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DTSTART;TZID=America/New_York:20220210T120000
DTEND;TZID=America/New_York:20220210T150000
DTSTAMP:20260406T185435
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SUMMARY:Women in Data Science (WiDS) Philadelphia @ Penn
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/women-in-data-science-wids-philadelphia-penn-2/
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220210T153000
DTEND;TZID=America/New_York:20220210T163000
DTSTAMP:20260406T185435
CREATED:20220131T204119Z
LAST-MODIFIED:20220131T204119Z
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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:20260406T185435
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/
CATEGORIES:Symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220211T103000
DTEND;TZID=America/New_York:20220211T114500
DTSTAMP:20260406T185435
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:20260406T185435
CREATED:20220208T133536Z
LAST-MODIFIED:20220208T133536Z
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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
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220214T120000
DTEND;TZID=America/New_York:20220214T130000
DTSTAMP:20260406T185435
CREATED:20220207T143038Z
LAST-MODIFIED:20220207T143038Z
UID:10007066-1644840000-1644843600@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: “Dynamics of early stages of cell adhesion on fluid substrates” (Oleg Mikhajlov)
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-dynamics-of-early-stages-of-cell-adhesion-on-fluid-substrates-oleg-mikhajlov/
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:20220215T100000
DTEND;TZID=America/New_York:20220215T113000
DTSTAMP:20260406T185435
CREATED:20220204T152708Z
LAST-MODIFIED:20220204T152708Z
UID:10007064-1644919200-1644924600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "The Unsteady Aerodynamics of Wind Power Generation"
DESCRIPTION:Wind energy plays a crucial role in clean energy generation. Currently\, horizontal axis wind turbines dominate the wind energy sector. Nevertheless\, vertical axis wind turbines (VAWTs) have some advantages over traditional horizontal axis wind turbines. However\, their performance is difficult to predict and they are prone to failure over time. This is because the axis of rotation of a VAWT is perpendicular to the wind direction\, which causes the individual blades to experience rapidly fluctuating airflows\, even when the wind direction is constant. These fluctuations can lead to unsteady flow phenomena that are not well understood. In this talk\, I will present new insights into the aerodynamics of VAWTs by elucidating the unsteady airflow over an individual turbine blade. I will discuss a flow phenomenon known as dynamic stall and its impact on VAWT performance. Because wind turbines are too large to study in a laboratory\, most experimental wind turbine research is conducted on scaled-down models\, but this typically changes the physics involved. The research I will present was conducted in a pressurized wind tunnel which allows for physically accurate downscaling of large-scale flows. The insights from this research can be used to design VAWTs with better durability and performance.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-the-unsteady-aerodynamics-of-wind-power-generation/
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:20220215T110000
DTEND;TZID=America/New_York:20220215T120000
DTSTAMP:20260406T185435
CREATED:20220208T153914Z
LAST-MODIFIED:20220208T153914Z
UID:10007074-1644922800-1644926400@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Autonomous Microsystems Based on Heterogeneously Integrated CMOS for Biological Big Data"
DESCRIPTION:Minimally invasive and chronic physiological monitoring can provide an effective means of disease prevention and early detection while the cumulative big data can unveil hidden patterns in our physiology. Yet\, current physiological monitoring tools are often bulky\, invasive\, and expensive\, limiting their sensitivity and applicability. In this talk\, I will discuss autonomous microsystems based on heterogeneously integrated CMOS\, a platform on which ideal physiological sensors and actuators can be built. \nA micro-scale optoelectronically transduced electrode (MOTE)\, an exemplary microsystem I have designed and built for tetherless neural recording\, is powered and communicates optically through a vertically integrated AlGaAs micro-scale light emitting diode (µLED)\, eliminating the needs for a battery or a RF coil; the MOTE is smaller than a human hair (~60 µm × 30 µm × 330 µm) and weighs about one 1 µg (cf. a grain of sand is about 670 µg). I will review the unique challenges and considerations in developing such heterogeneous systems in terms of device fabrication\, circuit design\, integration\, and handling/manipulation. \nWhile the MOTE is designed for neural recording\, its design methodologies can also be used to monitor other physiological parameters such as temperature\, pH\, glucose-level\, etc. I will introduce future autonomous microsystems with expanded modalities and how to interface them with existing wearables. As such microsystems become more accessible\, the resulting biological big data will help enable personalized healthcare and produce a physiological ‘digital twin’ (like the architectural digital twins of select cities) that can add a new dimension to epidemiological and aging studies.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-autonomous-microsystems-based-on-heterogeneously-integrated-cmos-for-biological-big-data/
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:20220215T153000
DTEND;TZID=America/New_York:20220215T163000
DTSTAMP:20260406T185435
CREATED:20220119T202143Z
LAST-MODIFIED:20220119T202143Z
UID:10007028-1644939000-1644942600@seasevents.nmsdev7.com
SUMMARY:Joseph Bordogna Forum: "Engineering for Everyone: Centering Diversity\, Equity\, and Inclusion"
