and Monte Carlo computations to obtain free energy density functions. These are used in mechano-chemically coupled continuum methods to predict the evolution of microstructure in alloys.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-data-driven-physics-discovery-and-scale-bridging-in-materials/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201027T130000
DTEND;TZID=America/New_York:20201027T140000
DTSTAMP:20260407T111440
CREATED:20201022T192142Z
LAST-MODIFIED:20201022T192142Z
UID:10006530-1603803600-1603807200@seasevents.nmsdev7.com
SUMMARY:ESE Seminar: "High-Frequency Power Conversion with Wide-Bandgap Semiconductors"
DESCRIPTION:With the commercialization of wide-bandgap power semiconductors\, multi-MHz switching frequencies are more compelling and critical to meet new applications demanding leaps in power density and efficiency. In the past\, studies of these converters reported significant gaps between measured and modeled performance\, often attributed to dynamic RDS\,ON in GaN HEMTs. In particular\, the power semiconductors – which often drive thermal constraints – dissipated much more power than expected\, rendering designs based on simulated values unusable. In soft-switched converters\, which dominate at MHz frequencies\, the semiconductor’s output capacitor is resonantly charged and discharged once per switching cycle. Recently\, multiple papers have found significant losses from this process in silicon and wide-bandgap devices\, explaining the unexpected power dissipation. With these losses known\, the MHz-frequency design space can be reopened – if designers are careful about semiconductor selection. In this talk\, I will discuss how to select the right device across material (GaN\, SiC\, or Si)\, device technology (superjunction or trench)\, size (lower RDS\,ON is not always better)\, and\, in some cases\, manufacturer. Further\, I will show how this selection drives thermal design\, input voltage selection\, and novel circuit topologies in a variety of high-performance demonstrations from 6.78 MHz all the way to 40.68 MHz.
URL:https://seasevents.nmsdev7.com/event/ese-seminar-high-frequency-power-conversion-with-widebandgap-semiconductors/
LOCATION:Zoom – Email ESE for Link jbatter@seas.upenn.edu
CATEGORIES:Seminar,Faculty,Colloquium,Student
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201027T150000
DTEND;TZID=America/New_York:20201027T160000
DTSTAMP:20260407T111440
CREATED:20201022T173327Z
LAST-MODIFIED:20201022T173327Z
UID:10006529-1603810800-1603814400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Advances in Machine Learning Systems Research"
DESCRIPTION:A long-standing grand challenge in computing is to enable machines to act autonomously and intelligently: to rapidly and repeatedly take appropriate actions based on information in the world around them. Driven by trends in the data economy\, rapid progress in AI\, and an increasingly programmable physical world we are at an inflection point that demands a new class of AI system. This new class of systems goes beyond training models at scale\, to connecting models with the world\, rendering predictions in real-time under heavy query load\, adapting to new observations and contexts. These systems will need to be composable and elastically scalable to accommodate new technologies and variations in workloads. Operating in the physical world\, observing intimate details of our lives\, and making critical decisions\, these systems must also be secure. \nIn this talk\, I will present work in my group exploring advances in systems for prediction serving\, autonomous driving\, and how model design and system design interact.  In particular\, I will discuss some of the key trade-offs between time\, accuracy\,  convergence\, throughput\, and security that govern how we design systems\, train models\, and make predictions that meet the demands of real-world applications.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-advances-in-machine-learning-systems-research/
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:20201028T150000
DTEND;TZID=America/New_York:20201028T160000
DTSTAMP:20260407T111440
CREATED:20200921T205522Z
LAST-MODIFIED:20200921T205522Z
UID:10006508-1603897200-1603900800@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Antibiotic Discovery by Means of Computers"
DESCRIPTION:Abstract \nUntil now\, the natural world has supplied us with antibiotics. Bacteria\, however\, are increasingly resistant to these drugs. The next generation of antibiotics will likely come not from nature but from computer-based discovery. Computer-driven approaches have the potential to outperform humans\, as demonstrated for pattern recognition of images and text. In order for machines to discover novel drugs and optimize antimicrobial properties\, they have to be able to understand\, read and write molecules. In this talk\, I will describe our efforts in developing computational approaches for antibiotic discovery. I will discuss how we trained a computer to execute a fitness function following Darwin’s algorithm of evolution to select for structures that interact with bacterial membranes\, yielding the first artificial antimicrobials that kill bacteria both in vitro and in animal models. My lab has also developed pattern recognition algorithms to mine the human proteome\, identifying throughout the body thousands of antibiotics encoded in proteins with unrelated biological function. Computer-made drugs may help to replenish our arsenal of effective drugs.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-antibiotic-discovery-by-means-of-computers/
