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DTSTART:20210314T070000
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DTSTART;TZID=America/New_York:20220207T120000
DTEND;TZID=America/New_York:20220207T130000
DTSTAMP:20260406T072545
CREATED:20220131T131006Z
LAST-MODIFIED:20220131T131006Z
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SUMMARY:PSOC@Penn Seminar: “Geometric packing problems in kidney development and disease" (Louis Prahl)
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-geometric-packing-problems-in-kidney-development-and-disease-louis-prahl/
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:20220208T080000
DTEND;TZID=America/New_York:20220208T170000
DTSTAMP:20260406T072545
CREATED:20220125T190412Z
LAST-MODIFIED:20220125T190412Z
UID:10007039-1644307200-1644339600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learned Query Optimization"
DESCRIPTION:Query optimizers are an important part of modern database management systems\, responsible for transforming the user’s declarative query into an executable plan. Because the space of executable plans is so large\, traditional query optimizers narrow the search space using complex hand-crafted heuristics\, which must be manually tuned on a per-application basis for maximum performance. Both the maintenance of these heuristics and their manual tuning require significant human effort. In this talk\, I will present two new approaches to query optimization that employ machine learning to entirely remove — or at least significantly lessen — the need for such heuristics. These learned approaches outperform traditional heuristics with a small amount of training overhead\, while also automatically adapting to changes in the user’s workload or even hardware. Finally\, this talk will highlight the opportunities for applying similar learning techniques to systems more broadly.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learned-query-optimization/
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:20220208T100000
DTEND;TZID=America/New_York:20220208T113000
DTSTAMP:20260406T072545
CREATED:20220201T164109Z
LAST-MODIFIED:20220201T164109Z
UID:10007061-1644314400-1644319800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Uncovering the Rules of Crumpling with a Data-Driven Approach"
DESCRIPTION:When a sheet of paper is crumpled\, it spontaneously develops a network of creases. Despite the apparent disorder of this process\, statistical properties of crumpled sheets exhibit striking reproducibility. Recent experiments have shown that when a sheet is repeatedly crumpled\, the total crease length grows logarithmically [1]. This talk will offer insight into this surprising result by developing a correspondence between crumpling and fragmentation processes. We show how crumpling can be viewed as fragmenting the sheet into flat facets that are outlined by the creases\, and we use this model to reproduce the characteristic logarithmic scaling of total crease length\, thereby supplying a missing physical basis for the observed phenomenon [2]. \nThis study was made possible by large-scale data analysis of crease networks from crumpling experiments. We will describe recent work to use the same data with machine learning methods to probe the physical rules governing crumpling. We will look at how augmenting experimental data with synthetically generated data can improve predictive power and provide physical insight [3\,4]. \n[1] O. Gottesman et al.\, Commun. Phys. 1\, 70 (2018).\n[2] J. Andrejevic et al.\, Nat. Commun. 12\, 1470 (2021).\n[3] J. Hoffmann et al.\, Sci. Advances 5\, eaau6792 (2019).\n[4] J. Andrejevic and C. H. Rycroft\, arXiv:2112.13268 (2021).