DESCRIPTION:Please join us for this distinguished lecture given by Dr. Gilda Barabino\, President of Olin College of Engineering. \n“Engineering for Everyone: Centering Diversity\, Equity\, and Inclusion” \nAt its core\, engineering involves creative problem solving. Diverse groups of problem solvers are more likely to outperform homogeneous groups and derive the best solution. Yet\, ensuring diverse groups in engineering is compromised by the persistent underrepresentation of members of racially minoritized groups and women\, and the lack of equitable and inclusive environments to ensure their success.  Centering diversity\, equity\, and inclusion in the context of engineering for everyone has the capacity to effect meaningful change within our institutions and across higher education. This presentation will challenge assumptions\, provide frameworks\, apply inclusion lessons\, and offer strategies for the future. \nThis event will be held in a hybrid format in the Wu and Chen Auditorium in Levine Hall (3330 Walnut Street). \nDr. Barabino’s talk was recorded and is available for viewing here. \n \nDr. Gilda A. Barabino is President of Olin College of Engineering and Professor of Biomedical and Chemical Engineering. She previously served as Daniel and Frances Berg Professor and Dean at The City College of New York’s (CCNY) Grove School of Engineering. Prior to joining CCNY\, she was Associate Chair for Graduate Studies and Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory. At Georgia Tech she also served as the inaugural Vice Provost for Academic Diversity. She is a noted investigator in the areas of sickle cell disease\, cellular and tissue engineering\, and the role of race/ethnicity and gender in science and engineering. Her many honors include an honorary degree from Xavier University of Louisiana and the Presidential Award for Excellence in Science\, Mathematics\, and Engineering Mentoring. Dr. Barabino is president-elect of the American Association for the Advancement of Science (AAAS)\, the world’s largest interdisciplinary scientific society. She is a Fellow of AAAS\, the American Institute of Chemical Engineers\, the American Institute for Medical and Biological Engineering and the Biomedical Engineering Society. She is an elected member of the National Academy of Engineering\, the National Academy of Medicine and the American Academy of Arts and Sciences.  She chairs the National Academies Committee on Women in Science\, Engineering and Medicine and serves on numerous committees of the National Academies including the Roundtable on Black Men and Black Women in Science\, Engineering and Medicine and the Health and Medicine Division Committee. She is also a member of the congressionally mandated Committee on Equal Opportunities in Science and Engineering. Dr. Barabino consults nationally and internationally on STEM education and research; diversity\, equity\, and inclusion in higher education; policy; faculty development; and workforce development. She received her B.S. degree in Chemistry from Xavier University of Louisiana and her PhD in Chemical Engineering from Rice University.
URL:https://seasevents.nmsdev7.com/event/joseph-bordogna-forum-with-dr-gilda-barabino/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Distinguished Lecture
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220215T153000
DTEND;TZID=America/New_York:20220215T163000
DTSTAMP:20260406T185435
CREATED:20220126T230231Z
LAST-MODIFIED:20220126T230231Z
UID:10007041-1644939000-1644942600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Foundations of Cryptographic Proof Systems"
DESCRIPTION:One of computer science’s greatest insights has been in understanding the power and versatility of *proofs*\, which were revolutionized in the 1980s to utilize *interaction* as well as other resources such as randomization and computational hardness. Today\, they form the backbone of both theoretical and practical cryptography and are simultaneously the source of deep connections to areas such as complexity theory\, game theory\, and quantum computation. \nIn this talk\, I will introduce general-purpose tools\, techniques\, and abstractions for two key aspects of cryptographic proof systems that have been poorly understood for decades: \n1) Can we remove interaction from interactive proofs? Already in the 1980s\, Fiat and Shamir proposed a heuristic *but unproven* methodology for removing interaction from interactive proofs\, which is now ubiquitous and essential for practical applications. However\, it remained open for over 30 years to prove the security of this transformation in essentially any setting of interest. \nMy work on the Fiat-Shamir transform has led to resolutions to many long-standing open problems\, including (i) building non-interactive zero knowledge proof systems based on lattice cryptography\, (ii) establishing the existence of highly efficient and succinct non-interactive proof systems\, and (iii) demonstrating that foundational protocols from the 80s fail to compose in parallel. \n2) Are classical interactive protocols secure against quantum computers? At its heart\, the problem of analyzing and ruling out quantum attacks on cryptographic protocols is the issue of “rewinding.” The inability to rewind a quantum attack stems from the no-cloning theorem\, a fundamental property of quantum information. As a result\, very few classical protocols were known to be secure against quantum attacks. \nIn a recent work\, I showed how to overcome these difficulties and settle many foundational questions on post-quantum cryptographic proof systems. Our main technique is showing how to efficiently extract certain pieces of (classical) information from a quantum attacker without disturbing its internal state.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-foundations-of-cryptographic-proof-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:20220216T110000
DTEND;TZID=America/New_York:20220216T120000
DTSTAMP:20260406T185435
CREATED:20220110T153308Z
LAST-MODIFIED:20220110T153308Z
UID:10007005-1645009200-1645012800@seasevents.nmsdev7.com
SUMMARY:CEMB Future Leaders: Richard Vincent
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-richard-vincent/
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:20220216T150000
DTEND;TZID=America/New_York:20220216T160000
DTSTAMP:20260406T185435
CREATED:20220210T193336Z
LAST-MODIFIED:20220210T193336Z
UID:10007077-1645023600-1645027200@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Johannes Betz\, University of Pennsylvania\, “Autonomous Handling at the Limits – Winning the Indy Autonomous Challenge”
