BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200921T110000
DTEND;TZID=America/New_York:20200921T120000
DTSTAMP:20260407T192134
CREATED:20200914T160000Z
LAST-MODIFIED:20200914T160000Z
UID:10006492-1600686000-1600689600@seasevents.nmsdev7.com
SUMMARY:Climate Week: Africa and Climate Change: Challenges and Solutions in a Globalized World
DESCRIPTION:Speaker:\nAnthony Nyong\, Director of Climate Change and Green Growth at the African Development Bank (AfDB) \nSpeaker Bio:\nBio: Professor Anthony Nyong is the Director of Climate Change and Green Growth at the African Development Bank. He has about 30 years of experience in environmental and natural resources management\, environmental and social safeguards\, renewable energy and green growth that span academia\, private sector and development finance. Positions he has held at the African Development Bank include Coordinator of the New Deal on Energy for Africa; Head of the Renewable Energy Flagship\, Head of Gender\, Climate Change and Sustainable Development; and Head of Compliance and Safeguards. Before joining the Bank\, he was a Senior Climate Change Specialist at the International Development Research Centre of Canada and prior to that\, a Professor of Climate Change at the University of Jos\, Nigeria. \nProf. Nyong has served on several Global Advisory and Scientific Boards including the Sustainable Stock Exchange Green Finance Advisory Group\, the Ministerial Advisory Committee on Agricultural Resilience in Nigeria; WHO Thematic Reference Group on Environment\, Agriculture and Infectious Disease; Scientific and Technical Advisory Panel of the Global Environment Facility; the International Human Dimensions Program\, Global Environmental Change and Food Systems\, and Pan-African committee for the Global Change System for Analysis\, Research and Training. He has served on the Boards of the Applied Center for Climate and Earth Systems Science\, South Africa and the International Centre for Climate Change and Development at the Independent University\, Bangladesh. Nyong is a member of the Planning Committee of the Climate and Health Initiative of the National Academy of Medicine (USA). He was a Coordinating Lead Author for the IPCC Fourth Assessment Report and a member of the IPCC Task Group on Data and Scenario Support for Impact and Climate Analysis. \nMr. Nyong holds a Ph.D. in Geography from McMaster University\, Canada and a D.Sc. (hc) from the University of Calabar in Nigeria\, a post-graduate Diploma from the University of Oxford and a Masters Degree in Land Surveying from Ahmadu Bello University in Nigeria. He is a Senior Executive Fellow of the Harvard Kennedy School of Government\, a Chartered Geographer\, a Fellow of the African Academy of Sciences and a Fellow of the Royal Geographical Society. He is named among the top 20 of the 100 most Influential People in Climate Policy 2019 by Apolitical. \nModerator:\nTukufu Zuberi\, Professor of Sociology and The Lasry Family Professor of Race Relations at the University of Pennsylvania \nDescription:\nStudies and forecasts indicate\, according to Dr. Anthony Nyong\, Director of Climate Change and Green Growth at the African Development Bank\, that “While Africa bears a considerably large proportion of the impacts of climate change\, it also has opportunities to enable it transition to a more sustainable growth pathway.” Dr. Nyong will discuss the effects of Climate Change in Africa and steps that encourage sustainability in Africa and thus resilience to Climate Change. These steps can lead to  transformation and transition to green economies in the continent with positive global implications.
URL:https://seasevents.nmsdev7.com/event/webinar-africa-and-climate-change-challenges-and-solutions-in-a-globalized-world/
LOCATION:PA
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2020/09/monday.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200922T030000
DTEND;TZID=America/New_York:20200922T040000
DTSTAMP:20260407T192134
CREATED:20200914T200450Z
LAST-MODIFIED:20200914T200450Z
UID:10006498-1600743600-1600747200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Engineering Approximate Computations"
DESCRIPTION:  \nThere’s a new ecosystem of applications that integrates machine learning into a variety of tasks. Typical domains have included image recognition and natural language processing. However\, these techniques have also spread to computer systems domains\, such as program compilation\, resource scheduling\, and database query optimization\, yielding new computer systems that learn from data to achieve their goals. \n  \nWith the success of these systems\, we must grapple with the reality that they model and compute with objects that are inherently approximate — real numbers (only computable up to a given precision)\, neural networks (only validated on a given dataset)\, and probabilistic computations (results only computable up to a given probability). This reality presents many engineering questions about interpreting\, debugging\, validating\, verifying\, and optimizing these systems. \n  \nAs an illustrative example of such a system\, I’ll present Ithemal\, our deep learning system for performance modeling of modern computer processors. Using data and simple models\, our system predicts the performance of assembly code on modern Intel CPUs better than state-of-the-art\, handcrafted techniques from LLVM and Intel. \n  \nGuided by Ithemal’s engineering challenges\, I’ll present our work on reasoning about the semantics and performance of such a system. \nIn particular\, I’ll present our results on the semantics of sound real-valued\, differentiable\, probabilistic computation\, which is the core computational model behind this new class of systems.  I’ll also present our work on the Lottery Ticket Hypothesis\, a set of techniques for producing small trainable neural networks that are 10-20% of the size of standard architectures. The promise of this latter work is not only faster inference and training\, but also smaller neural networks that are more amenable to reasoning\, such as verifying their robustness
URL:https://seasevents.nmsdev7.com/event/cis-seminar-engineering-approximate-computations/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200922T090000
DTEND;TZID=America/New_York:20200922T103000
DTSTAMP:20260407T192134
CREATED:20200914T155654Z
LAST-MODIFIED:20200914T155654Z
UID:10006496-1600765200-1600770600@seasevents.nmsdev7.com
SUMMARY:ESE Thesis Defense: "Constrained Learning and Inference"
DESCRIPTION:Learning is a core component of the information processing and autonomous systems upon which we increasingly rely on to select job applicants\, analyze medical data\, and drive cars. As these systems become ubiquitous\, so does the need to curtail their behavior. Left untethered\, they are susceptible to tampering (adversarial examples) and prone to prejudiced and unsafe actions. Currently\, this is done by either constructing models that embed the desired properties or tuning the training objective so as to promote them. Yet\, these approaches are often tailored to specific problems\, are hard to transfer between models\, and involve time consuming trial-and-error procedures that are impractical even for the current scale and complexity of modern machine learning systems. In this defense\, I develop the theoretical underpinnings of constrained learning to understand how requirements affect statistical learning and enable behaviors to be directly and systematically designed. To do so\, I will derive a generalization theory for constrained learning based on the probably approximately correct (PAC) learning framework. In particular\, I will show that imposing requirements does not make a learning problem harder in the sense that any PAC learnable class is also PAC constrained learnable using a constrained counterpart of the empirical risk minimization (ERM) rule. For typical parametrized models\, however\, this learner involves solving a non-convex constrained optimization program for which even obtaining a feasible solution may be hard. To overcome this issue\, we prove that under mild conditions the empirical dual problem of constrained learning is also a PAC constrained learner. Hence\, constrained learning problems can be solved by solving only unconstrained ones\, leading to a practical constrained learning algorithm. We illustrate how constrained learning can address problems in fair and robust classification.