URL:https://seasevents.nmsdev7.com/event/meam-seminar-uncovering-the-rules-of-crumpling-with-a-data-driven-approach/
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:20220209T100000
DTEND;TZID=America/New_York:20220209T120000
DTSTAMP:20260406T072545
CREATED:20220201T203145Z
LAST-MODIFIED:20220201T203145Z
UID:10007062-1644400800-1644408000@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Complex systems engineering: designing advanced functions in dynamical and mechanical systems" (Jason Kim)
DESCRIPTION:The Department of Bioengineering and Dr. Dani Bassett are pleased to announce the Doctoral Dissertation Defense of Jason Kim. \nDate:  February 9\, 2022\nTime: 10:00am\nZoom Link: https://us02web.zoom.us/j/4299926075?pwd=VmJmTkZMdmhFQSt0MVcwUFZ6aCtsQT09\n\nTitle: Complex systems engineering: designing advanced functions in dynamical and mechanical systems.\n\nAbstract: From computation in neural networks to allostery in proteins\, numerous natural and artificial systems are comprised of many interacting parts that give rise to advanced functions. To study such complex systems\, a diverse array of interdisciplinary tools have been developed that relate the interactions and functions of existing systems. However\, engineering the interactions to perform designed functions in novel systems remains a significant challenge due to the nonlinearities in the interactions and the vast dimensionality of the design space. Here we develop design principles for complex dynamical and mechanical systems at the lowest level of their microstate interactions. In dynamical neural systems\, we use methods from control theory and dynamical systems theory to mathematically map precise patterns of neural connectivity to the control of neural states in biological brains\, and to the learning of computations on internal representations in artificial recurrent neural networks. In mechanical systems\, we use methods from algebraic geometry and dynamical systems to mathematically map precise patterns of mechanical constraints to design shape changes as a minimal model of protein allostery and cooperativity\, and to engineer mechanical metamaterials that possess arbitrarily complex shape changes. These intuitive maps allow us to navigate previously unexplored design spaces in nonlinear and high-dimensional regimes\, enabling us to reverse engineer form from function in novel complex systems that have yet to exist.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-complex-systems-engineering-designing-advanced-functions-in-dynamical-and-mechanical-systems-jason-kim/
LOCATION:https://upenn.zoom.us/j/96715197752
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:20220209T120000
DTEND;TZID=America/New_York:20220209T150000
DTSTAMP:20260406T072545
CREATED:20220128T194609Z
LAST-MODIFIED:20220128T194609Z
UID:10007042-1644408000-1644418800@seasevents.nmsdev7.com
SUMMARY:Women in Data Science (WiDS) Philadelphia @ Penn
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/women-in-data-science-wids-philadelphia-penn/
LOCATION:PA
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220209T150000
DTEND;TZID=America/New_York:20220209T160000
DTSTAMP:20260406T072545
CREATED:20220207T185404Z
LAST-MODIFIED:20220207T185404Z
UID:10007072-1644418800-1644422400@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Nikos Kolotouros\, University of Pennsylvania\, “Reconstructing 3D Humans from Images”
DESCRIPTION:The past decade we have seen remarkable progress in Computer Vision\, mainly fueled by the recent advances in Deep Learning. Unsurprisingly\, human perception has been the center of attention. We now have access to systems that can work remarkably well for traditional 2D tasks like segmentation or pose estimation. However\, scaling this to 3D remains particularly challenging because of the inherent ambiguities and the scarcity of annotations. \nIn this talk I will focus on 3 important problems in reconstructing 3D bodies from images and how my research attempts to solve them. First\, I will talk about the limited availability of annotated data and I will propose a method for addressing it. Next\, I will present my work on modeling the ambiguities in 3D human reconstruction and demonstrate its usefulness for solving a variety of downstream tasks. Last\, I will move beyond single-person 3D pose estimation and show how we can scale our methods to work on scenes with multiple humans.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-nikos-kolotouros-university-of-pennsylvania-reconstructing-3d-humans-from-images/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
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:20220209T153000
DTEND;TZID=America/New_York:20220209T163000
DTSTAMP:20260406T072545
CREATED:20220112T001652Z
LAST-MODIFIED:20220112T001652Z
UID:10007008-1644420600-1644424200@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: “Investigating Biomedical Challenges Through State-of-the-Art DNA-based Technology”