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nThe rising popularity of self-driving cars has led to the creation of an additional research and development branch in the recent years: Autonomous racing. Researchers are developing algorithms and hardware for high performance race vehicles which aim to operate autonomously on the edge of the vehicles limits: High speeds\, high accelerations\, high computation power\, low reaction time\, adversarial environments. In addition\, with an increasing number of competitions in the field of autonomous racing\, researchers have the platforms to test their high performance algorithms. This talk will give an overview of the current efforts in the field\, the main research outcomes and the open challenges we can solve with the help of autonomous Racing. Especially we will focus on the Indy Autonomous Challenge and the the software setup of the TUM Autonomous Motorsports Team – the winning team of the Indy Autonomous Challenge. A detailed look into the software will show how each software module is connected and how we can achieve high speed autonomous driving on the racetrack.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-johannes-betz-university-of-pennsylvania-autonomous-handling-at-the-limits-winning-the-indy-autonomous-challenge/
LOCATION:Levine 512
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:20220216T153000
DTEND;TZID=America/New_York:20220216T163000
DTSTAMP:20260406T185435
CREATED:20220113T024323Z
LAST-MODIFIED:20220113T024323Z
UID:10007009-1645025400-1645029000@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: “BEYOND SURFACE” Facilitates Electrocatalytic Reactions of Renewable Carbons
DESCRIPTION:Abstract \nThere has been growing interest to drive chemical reactions via the direct use of renewable electricity to address sustainability challenges. The success of the approach rests on the use of the right materials to efficiently catalyze electrochemical reactions. Thus\, there have been intense efforts to engineer catalyst materials whose surface contains the desired active sites. Despite the success\, there is still much room for improvement in the field of electrocatalysis. However\, it is not because of our limited advances in the synthesis of materials and their use as catalysts. It is because of how we typically view catalytic reactions at the solid-liquid interface that often lacks consideration of the liquid phase (e.g.\, solvent molecules\, double-layer ions). The “BEYOND SURFACE” approach that not only recognizes the presence and role of liquid phase components\, but alters their characteristics to facilitate chemical reactions will bring the necessary advances to progress beyond the performance levels achieved to date. In this talk\, two examples of the “BEYOND SURFACE” approach are presented for electrocatalytic reactions of renewable carbons\, CO2 and biomass. \nThe first example concerns the discovery of a unique interfacial configuration on the surface of colloidal nanoparticles\, that is the Nanoparticle/Ordered-Ligand Interlayer (NOLI). Its operation as a catalytic pocket for CO2 reduction by the synergistic act of the nanoparticle surface and surface ligands hovering above suggests a new route to promote reactions by tuning the electric double layer using materials. The other example presents the need for a better understanding of solvent molecule behavior at electrochemically active interfaces. During electrooxidation of biomass-derived polyols\, it is shown that the interaction between the Pt surface and surrounding water eventually leads to its surface oxidation limiting catalytic activity at fixed potential conditions. Thus\, a unique method so-called electrochemical potential cycling is devised that continuously cycles between oxidative and reductive potentials exploiting the short-lived high activity state of Pt nanoparticles otherwise difficult to maintain under typical conditions. These studies highlight the complexity of electrochemical interfaces and the potential of thinking beyond the surface for electrocatalytic reactions.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-beyond-surface-facilitates-electrocatalytic-reactions-of-renewable-carbons/
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:20220216T153000
DTEND;TZID=America/New_York:20220216T163000
DTSTAMP:20260406T185435
CREATED:20220208T212321Z
LAST-MODIFIED:20220208T212321Z
UID:10007076-1645025400-1645029000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Principled Algorithm Design in the Era of Deep Learning"
DESCRIPTION:Deep learning has seen tremendous growth in the last decade with applications across almost all fields of science and technology. In the pursuit of making deep learning methods more efficient and adaptable\, there is an increasing need to design better algorithms and architectures. In this talk\, I will give an overview of my research efforts towards advancing the statistical and computational foundations of deep learning with the goal of designing new principled algorithms and models. I will show how techniques originally developed for classical learning theory and convex optimization can be combined and extended for the era of deep learning. I will highlight this through two main contributions: \n(1) New algorithms for training basic deep learning architectures that are simple\, computationally efficient\, and provably succeed even when the standard pipelines fail\,\n(2) A statistical characterization of state-of-the-art attention architectures\, like Transformers\, that gives new insights on their ability to capture long-range dependencies.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-principled-algorithm-design-in-the-era-of-deep-learning/
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:20220217T100000
DTEND;TZID=America/New_York:20220217T113000
DTSTAMP:20260406T185435
CREATED:20220204T174149Z
LAST-MODIFIED:20220204T174149Z
UID:10007065-1645092000-1645097400@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Robot-assisted Imaging of Neuromuscular Function: New Insights on the Neural Substrates of Motor Control"