URL:https://seasevents.nmsdev7.com/event/ese-thesis-defense-constrained-learning-and-inference/
LOCATION:Zoom – Email ESE for Link jbatter@seas.upenn.edu
CATEGORIES:Doctoral,Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200922T103000
DTEND;TZID=America/New_York:20200922T120000
DTSTAMP:20260407T192134
CREATED:20200901T145332Z
LAST-MODIFIED:20200901T145332Z
UID:10006466-1600770600-1600776000@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Robots and Mechatronic Systems can help us identify\, assess\, and treat Motor and Cognitive Impairment after Brain Injury"
DESCRIPTION:The US Centers for Disease Control (CDC) indicate that in 2017 about 12.7% of adults and children had some form of disability. Stroke is the leading cause of serious long-term disability with ~7 million in the US\, which will increase by 20.5% by 2030. Cerebral Palsy is the leading cause of serious long-term disability in children with reports suggesting that 1 in 323 children in the US have CP which represent approximately ~230\,000 children in the US. Both these diseases result in varying levels of motor and cognitive impairment due to brain injury which affects then affects the persons ability to complete activities of daily living and fully participate in society. Increasingly advanced technologies are being used to support identification\, diagnosis\, assessment\, and therapy for patients with brain injury. Specifically\, robot and mechatronic systems can provide patients\, physicians and rehabilitation clinical providers with additional support to care for and improve the quality of life of children and adults with motor and cognitive impairment. This talk will provide a brief introduction to the area of rehabilitation robotics and \,via case studies\, illustrate how we develop and use technology-assisted rehabilitation systems to assess motor and cognitive impairment\, detect early evidence of functional impairment\, and augment therapy in high and low-resource settings.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-robots-and-mechatronic-systems-can-help-us-identify-assess-and-treat-motor-and-cognitive-impairment-after-brain-injury/
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:20200922T130000
DTEND;TZID=America/New_York:20200922T140000
DTSTAMP:20260407T192134
CREATED:20200914T155952Z
LAST-MODIFIED:20200914T155952Z
UID:10006493-1600779600-1600783200@seasevents.nmsdev7.com
SUMMARY:Climate Week: Advancing Technology to Ensure Food\, Energy\, and Water Security
DESCRIPTION:Speaker:\nCherie Kagan\, Associate Dean of Research\, Stephen J Angello Professor\,  Electrical and Systems Engineering\, Material Science and Engineering\, Penn Engineering. Director\, NSF’s Internet of Thing’s for Precision Agriculture Engineering Research Center \nDescription:\nEnsuring food\, energy\, and water security is a societal grand challenge. By 2050\, the US population is estimated to grow from 330 million to 400 million\, and the world population from 7.8 billion to 9.7 billion\, requiring a 70% increase in global food production. Current agricultural practices account for 70% of global water use\, and energy use accounts for the largest cost on a farm. Furthermore\, the current inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land\, water\, and energy resources\, there is a critical need for new technologies and innovations to improve the efficiency of food production. These challenges provide a unique opportunity for scientists\, engineers\, practitioners\, and other stakeholders to come together and develop new technologies and solutions that would not be realized without a convergent approach. The NSF Engineering Research Center for the Internet of Things for Precision Agriculture (IoT4Ag) unites faculty and students from the University of Pennsylvania\, Purdue University\, the University of California at Merced\, and the University of Florida with government and industry partners\, establishing a convergence of expertise in agronomy\, agricultural engineering\, socio-economics\, environmental science\, and the science and engineering of physical and cyber-physical systems needed to transform agriculture. The goal of this center is to ensure food\, energy\, and water security by advancing technology to increase crop production while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. To realize this mission\, IoT4Ag will create and translate to practice Internet of Things (IoT) technologies for precision agriculture and train an educated and diverse workforce that will address the societal grand challenge of food\, energy\, and water security for decades to come. IoT4Ag institutions are located in regions of the United States of intense agricultural production and represent the diversity of both crops and agricultural environments across the country. The coverage of these diverse geographical locations will ensure that a broad range of crop types will benefit from the research\, education\, and training of IoT4Ag\, leading to the successful transformation of agricultural practices for a sustainable and secure future. \nThe IoT4Ag team will investigate how the complex systems of plant and environmental variables affect crop yield and resilience. To accomplish this task\, center researchers will focus on the development of low-cost sensor technologies to measure these variables at relevant spatial and temporal scales. To utilize these sensors and the data collected\, IoT4Ag will develop agriculture-specific communication technologies that relay data from sensors to both relevant farming equipment and to the cloud by autonomous aerial and ground-based robots equipped to be deployed at field scale. Data-driven models will capture plant physiology\, soil properties and dynamics\, historical weather trends and future forecasts\, management practice variations\, and socio-economic trends to provide farmers the situational awareness necessary for smart agricultural intervention and improved outcomes. Through the research and development of these proposed technologies and solutions\, IoT4Ag will educate a diverse workforce of pre-college students\, community college students\, university students\, and agriculture professionals through audience-specific lessons and hands-on classroom\, laboratory\, and field activities. These activities will arm this new workforce with the strong science and engineering knowledge to enable precision agriculture solutions. IoT4Ag will recruit\, retain\, and educate diverse participants and create a culture of inclusion through engagement\, participation\, and cohesion of a broad community of students\, faculty\, and professionals. This vibrant innovation ecosystem will bring together academic\, government\, and industry partners with the end-user farming community to ensure the rapid translation of IoT4Ag practices and technologies into commercial products and economic impact. Through all of these described activities\, IoT4Ag will enable the transformation of agriculture\, producing more crops for every drop of water or Joule of energy to realize a food\, energy\, and water-secure future for the United States.