LOCATION:Zoom – Email CBE for link
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201029T090000
DTEND;TZID=America/New_York:20201029T100000
DTSTAMP:20260407T111440
CREATED:20201006T144323Z
LAST-MODIFIED:20201006T144323Z
UID:10006520-1603962000-1603965600@seasevents.nmsdev7.com
SUMMARY:Doctoral Dissertation: "Computational Investigations of Neuronal Network Responses to Traumatic Brain Injury"
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. David Meaney are pleased to announce the Doctoral Dissertation Defense of Samantha Schumm. The public is welcome to attend the Zoom meeting via the details below.\n\nTitle: Computational Investigations of Neuronal Network Responses to Traumatic Brain Injury\nDate: Thursday\, October 29th\, 2020\nTime: 9:00am EST\n\n\nJoin Zoom Meeting https://upenn.zoom.us/j/94009572364\nMeeting ID: 940 0957 2364
URL:https://seasevents.nmsdev7.com/event/doctoral-dissertation-computational-investigations-of-neuronal-network-responses-to-traumatic-brain-injury/
LOCATION:PA
CATEGORIES:Doctoral,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201030T110000
DTEND;TZID=America/New_York:20201030T170000
DTSTAMP:20260407T111440
CREATED:20201001T185935Z
LAST-MODIFIED:20201001T185935Z
UID:10006517-1604055600-1604077200@seasevents.nmsdev7.com
SUMMARY:2020 CBE Graduate Student Symposium
DESCRIPTION:The Graduate Student Symposium will be held on October 30th\, 11:00AM-5:00PM EDT. We are excited to share the research conducted in our department with each other and invited industrial representatives\, with 14 oral talks and 36 poster presentations from soft matter\, biological and biomedical engineering\, energy\, and catalysis. Information on the program and abstracts can be found on the GSS website. \nGiven the virtual format\, we are requiring students and faculty to register prior to the event. This ensures that you receive the Zoom links for talks as well as have access to the poster presentations and happy hour. Please register for the symposium by October 15th so that we have an accurate head count for planning purposes. We welcome any faculty or research groups within Penn to attend the symposium if it aligns with their research and professional interests. \nAs always\, any questions can be directed to cbegss@seas.upenn.edu. We look forward to seeing everyone there! \nGSS Co-Chairs\nKatie\, Ali\, Adam\, Tianyi
URL:https://seasevents.nmsdev7.com/event/2020-cbe-graduate-student-symposium/
LOCATION:Zoom
CATEGORIES:Symposium
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201030T140000
DTEND;TZID=America/New_York:20201030T150000
DTSTAMP:20260407T111440
CREATED:20200902T125320Z
LAST-MODIFIED:20200902T125320Z
UID:10006470-1604066400-1604070000@seasevents.nmsdev7.com
SUMMARY:PICS Seminar: "Shock-induced turbulent mixing and interactions with flexible panels through simulations"
DESCRIPTION:Two fundamental challenges that arise in the development of air-breathing supersonic combustion ramjet engines (scramjets) for hypersonic flight are: 1) the rapid mixing of fuel and oxidizer that must occur prior to combustion\, and 2) the coupling between the engine structure and the flow dynamics. Interactions of shock waves and turbulence that characterize the flow inside scramjets play a key role in both mixing enhancement and aerostructural coupling. We present ongoing efforts on the high-fidelity numerical simulation of these two phenomena. \nScalar mixing under canonical shock-turbulence interactions will be addressed first by means of Direct Numerical Simulation\, evaluating the effects of variations in the relevant physical parameters: shock and turbulence Mach numbers\, Reynolds number\, and Schmidt numbers. The analysis will highlight changes along the shock-normal direction of scalar variance and dissipation-rate budgets\, flow topology\, and alignments of the scalar gradient with vorticity and strain-rate eigendirections. \nThen\, we will focus on interactions of shock waves reflecting off turbulent boundary layers that develop along the walls of the scramjet. Rigid and flexible walls will be considered\, by coupling a wall-modeled large-eddy simulation solver for the fluid flow with an elastic solid structural solver that accounts for geometric nonlinearities. We will emphasize strong shock/boundary-layer interactions resulting in mean flow separation and low-frequency unsteadiness that can interact with natural frequencies of the structure.
URL:https://seasevents.nmsdev7.com/event/pics-seminar-shock-induced-turbulent-mixing-and-interactions-with-flexible-panels-through-simulations/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
CATEGORIES:Seminar
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
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