DESCRIPTION:Can we use robots to help humans learn a new motor skill\, or to improve performance of a motor task? What are the neural substrates that support motor learning under physical interaction with external agents such as robots? How does repeated exposure to motor training induce plasticity in brain networks? These are fundamental neuroscience questions which have special relevance in multiple domains\, such as neuromodulation\, surgical training\, and motor recovery after stroke\, spinal cord injury\, or traumatic brain injury. In this talk\, I present methods that address these questions\, combining MRI-compatible robotics with functional neuroimaging and advanced biosignal processing. I demonstrate two applications of these methods to understand the function of multiple brain areas associated with motor control and motor learning. \nOver the past few years\, my lab has developed a family of MRI-compatible robots for use with functional Magnetic Resonance Imaging to study the neural control of movements. In this talk\, I present two systems\, the MR-SoftWrist\, a wrist exoskeleton capable of force feedback designed to study neural substrates involved in the control of wrist movements during externally imposed forces\, and the MR-StretchWrist\, a wrist robot designed to elicit stretch reflexes and study their neural correlates using fMRI. These MRI-compatible robots quantify function in the cortico-thalamic-cerebellar pathway involved in learning new motor tasks and quantify function in secondary motor pathways such as the reticulospinal tract involved in fast feedback responses. I detail how MRI-compatible robots and fMRI were combined to measure neural function associated with long-latency responses and to map the somatotopic organization of these responses of flexor and extensor muscles in the brainstem. Together\, these tools demonstrate how robotics\, functional imaging and neuroscience can be joined across disciplines to understand and perhaps eventually guide both normal function and the nervous system’s response to injury\, disease\, devices and rehabilitation.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-robot-assisted-imaging-of-neuromuscular-function-new-insights-on-the-neural-substrates-of-motor-control/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 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:20220217T110000
DTEND;TZID=America/New_York:20220217T120000
DTSTAMP:20260406T185435
CREATED:20220207T154154Z
LAST-MODIFIED:20220207T154154Z
UID:10007071-1645095600-1645099200@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Certifiable Outlier-Robust Geometric Perception: Robots that See through the Clutter with Confidence"
DESCRIPTION:Geometric perception is the task of estimating geometric models (e.g.\, object pose and 3D structure) from sensor measurements and priors (e.g.\, point clouds and neural network detections). Geometric perception is a fundamental building block for robotics applications ranging from intelligent transportation to space autonomy. The ubiquitous existence of outliers —measurements that tell no or little information about the models to be estimated— makes it theoretically intractable to perform estimation with guaranteed optimality. Despite this theoretical intractability\, safety-critical robotics applications still demand trustworthiness and performance guarantees on perception algorithms. In this talk\, I present certifiable outlier-robust geometric perception\, a new paradigm to design tractable algorithms that enjoy rigorous performance guarantees\, i.e.\, they return an optimal estimate with a certificate of optimality for a majority of problem instances\, but declare failure and provide a measure of suboptimality for worst-case instances. Particularly\, I present two general-purpose algorithms in the certifiable perception toolbox: (i) an estimator that uses graph theory to prune gross outliers and leverages graduated non-convexity to compute the optimal model estimate with high probability of success\, and (ii) a certifier that employs sparse semidefinite programming (SDP) relaxation and a novel SDP solver to endow the estimator with an optimality certificate or escape local minima otherwise. The estimator is fast and robust against up to 99% random outliers in practical perception applications\, and the certifier can compute high-accuracy optimality certificates for large-scale problems beyond the reach of existing SDP solvers. I showcase certifiable outlier-robust perception on robotics applications such as scan matching\, satellite pose estimation\, and vehicle pose and shape estimation. I conclude by remarking three opportunities arising from certifiable perception: to speedup online global optimization by offline learning from data; to enable safe learning-based perception by bridging certifiable estimation with deep representation learning; and to couple and unify perception with action towards trustworthy autonomy.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-certifiable-outlier-robust-geometric-perception-robots-that-see-through-the-clutter-with-confidence/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220217T153000
DTEND;TZID=America/New_York:20220217T163000
DTSTAMP:20260406T185435
CREATED:20220131T145540Z
LAST-MODIFIED:20220131T145540Z
UID:10007053-1645111800-1645115400@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "End-to-End Precision Medicine: Personalized Sensing\, Targeted Diagnostics\, and Therapeutic Discovery" (Ava Soleimany)
DESCRIPTION:This seminar will be held live and broadcast on zoom – check email for zoom link or contact ksas@seas.upenn.edu. \nPrecision medicine envisions a world where diagnostic and therapeutic opportunities are intelligently tailored to individual patient needs. Achieving this vision necessitates access to high quality\, accurate\, and individualized information about disease state. Engineered probes that sense disease activity — dynamically and directly within the body — could provide this information by generating signals that functionally measure the state of one’s disease. \nIn this talk\, I will discuss my work in engineering a novel class of nanoscale sensors that directly query disease microenvironments by measuring the activity of proteases\, enzymes directly involved in many diseases including cancer. I will share how we can leverage the rich\, functional data generated by these sensors to design and deploy novel\, expressive\, and high-fidelity machine learning models to power individualized diagnostic decision-making. Finally\, I show how we can close the precision medicine loop to advance new treatment strategies\, through the design of a novel algorithm for guided and robust therapeutic discovery. Together\, this talk will present a new paradigm for creating translational engineering and algorithmic advances across all stages of personalized disease management: from functional understanding of biological mechanisms\, to early disease interception\, to intelligent data-driven treatment design.