URL:https://seasevents.nmsdev7.com/event/webinar-advancing-technology-to-ensure-food-energy-and-water-security/
LOCATION:PA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200923T100000
DTEND;TZID=America/New_York:20200923T110000
DTSTAMP:20260407T192134
CREATED:20200917T213808Z
LAST-MODIFIED:20200917T213808Z
UID:10006504-1600855200-1600858800@seasevents.nmsdev7.com
SUMMARY:MEAM PHD Thesis Defense: "Control of Dry Adhesion via Mechanics and Structuring"
DESCRIPTION:Dry adhesives that rely on van der Waals forces have a number of applications due to their versatility\, reusability\, and repeatability. Applications include small-scale pick-and-place and microtransfer printing processes\, wearable sensors\, climbing/perching robots\, and robotic gripping. However\, van der Waals forces are macroscopically short-range and are the weakest of the interatomic forces\, so careful mechanical design of adhesive structures is required to provide sufficient dry adhesion strength for many of these applications. This thesis investigates the mechanics-based design of structured dry adhesives with enhanced and controllable adhesion. \nFirst\, a mechanics-based strategy for achieving the optimum interfacial stress distribution of an elastic layer to realize high adhesion strength is presented. Second\, dry adhesion tuning via the control of the interfacial stress distribution via subsurface pressure modulation in soft device is analyzed and demonstrated. Then\, the mechanics of adhesion of flat-ended pillars with non-circular contacts to enable the design of fibrillar adhesives with high packing density is investigated. Finally\, the mechanics of tunable adhesion in microtransfer printing processes is examined and a strategy to provide robust control of microtransfer printing processes is proposed.
URL:https://seasevents.nmsdev7.com/event/meam-phd-thesis-defense-control-of-dry-adhesion-via-mechanics-and-structuring/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200923T110000
DTEND;TZID=America/New_York:20200923T120000
DTSTAMP:20260407T192134
CREATED:20200914T155945Z
LAST-MODIFIED:20200914T155945Z
UID:10006494-1600858800-1600862400@seasevents.nmsdev7.com
SUMMARY:Climate Week: Carbon Offsets Should Make a Difference: Connecting Offsets for University-Sponsored Air Travel to a Vision for an Energy and Climate Partnership with West Philadelphia
DESCRIPTION:Speakers:\nMegan Ryerson\, UPS Chair of Transportation\, Associate Dean for Research\, Weitzman School\nBenjamin C. Pierce\, Henry Salvatori Professor of Computer and Information Science\, Penn Engineering\nWilliam W. Braham\, Professor of Architecture\, Director of the Master of Environmental Building Design and of the Center for Environmental Building + Design\, Weitzman School\nSteve Luxton\, Executive Director/CEO at the Energy Coordinating Agency of Philadelphia (ECA). ECA provides community-based energy efficiency services and assistance to low-income families in Philadelphia.\nAndrew Huemmler\, Senior Lecturer\, School of Engineering and Applied Science\, Member of the Board of Directors of the Energy Coordinating Agency of Philadelphia\nRegina Bynum\, Director of Teaching and Learning for University-Assisted Community School Programs\, The Netter Center for Community Partnerships \nModerator:\nSimon Richter\, Class of 1942 Endowed Term Professor of Germanic Languages and Literature\, Chair of the Climate Week at Penn Organizing Team \nDescription: \nBefore the pandemic\, air travel was one of the major contributors to global greenhouse gas emissions. Whether you travel privately or for your institution or company\, invariably air travel makes up the biggest chunk of your carbon footprint and overshadows your other efforts. To its credit\, the University of Pennsylvania recognized that University-sponsored air travel made up 20% of Penn’s carbon emissions\, making it the second largest source of carbon emissions at Penn. In January\, 2020\, the University announced a plan to purchase carbon offsets to neutralize its emissions. Join Penn experts and Steve Luxton\, CEO of the Energy Coordinating Agency\, for a webinar that will focus on \n– the carbon footprint of air travel and air transportation trends in the US and globally\n– how carbon offsets work and what options there are for individuals\n– Penn’s plans to offset university-sponsored air travel\n– developing a vision of how Penn could invest its carbon offsets to help residents in West Philadelphia become more energy efficient\, switch to renewables\, and become more climate adaptive
URL:https://seasevents.nmsdev7.com/event/webinar-carbon-offsets-should-make-a-difference-connecting-offsets-for-university-sponsored-air-travel-to-a-vision-for-an-energy-and-climate-partnership-with-west-philadelphia/
LOCATION:PA
ATTACH;FMTTYPE=image/png:https://seasevents.nmsdev7.com/wp-content/uploads/2020/09/plane.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200924T104500
DTEND;TZID=America/New_York:20200924T114500
DTSTAMP:20260407T192134
CREATED:20200910T134558Z
LAST-MODIFIED:20200910T134558Z
UID:10006487-1600944300-1600947900@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "How to Care for Yourself While Navigating a Complex World"
DESCRIPTION:As graduate students\, it can be difficult to maintain a sense of balance throughout your academic career. There are often multiple demands on your time\, from having a social life while performing well academically to maintaining your mental health and wellness. However\, 2020 has brought unique challenges that include\, managing a global pandemic\, navigating issues related to racism and xenophobia and coping with significant losses of loved ones and experiences. Come join us as we discuss the impact of these stressors on your mental health and explore strategies for coping.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-how-to-care-for-yourself-while-navigating-a-complex-world/
LOCATION:PA
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200924T110000
DTEND;TZID=America/New_York:20200924T120000
DTSTAMP:20260407T192134
CREATED:20200914T155858Z
LAST-MODIFIED:20200914T155858Z
UID:10006495-1600945200-1600948800@seasevents.nmsdev7.com
SUMMARY:Climate Week: Embodied Carbon and the Built Environment: A Focus on Mass Timber
DESCRIPTION:Speakers:\nKerry Phillips\, Associate at Lake|Flato Architects\nHeather Gayle Holdridge\, Director of Design Performance at Lake|Flato Architects\nTerry Pattillo\, AIA\, Mid-Atlantic Regional Director\, WoodWorks – Wood Products Council \nModerator:\nStephanie Carlisle\, Senior Researcher\, Carbon Leadership Forum
URL:https://seasevents.nmsdev7.com/event/webinar-embodied-carbon-and-the-built-environment-a-focus-on-mass-timber/
LOCATION:PA
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2020/09/timber.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200924T150000
DTEND;TZID=America/New_York:20200924T160000
DTSTAMP:20260407T192134
CREATED:20200728T152022Z
LAST-MODIFIED:20200728T152022Z
UID:10006444-1600959600-1600963200@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Patients\, Providers and Data: How the EMR and Data Science are Changing Clinical Care" (Kevin Johnson)
DESCRIPTION:This event will be held virtually via zoom. Check your email for the link and passcode or contact ksas@seas.upenn.edu. \nThe electronic health record (EHR) is a powerful application of Systems Engineering to healthcare. It is a byproduct of a host of pressures including  cost\, consolidation of providers into networks\, uniform drivers of quality\, and the need for timely care across disparate socioeconomic and geographic landscapes within health systems. The EHR is also a fulcrum for innovation and one of the most tangible examples of how data science affects our health and health care. In this talk I will showcase projects from my lab that demonstrate the multi-disciplinary nature of biomedical informatics/data science research and translation using the EHR\, and our current understanding of its potential from my perspective as a pediatrician\, a researcher in biomedical informatics\, a Chief Information Officer\, an educator\, and an advisor to local and international policy. I will describe advances in applying human factors engineering to support medical documentation and generic prescribing\, approaches to improve medication safety\, and innovations to support precision medicine and interoperability. I will present our efforts to integrate EHR-enabled data science into the Vanderbilt health system and provide a vision for what this could mean for our future.