DESCRIPTION:Abstract \nDNA can serve purposes beyond conveying hereditary information – its highly specific Watson-Crick base pairing can also be used to direct the assembly of cells\, nanoparticles\, and proteins. Recently developed in the Sohn lab [1]\, high-throughput DNA-directed patterning takes advantage of the versatile and iterative aspects of photolithography to define clearly regions on an aldehyde-functionalized slide to which amine-terminated 20 nucleotide oligonucleotides are conjugated. By tagging antibodies\, liposomes\, or cells with the complementary oligonucleotide\, I can create patterns with high spatial resolution. In this talk\, I will demonstrate the versatility of high-throughput DNA-directed patterning through disparate applications\, including the immobilization of antibodies [2]\, the validation of a liposome model of SARS-CoV-2 [3]\, and an in vitro model of the tumor microenvironment. The advantages afforded by this technique enable me to validate ACE2-binding and antibody neutralization of different variant model liposomes and to study interactions of the multiple types of cells found in the bone marrow. By controlling the organization of cells with single-cell resolution and the ability to configure heterogeneous cellular environments\, DNA-directed patterning presents opportunities in the study of high complexity biomedical challenges.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-investigating-biomedical-challenges-through-state-of-the-art-dna-based-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:20220209T153000
DTEND;TZID=America/New_York:20220209T163000
DTSTAMP:20260406T072545
CREATED:20220131T201411Z
LAST-MODIFIED:20220131T201411Z
UID:10007058-1644420600-1644424200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learning with Feedback from Strategic Stakeholders: Algorithms and Systems"
DESCRIPTION:Machine learning has made great strides in the recent past\, achieving super-human performance in tasks requiring learning from data. However\, intelligent algorithms should go beyond simply learning; they should be able to make decisions to collect data in unknown environments and work towards a desired outcome. Quite often\, we need to rely on feedback from stakeholders for this data\, who themselves have vested interest in the decisions taken by such algorithms. In this talk\, I will argue that effective learning and decision-making in such problems requires that we combine ideas from economics with machine learning.\n\nI will present some of our recent work on learning with feedback from strategic stakeholders in fair division and in auctions. We will strive to design algorithms that are efficient (finds optimal outcomes)\, fair (treats all stakeholders fairly)\, and strategy-proof (cannot be manipulated by selfish stakeholders) when agent preferences and environment characteristics are unknown. On the theoretical side\, I will discuss algorithms\, asymptotic upper bounds on the three criteria\, and complementary hardness results. On the applied side\, I will discuss Cilantro\, a Kubernetes-based system for resource allocation in clusters while obtaining feedback from a job’s performance. We implement our methods on Cilantro and show that they are able to quickly learn efficient resource allocations while being empirically fair and strategy-proof.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learning-with-feedback-from-strategic-stakeholders-algorithms-and-systems/
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:20220210T120000
DTEND;TZID=America/New_York:20220210T150000
DTSTAMP:20260406T072545
CREATED:20220128T201207Z
LAST-MODIFIED:20220128T201207Z
UID:10007043-1644494400-1644505200@seasevents.nmsdev7.com
SUMMARY:Women in Data Science (WiDS) Philadelphia @ Penn
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/women-in-data-science-wids-philadelphia-penn-2/
LOCATION:PA
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220210T153000
DTEND;TZID=America/New_York:20220210T163000
DTSTAMP:20260406T072545
CREATED:20220131T204119Z
LAST-MODIFIED:20220131T204119Z
UID:10007059-1644507000-1644510600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar:"Improving the Privacy\, Scalability\, and Ecological Impact of Blockchains"
DESCRIPTION:Blockchains are an exciting area of research that touches on many areas of Computer Science and beyond.   This technology has the potential to enable a fast\, cheap\, and private financial system based on distributed consensus and cryptography\, instead of trusted parties.  Despite this potential\, the reality still shows severe limitations of blockchains: (i) transactions can cost hundreds of dollar and take minutes to confirm\, (ii) some blockchains offer little privacy\, and (iii) proof-of-work consensus consumes too much energy.  In this talk\, I will discuss powerful techniques that follow a prover paradigm and can mitigate these limitations.  The first technique\, called Bulletproofs\, is a general-purpose zero-knowledge proof system that is specifically designed to enable confidential blockchain transactions. Bulletproofs requires minimal trust assumptions and gives the shortest zero-knowledge proofs without trusted setup. The system is widely deployed and powers tens of thousands of private blockchain transactions per day.   The second technique\, called inner pairing products\, is a way to aggregate many zero knowledge proofs into a single short proof. This can significantly reduce on-chain data\, leading to a significant increase in transactions per second that the chain can process.   The third technique is a new concept called a verifiable delay function (VDF) that is vital for permission-less and eco-friendly consensus. VDFs are already deployed in Filecoin and Chia\, and are planned for Ethereum 2.0\, the upcoming upgrade to Ethereum.