URL:https://seasevents.nmsdev7.com/event/be-seminar-ava-soleimany/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220217T153000
DTEND;TZID=America/New_York:20220217T163000
DTSTAMP:20260406T185435
CREATED:20220131T210915Z
LAST-MODIFIED:20220131T210915Z
UID:10007060-1645111800-1645115400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learning-Based Program Synthesis: Learning for Program Synthesis and Program Synthesis for Learning"
DESCRIPTION:With the advancement of modern technologies\, programming becomes ubiquitous not only among professional software developers\, but also for general computer users. However\, gaining programming expertise is time-consuming and challenging. Therefore\, program synthesis has many applications\, where the computer automatically synthesizes programs from specifications such as natural language descriptions and input-output examples. In this talk\, I will present my work on learning-based program synthesis\, where I have developed deep learning techniques for various program synthesis problems. Despite the remarkable success of deep neural networks for many domains\, including natural language processing and computer vision\, existing deep neural networks are still insufficient for handling challenging symbolic reasoning and generalization problems. \nMy learning-based program synthesis research lies in two folds: (1) learning to synthesize programs from potentially ambiguous and complex specifications; and (2) neural-symbolic learning for language understanding. I will first talk about program synthesis applications\, where my work demonstrates the applicability of learning-based program synthesizers for production usage. I will then present my work on neural-symbolic frameworks that integrate symbolic components into neural networks\, which achieve better reasoning and generalization capabilities. In closing\, I will discuss the challenges and opportunities of further improving the complexity and generalizability of learning-based program synthesis for future work.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learning-based-program-synthesis-learning-for-program-synthesis-and-program-synthesis-for-learning/
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:20220218T103000
DTEND;TZID=America/New_York:20220218T114500
DTSTAMP:20260406T185435
CREATED:20220124T151125Z
LAST-MODIFIED:20220124T151125Z
UID:10007034-1645180200-1645184700@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Volkan Isler\, University of Minnesota\, “From Surveying Farms to Tidying our Homes with Robots”
DESCRIPTION:For decades\, the robotics community has been working on developing intelligent autonomous machines that can perform complex tasks in unstructured environments. We are now closer than ever to delivering on this promise. Robotic systems are being developed\, tested and deployed for a wide range of applications. In this talk\, I will present our work on building robots for agriculture and home automation which are two application domains with distinct sets of associated challenges. In agriculture\, robots must be capable of operating on very large farms under rough conditions while maintaining precision to efficiently perform tasks such as yield mapping\, fruit picking and weeding. In these applications\, the state of the art perception algorithms are capable of generating intermediate geometric representations of the environment. However\, the resulting planning problems are often hard. I will present some of our work on tracking and mapping and give examples of field deployments. In home automation\, the robots must be able to handle a large variety of objects and clutter. In such settings\, generating precise geometric models as intermediate representations is not always possible. To address this challenge\, I will present our recent and ongoing work on developing state representations for coupled perception and action planning for representative home automation applications such as decluttering.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-from-surveying-farms-to-tidying-our-homes-with-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:20220222T100000
DTEND;TZID=America/New_York:20220222T113000
DTSTAMP:20260406T185435
CREATED:20220214T152040Z
LAST-MODIFIED:20220214T152040Z
UID:10007085-1645524000-1645529400@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Understanding Particulate Soft Materials: An Integrated Approach for Novel Energy and Environmental Solutions"