URL:https://seasevents.nmsdev7.com/event/be-seminar-6/
LOCATION:PA
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200925T100000
DTEND;TZID=America/New_York:20200925T110000
DTSTAMP:20260407T192134
CREATED:20200924T185639Z
LAST-MODIFIED:20200924T185639Z
UID:10006512-1601028000-1601031600@seasevents.nmsdev7.com
SUMMARY:SIG Seminar: "Coupling Sub-Grid Solids\, Simulating Liquid Metals\, and Inferring Facial Expressions"
DESCRIPTION:This lecture will discuss recent results in computational physics\, computer graphics\, and learning/data science.  The first section will present a method for accurately simulating two-way solid-fluid coupling even when solids may be smaller than the size of a computational grid cell.  Next\, a numerical method for simulating materials with large surface energy (such as liquid metals) will be discussed.  The third part of the lecture will introduce techniques for obtaining sparse semantic solutions to inverse and optimization problems\, with a case study of inferring facial expressions from RGB images.  The lecture will conclude with future research directions at the interfaces of simulation\, graphics\, learning\, and data.
URL:https://seasevents.nmsdev7.com/event/sig-seminar-coupling-sub-grid-solids-simulating-liquid-metals-and-inferring-facial-expressions/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200925T110000
DTEND;TZID=America/New_York:20200925T120000
DTSTAMP:20260407T192134
CREATED:20200914T155914Z
LAST-MODIFIED:20200914T155914Z
UID:10006497-1601031600-1601035200@seasevents.nmsdev7.com
SUMMARY:Climate Week: A Case for Carbon Removal From Air
DESCRIPTION:Speakers:\nJennifer Wilcox\, Presidential Distinguished Professor of Chemical Engineering and Energy Policy\, Penn Engineering\, Weitzman School\nNoah McQueen\, Third year Ph.D. candidate in Chemical Engineering\, Penn Engineering \nModerator:\nMark Alan Hughes\, Founding Faculty Director of the Kleinman Center for Energy Policy \nDescription:\nAs the atmospheric concentration of carbon dioxide (CO2) continues to rise\, it is imperative that we develop technologies that not only mitigate CO2 emissions\, but also remove CO2 directly from the atmosphere. There are a variety of approaches that are being developed to do just this\, and many approaches will be required to achieve a meaningful scale to mitigate climate change. In our work\, we have been developing a novel\, land-based magnesium oxide looping process to capture CO2 from the air. The process takes in magnesium carbonate (MgCO3) and calcines the material at high temperatures (roughly 600 – 900ºC) to produce amorphous MgO. The produced MgO is subsequently spread out over land to carbonate for a year. Following carbonation\, the mineral is recollected and recalcined to reproduce MgO and a high purity stream of CO2. The MgO can then be spread out over the land to carbonate again. The resulting CO2 may be compressed and stored geologically or otherwise utilized. This carbon removal approach demonstrates the potential for high impact\, low cost carbon removal. \nPreliminary experiments were performed to corroborate the experimental uptake rate of CO2 onto MgO. Additional laboratory experiments will focus on the effect of the ambient reaction conditions on the overall kinetic rate. Further\, we have planned experiments for a small pilot test at the Pennovation center. This will use 1 m by 1 m containers of MgO to determine the viability of the process in open\, realistic ambient conditions\, as well as the impact of different experimental parameters on the reaction rate (including bed depth\, particle size distribution and material vendor). These parameters will help us optimize the MgO looping process and determine the potential impact as a carbon removal approach.
URL:https://seasevents.nmsdev7.com/event/webinar-a-case-for-carbon-removal-from-air/
LOCATION:PA
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2020/09/beach.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200926T100000
DTEND;TZID=America/New_York:20200926T160000
DTSTAMP:20260407T192134
CREATED:20200902T131849Z
LAST-MODIFIED:20200902T131849Z
UID:10006472-1601114400-1601136000@seasevents.nmsdev7.com
SUMMARY:PICS Workshop: "Machine Learning with MATLAB"
DESCRIPTION:Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. \nUsing MATLAB\, engineers and other domain experts have deployed thousands of applications for predictive maintenance\, sensor analytics\, finance\, and communication electronics. \nIn this hands-on workshop\, you will use MATLAB to: \n\nLearn the fundamentals of machine learning and understand terms like “supervised learning”\, “feature extraction”\, and “hyperparameter tuning”\nBuild and evaluate machine learning models for classification and regression\nPerform automatic hyperparameter tuning and feature selection to optimize model performance\nApply signal processing and feature extraction techniques\n\nPlease register here if you would like to attend:  https://www.mathworks.com/company/events/seminars/machine-learning-with-matlab-a-hands-on-workshop-3212994.html
URL:https://seasevents.nmsdev7.com/event/pics-workshop-machine-learning-with-matlab/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
CATEGORIES:Workshop
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200929T103000
DTEND;TZID=America/New_York:20200929T120000
DTSTAMP:20260407T192134
CREATED:20200827T212941Z
LAST-MODIFIED:20200827T212941Z
UID:10006449-1601375400-1601380800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Aluminum Scandium Nitride Microdevices for Next Generation Nonvolatile Memory and Microelectromechanical Systems"
DESCRIPTION:Aluminum Nitride (AlN) is a well-established thin film piezoelectric material. AlN bulk acoustic wave (BAW) radio frequency (RF) filters were one of the key innovations that enabled the 3G and 4G smart phone revolution. Recently\, the substitutional doping of scandium (Sc) for aluminum (Al) to form aluminum scandium nitride (AlScN) has been studied to significantly enhance the piezoelectric properties and to introduce ferroelectric properties into AlN based material systems. The properties achieved have profound implications for the performance of future 5G and 6G RF filters\, piezoelectric sensors\, piezoelectric energy harvesters\, and for scaling the bit density of ferroelectric nonvolatile memories. This talk will present on the synthesis of highly Sc doped AlScN materials of the thickness and quality needed for applications in memory and microelectromechanical systems (MEMS). The material properties achieved will be reported and placed in the context of device specific figures-of-merit and competing material systems. Ferroelectric and electromechanical devices that utilize the unique properties of AlScN to achieve state-of-the-art (SOA) performance will be shown.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-aluminum-scandium-nitride-microdevices-for-next-generation-nonvolatile-memory-and-microelectromechanical-systems/
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:20200929T110000
DTEND;TZID=America/New_York:20200929T120000
DTSTAMP:20260407T192134
CREATED:20200918T004934Z
LAST-MODIFIED:20200918T004934Z
UID:10006505-1601377200-1601380800@seasevents.nmsdev7.com
SUMMARY:ESE Seminar: "Evolutionary Adaptations and Spreading Processes in Complex Networks"
DESCRIPTION:A common theme among many models for spreading processes in networks is the assumption that the propagating object (e.g.\, a pathogen\, in the context of infectious disease propagation\, or a piece of information\, in the context of information propagation) is transferred across network nodes without going through any modification. However\, in real-life spreading processes\, pathogens often evolve in response to changing environments or medical interventions\, and information is often modified by individuals before being forwarded. In this talk\, we will discuss the effects of such adaptations on spreading processes in complex networks with the aim of revealing their role in determining the threshold\, probability\, and final size of epidemics\, and exploring the interplay between them and the structural properties of the network.