URL:https://seasevents.nmsdev7.com/event/cis-seminarimproving-the-privacy-scalability-and-ecological-impact-of-blockchains/
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:20220211T100000
DTEND;TZID=America/New_York:20220211T180000
DTSTAMP:20260406T072545
CREATED:20211206T213742Z
LAST-MODIFIED:20211206T213742Z
UID:10006990-1644573600-1644602400@seasevents.nmsdev7.com
SUMMARY:ODEI Spotlight: Women+ in STEM at Penn Research Symposium
DESCRIPTION:Women+ in Chemistry is excited to announce the Women+ in STEM at Penn Research Symposium\, which will be held on the International Day of Women in Science\, on February 11th 2022 from 10:00AM-6:00PM. This event is co-sponsored by Penn Graduate Women in Science (PGWISE)\, Graduate Student Engineering Government (GSEG) and Penn INSPIRE.  While the symposium will feature research from members of the community who identify as gender minorities\, the whole event is open to anyone at Penn. \n  \nThis symposium will highlight the amazing science being performed by gender minorities at Penn. If interested in attending\, please fill out this Google form. \n  \nIf you have questions or concerns\, please email us at upennwomeninchemistry@gmail.com.
URL:https://seasevents.nmsdev7.com/event/odei-spotlight-women-in-stem-at-penn-research-symposium/
LOCATION:PA
CATEGORIES:Symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220211T103000
DTEND;TZID=America/New_York:20220211T114500
DTSTAMP:20260406T072545
CREATED:20220203T192846Z
LAST-MODIFIED:20220203T192846Z
UID:10007063-1644575400-1644579900@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Ankur Mehta\, University of California\, Los Angeles\, “Towards $1 Robots”
DESCRIPTION:Robots are pretty great — they can make some hard tasks easy\, some dangerous tasks safe\, or some unthinkable tasks possible. And they’re just plain fun to boot. But how many robots have you interacted with recently? And where do you think that puts you compared to the rest of the world’s people? \nIn contrast to computation\, automating physical interactions continues to be limited in scope and breadth. I’d like to change that. But in particular\, I’d like to do so in a way that’s accessible to everyone\, everywhere. In our lab\, we work to lower barriers to robotics design\, creation\, and operation through material and mechanism design\, computational tools\, and mathematical analysis. We hope that with our efforts\, everyone will be soon able to enjoy the benefits of robotics to work\, to learn\, and to play.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-ankur-mehta-university-of-california-los-angeles-towards-1-robots/
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:20220211T140000
DTEND;TZID=America/New_York:20220211T160000
DTSTAMP:20260406T072545
CREATED:20220208T133536Z
LAST-MODIFIED:20220208T133536Z
UID:10007073-1644588000-1644595200@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "T Cell Recruiting Bispecific Autoantibodies for Personalized Cancer Treatment" (Fabiana Zappala)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Andrew Tsourkas are pleased to announce the Doctoral Dissertation Defense of Fabiana Zappala.\n\n\nTitle: “T Cell Recruiting Bispecific Autoantibodies for Personalized Cancer Treatment”\nDate: Friday February 11\, 2022\nTime: 2:00 PM\nLocation: Glandt Forum\, Singh Center for Nanotechnology\nZoom link: https://upenn.zoom.us/j/95334318432?pwd=YllrU0lvMnhVRUdZTk1iRjNvVEdzUT09\nZoom password: antibody\n\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-t-cell-recruiting-bispecific-autoantibodies-for-personalized-cancer-treatment-fabiana-zappala/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
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