DESCRIPTION:Many industrial processes involve multiphase soft materials in which solid particles are dispersed or co-exists with a fluid phase and are therefore referred to as Particulate Soft Materials (PSMs). Examples can be found in many industries\, including food\, cosmetics\, pharmaceutical\, and energy\, as well as in natural settings\, e.g.\, soils and glaciers. PSMs often display a complex mechanical behavior that is characterized by features common to both viscous fluids and elasto-plastic solids\, with material properties that can change over time due to thermodynamic\, chemical or kinematic conditions. Consequently\, these complexities and our limited understanding of the behavior of PSMs can lead to critical industrial challenges\, ranging from quality control of concrete to shelf-life of consumer products. These issues can also prove environmentally disastrous\, as in the case of clogged subsea pipelines or in landslides and avalanches. Such problems call for immediate solutions to measure and model the PSM overall mechanical behavior\, towards an improved understanding of this vast class of materials and corresponding processes. \nMy research demonstrates that these challenges can be overcome by: (i) introducing novel experimental tools and protocols that allow us to study the mechanical and rheological response of PSMs\, even when their behavior is rapidly changing\, or mutating\, in time; and (ii) rigorously setting sound theoretical frameworks that explain the experimental observations. In this talk\, focusing on two PSMs that are of interest to the energy industry (i.e.\, paraffin gels and hydrate suspensions)\, I will introduce an example of the integrated experimental and theoretical framework that can successfully capture PSM complex visco-plastic response. As I will demonstrate in my talk\, this powerful approach not only improves our understanding of both artificial and natural PSMs\, but also provides guidelines to develop superior materials for critical energy and environmental challenges.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-understanding-particulate-soft-materials-an-integrated-approach-for-novel-energy-and-environmental-solutions/
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:20220222T110000
DTEND;TZID=America/New_York:20220222T120000
DTSTAMP:20260406T185435
CREATED:20220216T145905Z
LAST-MODIFIED:20220216T145905Z
UID:10007087-1645527600-1645531200@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Towards Fair and Efficient Machine Learning with Large Models"
DESCRIPTION:Deep networks often achieve better accuracy as we employ larger models. However\, modern machine learning applications involve multiple considerations alongside accuracy\, such as resource-efficiency\, robustness\, or fairness. Deploying ML in the real-world requires sound solutions addressing these considerations. \nIn this talk\, I will first discuss optimizing fairness objectives for imbalanced data. We observe that a large model can easily achieve “perfect fairness” on training data but dramatically fail at the test-time due to overfitting. To address this\, we propose two strategies\, (1) A new family of fairness-seeking loss functions\, (2) Algorithms that optimize validation (rather than training) objective\, and combine them to achieve state-of-the-art performance. We also introduce new optimization methods that extend these to decentralized settings. \nI will then discuss training efficient sparse models. While conventional wisdom strongly advocates the use of regularization\, we observe that perfectly fitting a large model to data and then pruning it achieves stellar accuracy. We demystify this surprising feature-selection ability through a flexible theory which can answer “How good is the pruned model?”. \nIn summary\, our results provide several insights on learning with large models: (1) Our theory based on linear and random-feature models provide useful intuitions for understanding modern deep learning\, (2) Large models can benefit from unconventional training strategies such as new loss functions\, and (3) Validation phase is particularly helpful for large models that are susceptible to overfitting.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-towards-fair-and-efficient-machine-learning-with-large-models/
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:20220222T153000
DTEND;TZID=America/New_York:20220222T163000
DTSTAMP:20260406T185435
CREATED:20220208T210700Z
LAST-MODIFIED:20220208T210700Z
UID:10007075-1645543800-1645547400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Modern Fine-grained Algorithms for Classic Problems"
DESCRIPTION:How fast can we solve or approximate classic problems that are known to admit a polynomial time solution? Often times the existing polynomial time algorithms are slow for practical applications. Fine-grained algorithm design aims to better understand the computational complexity of these problems and illustrates tradeoffs between the runtime of the algorithms and the quality of their solutions.\n\nIn this talk\, I will present my work on classic and fundamental problems in fine-grained complexity including edit distance\, longest common subsequence\, pattern matching\, longest increasing subsequence\, and knapsack. In particular\, my talk will cover an algorithm that approximates edit distance within a constant factor in truly subquadratic time. This answers a well-known question in combinatorial pattern matching.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-modern-fine-grained-algorithms-for-classic-problems/
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:20220223T110000
DTEND;TZID=America/New_York:20220223T120000
DTSTAMP:20260406T185435
CREATED:20220211T150239Z
LAST-MODIFIED:20220211T150239Z