URL:https://seasevents.nmsdev7.com/event/ese-seminar-vince-poor/
LOCATION:Zoom – Email ESE for Link jbatter@seas.upenn.edu
CATEGORIES:Seminar,Faculty,Colloquium,Graduate,Undergraduate
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200929T110000
DTEND;TZID=America/New_York:20200929T120000
DTSTAMP:20260407T192134
CREATED:20200923T204317Z
LAST-MODIFIED:20200923T204317Z
UID:10006511-1601377200-1601380800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Experiencing a new Internet architecture"
DESCRIPTION:Imagining a new Internet architecture enables us to explore new networking concepts without the constraints imposed by the current infrastructure. What are the benefits of a routing protocol that does not rely on convergence? What about a data plane without inter-domain forwarding tables on routers? How can we build secure systems if a router can derive a symmetric key for any host within 20ns? \nIn this presentation\, we invite you to join us on our 11-year long expedition of creating a next-generation secure Internet architecture: SCION. SCION has already been deployed at several ISPs and domains\, and has been in production use for the past 3 years. On our journey\, we have found that path-aware networking and multipath communication not only provide security benefits\, but also enable higher efficiency for communication\, increased network capacity\, and even reduce power utilization. \n 
URL:https://seasevents.nmsdev7.com/event/cis-seminar-2/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200929T150000
DTEND;TZID=America/New_York:20200929T170000
DTSTAMP:20260407T192134
CREATED:20200922T212121Z
LAST-MODIFIED:20200922T212121Z
UID:10006510-1601391600-1601398800@seasevents.nmsdev7.com
SUMMARY:ESE PhD Defense: "Orbital angular momentum microlasers: From the first demonstration to ultrafast tunability"
DESCRIPTION:Orbital angular momentum (OAM) carried by structured vortex light establishes a new information dimension\, thereby promising high capacity optical communication and high performance computation in both classical and quantum regimes. Meanwhile\, laser is the key driver in the field of optics and photonics over other photonic components. Since its discovery\, laser technology has demonstrated strong impacts on a broad variety of applications\, especially in today’s information technology supporting fast growing cloud computing and communication. As microlaser plays an imperative role in modern integrated photonic platforms\, the development of OAM microlasers capable of direct generation of vortex light is critical in applying unbounded OAMs as information carriers to address the upcoming information explosion. However\, conventional microlaser designs offer coherent emission with rather simple polarization/phase states and suffer from instability. In this work\, we bring the non-Hermitian physics into the regime of nanophotonics to explore feasible designs of OAM microlasers. Non-Hermitian photonics based on parity-time symmetry successfully expands the design freedom from real material permittivity to a complete complex domain\, providing a versatile toolbox that empowers new functionalities in the realm of nanophotonics. Adapting optical non-Hermiticity into the design of microlasers enables enhanced lasing stability and efficiency\, leading to vortex microlaser emissions with a high sideband suppression ratio. By tailoring the complex index modulations at an exceptional point (EP) on a microring laser\, we demonstrated the very first OAM microlaser of which both the topological charge and the polarization state can be designed on demand. More recently\, we successfully promoted the OAM microlaser technology and achieved a dynamically tunable and scalable vortex microlaser\, providing 5 different OAM states at the same wavelength\, by optically controlled non-Hermitian coupling and spin-orbit interaction. Moreover\, we realized the ultrafast control of the fractional OAM by leveraging the rapid transient response of the semiconductor optical gain and demonstrated continuous sweeping of the fractional charge of microlaser emissions from 0 to +2 in a 100 ps time scale. The toolbox of ultrafast generation and control of various vortex light holds great promise for the development of entirely new high-speed secure information systems in a unique multidimensional space.