UID:10007084-1645614000-1645617600@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Quantum Many-Body Physics in the NISQ Era"
DESCRIPTION:Rapid progress in quantum computing technologies is ushering in a new era for quantum many-body physics. Today’s noisy\, intermediate-scale quantum (NISQ) devices\, while still far from fault-tolerant quantum computers\, are exceptional laboratory systems\, with large many-body Hilbert spaces and unprecedented capabilities for control and measurement. This allows the exploration of quantum dynamics in new far-from-equilibrium regimes\, and motivates new paradigms of phase structure. In this talk I will focus on two such paradigms: eigenstate-ordered phases in periodically driven systems\, and entanglement phases in “monitored” systems\, whose dynamics include projective measurements alongside unitary operations. As an example of the former\, I will discuss the realization of a “discrete time crystal” (DTC) on Google Quantum AI’s Sycamore processor\, focusing on the conceptual challenges involved in detecting the DTC’s signature eigenstate order despite intrinsic limitations of NISQ hardware. I will then present a new window into measurement-induced entanglement phases based on the idea of space-time duality: a transformation that relates unitary and monitored circuits by exchanging the roles of space and time in the dynamics\, which can be implemented on digital quantum simulators through a generalized “quantum teleportation” protocol.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-quantum-many-body-physics-in-the-nisq-era/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220223T150000
DTEND;TZID=America/New_York:20220223T160000
DTSTAMP:20260406T185435
CREATED:20220218T161426Z
LAST-MODIFIED:20220218T161426Z
UID:10007090-1645628400-1645632000@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Marc Finzi\, New York University\, "Embedding Symmetries and Conservation Laws in Deep Learning Models for Dynamical Systems"
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nIn contrast to traditional control systems where detailed dynamics models are constructed from a mix of physical understanding and empirical data\, machine learning for intuitive physics\, reinforcement learning\, and robotics often takes a hands off approach treating the dynamics as a black box with little to no assumed structure. We show how desirable high level properties like symmetries\, energy and momentum conservation\, and other constraints can be reintroduced into these models to improve generalization. These high level attributes represent prior knowledge about the underlying physics of the system in the Bayesian sense\, and can even be incorporated in a way that does not limit the flexibility of the model.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-marc-finzi-new-york-university-embedding-symmetries-and-conservation-laws-in-deep-learning-models-for-dynamical-systems/
LOCATION:Levine 512
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:20220223T153000
DTEND;TZID=America/New_York:20220223T163000
DTSTAMP:20260406T185435
CREATED:20220113T034509Z
LAST-MODIFIED:20220113T034509Z
UID:10007010-1645630200-1645633800@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: “Beyond Ethanol: A Process and Systems Engineering Framework for the Design of Advanced Biofuels”
DESCRIPTION:Abstract \nIn my talk\, I will present my work on the application of process and systems engineering techniques to the design of integrated biorefineries that produce middle distillates (jet fuel and diesel). Unlike gasoline\, demand for middle distillates is expected to increase over the next 30 years\, and electrification and decarbonization of sectors where middle distillates are used (such as aviation and freight) is challenging. Biofuels offer a potentially sustainable alternative\, with the upgrading of ethanol to diesel and jet fuel being especially attractive. The ethanol upgrading platform has several advantages: (1) it can make use of available infrastructure; (2) it can be used to produce fuels over the whole distillation spectrum; and (3) it offers multiple chemical alternatives\, enabling the possibility of tailoring the properties of the fuels produced. \nDespite its advantages\, designing an optimal ethanol upgrading strategy is challenging\, as it requires the integration of three different areas: catalysis\, process synthesis\, and fuel property modeling. The challenges associated with the formulation of a framework integrating these areas\, coupled with the large design space characteristic of the problem\, have led scientists to rely on ad hoc approaches. In contrast\, in this talk\, the systematic design of ethanol upgrading biorefineries based on superstructure optimization will be discussed. Four fundamental questions will be addressed: (1) What are the energy requirements associated with the production of middle distillates? (2) What is the interplay among fuel properties\, economics\, and processes? (3) What is the relationship among biorefinery complexity\, processes\, and the fuels obtained? and (4) What is the ability of the advanced fuels identified in this work to satisfy fuel demand and mitigate CO2 emissions?