URL:https://seasevents.nmsdev7.com/event/ese-phd-defense-orbital-angular-momentum-microlasers-from-the-first-demonstration-to-ultrafast-tunability/
LOCATION:Zoom – Email ESE for Link jbatter@seas.upenn.edu
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200930T150000
DTEND;TZID=America/New_York:20200930T160000
DTSTAMP:20260407T192134
CREATED:20200916T233843Z
LAST-MODIFIED:20200916T233843Z
UID:10006500-1601478000-1601481600@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Understanding and Engineering Catalytic Materials Using Nanocrystal Precursors"
DESCRIPTION:Abstract\n \nCatalytic processes are central to the goal of a sustainable future. A promising approach in developing catalytic materials is represented by the design of catalytic sites based on the knowledge of reaction mechanisms and structure-property relationships and aided by computation\, and in the precise synthesis of these sites at the atomic and molecular level. Nanocrystal precursors\, with tunable active sites and compositions\, can help in this mission. The goal of this talk is to show how this approach can provide not only fundamental understanding of catalytic reactions\, but also a way to precisely engineer sites to produce efficient catalysts that are active\, stable and selective for several important transformations. Advances in the synthesis of these materials will be presented. Examples of the use of these building blocks as supported systems\, or in combination with hybrid organic materials\, will be shown. This will be done to both understand trends in methane and CO2 activation\, and in the preparation of optimized catalytic systems combining multiple active phases. In all these examples\, important efforts to obtain precious structure-property relationships will be highlighted with this knowledge used to prepare more efficient and stable catalysts for the sustainable production of fuels and chemicals.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-understanding-and-engineering-catalytic-materials-using-nanocrystal-precursors/
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:20201001T104500
DTEND;TZID=America/New_York:20201001T114500
DTSTAMP:20260407T192134
CREATED:20200828T150842Z
LAST-MODIFIED:20200828T150842Z
UID:10006453-1601549100-1601552700@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Predicting Properties of Structurally and Chemically Complex Materials using Physics-informed Statistical Learning"
DESCRIPTION:To apply statistics and data science tools to aid computational designs of materials is under fast development. There are two unique aspects of the applications of these tools in materials science. First\, the training sets are usually small. Second\, physical mechanisms of material properties can be applied to facilitate the constructions of descriptors and statistics learning methods. In this talk\, I will give three examples to address these two issues. The first example is to use machine learning to predict density and elastic moduli of SiO2-based glasses. Our machine learning approach relies on a training set generated by high-throughput atomistic simulations and a set of elaborately constructed descriptors with the fundamental physics of interatomic bonding. The predictions of our model are comprehensively compared and validated with a large amount of both simulation and experimental data. In the second example\, a general linear correlation can be found between two descriptors of local electronic structures at defects in pure metals and the solute-defect interaction energies in binary alloys of refractory metals with transition-metal substitutional solutes. This linear correlation plus a residual-corrected regression model provides quantitative and efficient predictions on the solute-defect interactions in alloys. In addition\, with these local/global electronic descriptors and a simple bond-counting model\, we developed regression models to accurately and efficiently predict the unstable stacking fault energy (γusf) and surface energy (γsurf) for refractory multicomponent alloys. Using the regression models\, we performed a systematic screening of γusf\, γsurf\, and their ratio in the high-order multicomponent systems to search for alloy candidates that may have enhanced strength-ductile synergies. First-principles calculations also confirmed search results.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-predicting-properties-of-structurally-and-chemically-complex-materials-using-physics-informed-statistical-learning/
LOCATION:PA
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201001T150000
DTEND;TZID=America/New_York:20201001T160000
DTSTAMP:20260407T192134
CREATED:20200814T180447Z
LAST-MODIFIED:20200814T180447Z
UID:10006445-1601564400-1601568000@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Predicting the effects of engineering immune cells using systems biology modeling" (Stacey Finley)
DESCRIPTION:This event will be held virtually on zoom. Check your email for the link and passcode or contact ksas@seas.upenn.edu. \nSystems biology approaches\, including computational models\, provide a framework to test biological hypotheses and optimize effective therapeutic strategies to treat human diseases. In this talk\, I present recent work in modeling signaling in cancer-targeting immune cells\, including CAR T cells at Natural Killer cells. Chimeric antigen receptors (CARs) are comprised of a variety of different activating domains and co-stimulatory domains that initiate signaling required for T cell activation. There is a lack of understanding of the mechanisms by which activation occurs. We apply mathematical modeling to investigate how CAR structure influences downstream T cell signaling and develop new hypotheses for the optimal design of CAR-engineered T cell systems. Natural Killer cells also provide a useful platform for targeting cancer cells. However\, NK cells have been shown to exhibit reduced killing ability with prolonged stimulation by cancer cells. We use a combination of mechanistic model\, optimal control theory and in silico synthetic biology to investigate strategies to enhance NK cell-mediated killing.
URL:https://seasevents.nmsdev7.com/event/be-seminar-stacey-finley/
LOCATION:PA
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201002T100000
DTEND;TZID=America/New_York:20201002T110000
DTSTAMP:20260407T192134
CREATED:20200924T191009Z
LAST-MODIFIED:20200924T191009Z
UID:10006513-1601632800-1601636400@seasevents.nmsdev7.com
SUMMARY:SIG Seminar:"Differentiable Machine Learning in Deformable Simulation"
DESCRIPTION:Using the digital computer to simulate dynamic behavior of elastic and soft objects is a highly desired feature in many scientific and engineering areas: in computer animation\, it provides realistic effects of soft characters; in surgical simulation\, it delivers vivid visual experiences to the trainee; in digital fabrication\, it couples geometry design and mechanical analysis. While the basic computation model has been well established\, robustly simulating nonlinear and detailed elastic models remains an open problem\, and significant implementation and computation efforts are needed. In this talk\, I will share several new perspectives to tackle those classic yet challenging computation problem. We leverage deep neural nets mapping linear and nonlinear models by carefully crafting informative context features. This framework is called NNWarp. NNWarp is probably the first neural network based deformable simulator. With it\, we obtain nonlinear simulations via solving a fixed linear system (so the complexity is lowed by an order). More importantly\, NNWarp is highly re-usable. The resulting net trained for a rectangular beam can be directly used to simulate a swaying maple tree or a soft Armadillo. To relieve the implementation efforts\, we lift the simulation from high-dimension real domain to high-dimension complex domain. By doing so\, we generalize classic Taylor theory to a new set of equations for numerical differentiation. Unlike classic finite difference method\, this complex-step finite difference method does not suffer with subtractive cancellation issues\, making the implementation joyful\, relaxing and as accurate as using the analytic differentiation. In our recently work\, it is also used for training deep neural works. This is the first true second-order neural network training algorithm that has strong quadratic convergency in various classic network architectures.
URL:https://seasevents.nmsdev7.com/event/sig-seminardifferentiable-machine-learning-in-deformable-simulation/
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:20201002T140000
DTEND;TZID=America/New_York:20201002T150000
DTSTAMP:20260407T192134
CREATED:20200914T132816Z
LAST-MODIFIED:20200914T132816Z
UID:10006491-1601647200-1601650800@seasevents.nmsdev7.com
SUMMARY:PICS Seminar: "Fusing machine learning and atomistic simulations for materials design"
DESCRIPTION:Data-driven approaches match or outperform humans at a number of tasks\, including pattern recognition in images and text or planning and strategy in rule-based games. The application of machine learning techniques is also promising for accelerating materials design. However\, experimental data for training is typically scarce and sparse. The interplay between physics-based simulations and data-driven models is particularly advantageous. It allows relying on transferable laws rather than only fitting data in a black box fashion. Meanwhile\, learning from data\nprovides a unique opportunity to parameterize and augment physics-based models\, or completely replace them. \nModels can be built that map the structure and composition of materials to their properties. With such models\, it is\nthen possible to rapidly screen libraries of candidate materials for a desired application before going to the lab. Generative models go one step further and allow tackling the inverse problem: given the desired property\, automatically suggesting a new optimal material that achieves it. \nHow to represent matter so that it can be read into or written by a computer program is key for these coupled tasks of property prediction and materials optimization. Strategies are needed to represent materials in a machine-readable way that is data-efficient\, expressive\, respectful of physical invariants and\, ideally\, invertible. \nHere\, we will discuss our current efforts in building bottom-up atom-level representations for materials design. These include variational autoencoders for dimensionality reduction and inverse design in molecules and polymers\,\nrepresentation and unsupervised learning for graphs and sequences in crystals and polymers\, generative models to\naccelerate Monte Carlo simulations of alloy phase diagrams or end-to-end differentiable simulations. \n 
URL:https://seasevents.nmsdev7.com/event/pics-seminar-fusing-machine-learning-and-atomistic-simulations-for-materials-design/
LOCATION:Zoom – email kathom@seas.upenn.edu
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201005T120000
DTEND;TZID=America/New_York:20201005T130000
DTSTAMP:20260407T192134
CREATED:20200908T165205Z
LAST-MODIFIED:20200908T165205Z
UID:10006476-1601899200-1601902800@seasevents.nmsdev7.com
SUMMARY:PSOC Webinar: "The DNA Damageome and Cancer" (Susan Rosenberg)
DESCRIPTION:“The DNA Damageome and Cancer” \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-the-dna-damageome-and-cancer-susan-rosenberg/
LOCATION:PA
CATEGORIES:Seminar
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201006T090000
DTEND;TZID=America/New_York:20201006T100000
DTSTAMP:20260407T192134
CREATED:20200925T180645Z
LAST-MODIFIED:20200925T180645Z
UID:10006515-1601974800-1601978400@seasevents.nmsdev7.com
SUMMARY:MEAM PhD Thesis Defense: "Delivering Expressive and Personalized Fingertip Tactile Cues"
DESCRIPTION:Wearable haptic devices have seen growing interest in recent years\, but providing realistic tactile feedback is not a challenge that is soon to be solved. Daily interactions with physical objects elicit complex sensations at the fingertips. Furthermore\, human fingertips exhibit a broad range of physical dimensions and perceptive abilities\, adding increased complexity to the task of simulating haptic interactions in a compelling manner. However\, as the applications of wearable haptic feedback grow\, concerns of wearability and generalizability often persuade tactile device designers to simplify the complexities associated with rendering realistic haptic sensations. As such\, wearable devices tend to be optimized for particular uses and average users\, rendering only the most salient dimensions of tactile feedback for a given task and assuming all users interpret the feedback in a similar fashion. We propose that providing more realistic haptic feedback will require in-depth examinations of higher-dimensional tactile cues and personalization of these cues for individual users. In this thesis\, we aim to provide hardware and software-based solutions for rendering more expressive and personalized tactile cues to the fingertip. \nWe first explore the idea of rendering six-degree-of-freedom (6-DOF) tactile fingertip feedback via a wearable device\, such that any possible fingertip interaction with a flat surface can be simulated. We highlight the potential of parallel continuum manipulators (PCMs) to meet the requirements of such a device\, and we refine the design of a PCM for providing fingertip tactile cues. We construct a manually actuated prototype to validate the concept\, and then continue to develop a motorized version\, named the Fingertip Puppeteer\, or Fuppeteer for short. Various error reduction techniques are presented\, and the resulting device is evaluated by analyzing system responses to step inputs\, measuring forces rendered to a biomimetic finger sensor\, and comparing intended sensations to perceived sensations of twenty-four participants in a human-subject study. \nOnce the functionality of the Fuppeteer is validated\, we begin to explore how the device can be used to broaden our understanding of higher-dimensional tactile feedback. One such application is using the 6-DOF device to simulate different lower-dimensional devices. We evaluate 1-\, 3-\, and 6-DOF tactile feedback during shape discrimination and mass discrimination in a virtual environment\, also comparing to interactions with real objects. Results from 20 naive study participants show that higher-dimensional tactile feedback may indeed allow completion of a wider range of virtual tasks\, but that feedback dimensionality surprisingly does not greatly affect the exploratory techniques employed by the user. \nTo address alternative approaches to improving tactile rendering in scenarios where low-dimensional tactile feedback is appropriate\, we then explore the idea of personalizing feedback for a particular user. We present two software-based approaches to personalize an existing data-driven haptic rendering algorithm for fingertips of different sizes. We evaluate our algorithms in the rendering of pre-recorded tactile sensations onto rubber casts of six different fingertips as well as onto the real fingertips of 13 human participants\, all via a 3-DOF wearable device. Results show that both personalization approaches significantly reduced force error magnitudes and improved realism ratings.
URL:https://seasevents.nmsdev7.com/event/meam-phd-thesis-defense-delivering-expressive-and-personalized-fingertip-tactile-cues/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
CATEGORIES:Seminar,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201006T103000
DTEND;TZID=America/New_York:20201006T120000
DTSTAMP:20260407T192134
CREATED:20200911T213458Z
LAST-MODIFIED:20200911T213458Z
UID:10006490-1601980200-1601985600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Operator Inference: Bridging Model Reduction and Scientific Machine Learning"
DESCRIPTION:Model reduction methods have grown from the computational science community\, with a focus on reducing high-dimensional models that arise from physics-based modeling\, whereas machine learning has grown from the computer science community\, with a focus on creating expressive models from black-box data streams. Yet recent years have seen an increased blending of the two perspectives and a recognition of the associated opportunities. This talk presents our work in operator inference\, where we learn effective reduced-order operators directly from data. The physical governing equations define the form of the model we should seek to learn. Thus\, rather than learn a generic approximation with weak enforcement of the physics\, we learn low-dimensional operators whose structure is defined by the physics. This perspective provides new opportunities to learn from data through the lens of physics-based models and contributes to the foundations of Scientific Machine Learning\, yielding a new class of flexible data-driven methods that support high-consequence decision-making under uncertainty for physical systems.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-operator-inference-bridging-model-reduction-and-scientific-machine-learning/
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:20201006T110000
DTEND;TZID=America/New_York:20201006T120000
DTSTAMP:20260407T192134
CREATED:20200918T010946Z
LAST-MODIFIED:20200918T010946Z
UID:10006507-1601982000-1601985600@seasevents.nmsdev7.com
SUMMARY:ESE Grace Hopper Lecture: "Emerging Non-Volatile Ferroelectric Memory"
DESCRIPTION:Abstract\nThe last decade has seen a remarkable shift in usage and value of semiconductor memory technologies. These changes are driven by the elevation of four particular target applications –(1) mobile multi-media applications\, (2) explosive growth in the sheer volume of data that is being created and stored\, (3) emphasis from the individual components to the configurability in high-volume subsystems and (4) applications in brain inspired artificial intelligence systems. \nThe dominating memory technologies in the industry have been SRAM\, DRAM (volatile) and NAND flash (non-volatile). Storage class memory (SCM) describes a device category that combines the benefits of solid-state memory with the archival capabilities and low cost per bit of conventional hard disk magnetic storage. In the past decade\, significant focus has been put on the emerging memory technologies that include: MRAM (Magnetic RAM)\, STTRAM (Spin-Transfer Torque RAM)\, FeRAM (Ferroelectric RAM)\, PCRAM (Phase Change RAM)\, RRAM (Resistive RAM) and Memristor. \nThe invention of ferroelectricity in doped hafnium based oxides (HfZrO2\, doped HfO2) has attracted tremendous interest in realizing HfO 2  based devices.  They have large remnant polarization of up to 45 μC cm −2 \, and their coercive field (≈1–2 MV cm −1 ) is larger than conventional ferroelectric films by approximately one order of magnitude. Furthermore\, they can be extremely thin (<10 nm) and have a large bandgap (>5 eV).  The primary devices aimed in these applications are ferroelectric field effect transistors (FeFETs) and ferroelectric tunnel junctions (FTJs).  In FeFETs\, the conventional logic gate dielectric is replaced with a ferroelectric material that remembers the electric field to which it had been exposed resulting in the threshold voltage of two stable binary states similar to the way it is done in a flash memory cell. \nWe are aiming at developing a fabrication platform that will allow fabrication of n and p channel FeFETs and FTJ based circuits using standard CMOS process on 150 mm wafers in a university environment.  We observe FeFETs exhibiting charge trapping and polarization induced memory window. The process developed for fabricating 1T1R FTJ array integrated with NMOS will be described. FTJs are promising candidates for synaptic weight elements in neural network hardware because of their nonvolatile multilevel memory effect. The talk will provide an overview of advances made in various memory technologies with their future trends.