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-beyond-ethanol-a-process-and-systems-engineering-framework-for-the-design-of-advanced-biofuels/
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:20220223T153000
DTEND;TZID=America/New_York:20220223T163000
DTSTAMP:20260406T185435
CREATED:20220211T010712Z
LAST-MODIFIED:20220211T010712Z
UID:10007078-1645630200-1645633800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Firm Foundations for Private Machine Learning and Statistics"
DESCRIPTION:How can researchers use sensitive datasets for machine learning and statistics without compromising the privacy of the individuals who contribute their data?  In this talk I will describe my work on the foundations of differential privacy\, a rigorous framework for answering this question.  In the past decade\, differential privacy has gone from largely theoretical to widely deployed\, and a theme of the talk will be how new deployments are forcing us to revisit foundational questions about differential privacy.  This talk will cover a range of issues from the fundamental—like optimal private statistical inference—to the applied—like auditing differentially private machine learning.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-firm-foundations-for-private-machine-learning-and-statistics/
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:20220224T110000
DTEND;TZID=America/New_York:20220224T120000
DTSTAMP:20260406T185435
CREATED:20220222T131917Z
LAST-MODIFIED:20220222T131917Z
UID:10007099-1645700400-1645704000@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Provably Robust Algorithms for Prediction and Control"
DESCRIPTION:Feedback-driven decision-making systems are at the emerging frontier of machine learning applications. Upcoming applications of societal consequence\, such as self-driving vehicles and smartwatch-based health interventions\, have to contend with the challenge of operating in reactive stateful environments. In this talk\, I will describe my work on designing principled robust algorithms for feedback-driven learning\, with provable guarantees on computational and statistical efficiency. \nFirst\, I will introduce an efficient instance-optimal algorithm for control in the presence of adversarial disturbances. Beyond the realm of both stochastic and robust control\, such a data-driven notion of optimality combines worst-case guarantees with a promise of exceptional performance on benign instances. Moving on to prediction\, I will present a computationally and statistically efficient forecasting strategy for latent-state dynamical systems exhibiting long term dependencies\, mitigating the statistical challenge of learning with correlated samples\, and the computational difficulties associated with a non-convex maximum likelihood objective. To conclude\, I will discuss some practically relevant fundamental questions at the intersection of machine learning\, optimization\, and control that have the potential to unlock real progress in downstream applications.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-provably-robust-algorithms-for-prediction-and-control/
LOCATION:Zoom – Meeting ID 958 3045 4776
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220224T153000
DTEND;TZID=America/New_York:20220224T163000
DTSTAMP:20260406T185435
CREATED:20220211T012014Z
LAST-MODIFIED:20220211T012014Z
UID:10007079-1645716600-1645720200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learning to Generate Data by Estimating Gradients  of the Data Distribution"
DESCRIPTION:Generating data with complex patterns\, such as images\, audio\, and molecular structures\, requires fitting very flexible statistical models to the data distribution. Even in the age of deep neural networks\, building such models is difficult because they typically require an intractable normalization procedure to represent a probability distribution. To address this challenge\, I propose to model the vector field of gradients of the data distribution (known as the score function)\, which does not require normalization and therefore can take full advantage of the flexibility of deep neural networks. I will show how to (1) estimate the score function from data with flexible deep neural networks and principled statistical methods\, (2) generate new data using stochastic differential equations and Markov chain Monte Carlo\, and even (3) evaluate probabilities as in a traditional statistical model. The resulting method\, called score-based generative modeling\, achieves record-breaking performance in applications including image synthesis\, text-to-speech generation\, time series prediction\, and point cloud generation\, challenging the long-time dominance of generative adversarial networks (GANs) on many of these tasks. Furthermore\, unlike GANs\, score-based generative models are suitable for Bayesian reasoning tasks such as solving ill-posed inverse problems\, and I have demonstrated their superior performance on examples like sparse-view computed tomography and accelerated magnetic resonance imaging. Finally\, I will discuss how score-based generative modeling opens up new opportunities and new future research directions for building better machines to create and understand complex data in various disciplines of science and engineering.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learning-to-generate-data-by-estimating-gradients-of-the-data-distribution/
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:20220225T100000
DTEND;TZID=America/New_York:20220225T110000
DTSTAMP:20260406T185435
CREATED:20220217T164449Z
LAST-MODIFIED:20220217T164449Z
UID:10007089-1645783200-1645786800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Microfluidic Devices with Capillary Circuits for User-friendly\, Low-cost\, Multiplexed Point-of-care\, Molecular Diagnostics"
DESCRIPTION:Rapid\, sensitive\, and specific detection is key to personalized medicine and to the prompt implementation of appropriate mitigation measures to reduce disease transmission\, mortality\, morbidity\, and cost. Conventional molecular detection methods require trained personnel and specialized laboratories\, which limits their use to centralized laboratories. Microfluidics enables point-of-care testing. \nIn this talk\, I will show how capillary circuits help automate liquid-distribution and sealing processes and eliminate the need for expensive equipment and highly skilled personnel. Next\, I will present two examples of fully 3D-printed microfluidic devices with capillary valves that were designed\, respectively\, for single-stage and two-stage\, multiplexed isothermal molecular detections of human\, animal\, and plant diseases.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-microfluidic-devices-with-capillary-circuits-for-user-friendly-low-cost-multiplexed-point-of-care-molecular-diagnostics/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220225T103000
DTEND;TZID=America/New_York:20220225T114500
DTSTAMP:20260406T185435
CREATED:20220221T195817Z
LAST-MODIFIED:20220221T195817Z
UID:10007098-1645785000-1645789500@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Jia Deng\, Princeton University\, “Toward Dense 3D Reconstruction in the Wild”
DESCRIPTION:This seminar will be held in person in Wu and Chen Auditorium as well as virtually via Zoom. \nReconstructing depth and motion of every pixel for arbitrary scenes is a core problem in 3D vision with many downstream applications. In this talk\, I will describe some of our recent efforts toward this goal\, including various strategies to obtain effective training data for single-image 3D reconstruction\, and new neural architectures that advance the state of the art of multiview 3D reconstruction.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-jia-deng-princeton-university-toward-dense-3d-reconstruction-in-the-wild-2/
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
END:VCALENDAR