URL:https://seasevents.nmsdev7.com/event/ese-grace-hopper-lecture-santosh-kurinec/
LOCATION:Zoom – Email ESE for Link jbatter@seas.upenn.edu
CATEGORIES:Distinguished Lecture,Faculty,Colloquium,Graduate,Undergraduate
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201006T150000
DTEND;TZID=America/New_York:20201006T160000
DTSTAMP:20260407T192134
CREATED:20201001T191507Z
LAST-MODIFIED:20201001T191507Z
UID:10006518-1601996400-1602000000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar:"Language\, Brain\, and Computation"
DESCRIPTION:How does the brain beget the mind?  How do molecules\, cells and synapses effect reasoning\, intelligence\, language?   Despite dazzling progress in experimental neuroscience\, as well as in cognitive science at the other extreme of scale\, we do not seem to be making progress in the overarching question — the gap is huge and a completely new approach seems to be required.  As Richard Axel recently put it:  “We don’t have a logic for the transformation of neural activity into thought […].” \nWhat kind of formal system would qualify as this “logic”? \nI will introduce the Assembly Calculus\, a computational system whose basic data structure is the assembly — assemblies are large populations of neurons representing concepts\, words\, thoughts\, etc. –\, and which is informed by recent progress in understanding how language happens in the brain.
URL:https://seasevents.nmsdev7.com/event/cis-seminarlanguage-brain-and-computation/
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:20201008T104500
DTEND;TZID=America/New_York:20201008T114500
DTSTAMP:20260407T192134
CREATED:20200828T152406Z
LAST-MODIFIED:20200828T152406Z
UID:10006454-1602153900-1602157500@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Characterization of Complex Eutectic Microstructures"
DESCRIPTION:Eutectic phase transitions play an important role in many engineering materials\, from cast iron to electronic solder. Regular binary eutectics are relatively straightforward and generally well understood\, but the additional degree of freedom in three-component alloys introduces a far greater level of complexity\, as three solid phases can form simultaneously from the melt. These ternary eutectic structures show promise for creating materials with unique optical and electronic properties\, and are also useful for understanding the factors that control multi-phase\, multi-component solidification more generally. The fundamentals of higher-order eutectics will be explained\, before describing recent experimental and simulation work primarily on the model system of Al-Ag-Cu. By directional solidification at relatively low velocities and thermal gradients\, ternary microstructures with varying degrees of alignment were produced and studied. These microstructures will be discussed both qualitatively and quantitatively\, along with the role of diffusion\, interfacial energy and crystal structure in their formation.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-characterization-of-complex-eutectic-microstructures/
LOCATION:PA
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201008T140000
DTEND;TZID=America/New_York:20201008T150000
DTSTAMP:20260407T192134
CREATED:20200710T163320Z
LAST-MODIFIED:20200710T163320Z
UID:10006443-1602165600-1602169200@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Imaging and sequencing single cells" (Aaron Streets)
DESCRIPTION:This event will be held virtually on zoom. Check your email for the link and passcode or contact ksas@seas.upenn.edu. \nRecent advances in microfluidics and high-throughput sequencing technology have enabled rapid profiling of genomic material in single cells. Valve- and droplet-based microfluidic platforms can precisely and efficiently manipulate\, sort\, and process cells to generate indexed sequencing libraries\, allowing for high-throughput single-cell analysis of the genome\, transcriptome\, proteome\, and epigenome. Such technology has been instrumental in the global effort to create a human cell atlas\, with the ambitious goal of identifying and cataloging all human cell types and cell states in health and disease. However\, not all cell phenotypes are directly encoded in the genome and high-throughput sequencing cannot probe the full space of cellular identity. Therefore\, microscopy remains one of the most powerful and versatile tools for characterizing cells. Fluorescent imaging and quantitative non-linear optical imaging can reveal morphological characteristics\, protein localization\, chromatin organization\, and chemical composition in single cells.  Both single-cell genomics and microscopy can uncover heterogeneity in cellular populations that would otherwise be obscured in ensemble measurement. In this talk\, I will discuss a suite of new microfluidic platforms for coupling genomic measurements and optical measurements of the same single cell\, and some novel computational approaches to grapple with these new datasets. With a combination of new hardware and software\, our goal is to converge on a quantitative and comprehensive understanding of cellular identity.
URL:https://seasevents.nmsdev7.com/event/be-seminar-5/
LOCATION:PA
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201009T100000
DTEND;TZID=America/New_York:20201009T110000
DTSTAMP:20260407T192134
CREATED:20201015T184140Z
LAST-MODIFIED:20201015T184140Z
UID:10006525-1602237600-1602241200@seasevents.nmsdev7.com
SUMMARY:SIG Seminar: “A History of Crowd Simulation and Rendering at Pixar”
DESCRIPTION:This talk will cover how Pixar’s crowds pipeline evolved from “A Bug’s Life” to “Onward”\, and how the studio’s artists and engineers refined and re-invented their tools over the years to create memorable animated crowd scenes.  We’ll cover the progression from finite state machine control\, to agent based crowd simulation\, to sketch based workflows\, using case studies from Pixar’s feature films.
URL:https://seasevents.nmsdev7.com/event/sig-seminar-a-history-of-crowd-simulation-and-rendering-at-pixar/
LOCATION:PA
END:VEVENT
END:VCALENDAR