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DTSTART;TZID=America/New_York:20220301T100000
DTEND;TZID=America/New_York:20220301T113000
DTSTAMP:20260406T033636
CREATED:20220211T142802Z
LAST-MODIFIED:20220211T142802Z
UID:10007083-1646128800-1646134200@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Unknown Unknowns in Designing Porous Intercalation Electrodes for Batteries"
DESCRIPTION:Many batteries\, including the state-of-the-art Lithium-ion technology\, use porous intercalation electrodes. In such electrodes\, energy is stored in the form of ions intercalating in particles. The conventional approach to designing such electrodes relies on using the porous electrode theory to upscale particle-scale behavior to the electrode-scale response. In this talk\, I will discuss unusual material effects that obfuscate such a connection and can considerably change the design guidelines. Understanding these effects is critical to building lithium-ion batteries for new applications like extreme fast charging and electric flight as well as enabling batteries with new intercalation hosts.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-unknown-unknowns-in-designing-porous-intercalation-electrodes-for-batteries/
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:20220301T110000
DTEND;TZID=America/New_York:20220301T120000
DTSTAMP:20260406T033636
CREATED:20220223T141705Z
LAST-MODIFIED:20220223T141705Z
UID:10007100-1646132400-1646136000@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Bridging Safety and Learning in Human-Robot Interaction"
DESCRIPTION:From autonomous cars in cities to mobile manipulators at home\, robots must interact with people. What makes this hard is that human behavior—especially when interacting with other agents—is vastly complex\, varying between individuals\, environments\, and over time. Thus\, robots rely on data and machine learning throughout the design process and during deployment to build and refine models of humans. However\, by blindly trusting their data-driven human models\, today’s robots confidently plan unsafe behaviors around people\, resulting in anything from miscoordination to dangerous collisions. \nMy research aims to ensure safety in human-robot interaction\, particularly when robots learn from and about people. In this talk\, I will discuss how treating robot learning algorithms as dynamical systems driven by human data enables safe human-robot interaction. I will first introduce a Bayesian monitor which infers online if the robot’s learned human model can evolve to well-explain observed human data. I will then discuss how a novel\, control-theoretic problem formulation enables us to formally quantify what the robot could learn online from human data and how quickly it could learn it. Coupling these ideas with robot motion planning algorithms\, I will demonstrate how robots can safely and automatically adapt their behavior based on how trustworthy their learned human models are. I will end this talk by taking a step back and raising the question: “What is the ‘right’ notion of safety when robots interact with people?” and discussing opportunities for how rethinking our notions of safety can capture more subtle aspects of human-robot interaction.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-bridging-safety-and-learning-in-human-robot-interaction/
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:20220301T153000
DTEND;TZID=America/New_York:20220301T163000
DTSTAMP:20260406T033636
CREATED:20220217T010143Z
LAST-MODIFIED:20220217T010143Z
UID:10007088-1646148600-1646152200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Neural Representation and Rendering of 3D Real-world Scenes"
DESCRIPTION:High-quality reconstruction and photo-realistic rendering of real-world scenes are two important tasks that have a wide range of applications in AR/VR\, movie production\, games\, and robotics. These tasks are challenging because real-world scenes contain complex phenomena\, such as occlusions\, motions and interactions. Approaching these tasks using classical computer graphics techniques is a highly difficult and time-consuming process\, which requires complicated capture procedures\, manual intervention\, and a sophisticated global illumination rendering process. In this talk\, I will introduce our recent work that integrates deep learning techniques into the classical graphics pipeline for modelling humans and static scenes in an automatic way. Specifically\, I will talk about creating photo-realistic animatable human characters from only RGB videos\, high-quality reconstruction and fast novel view synthesis of general static scenes from RGB image inputs\, and scene generation with a 3D generative model. Finally\, I will discuss challenges and opportunities in this area for future work.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-neural-representation-and-rendering-of-3d-real-world-scenes/
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:20220302T150000
DTEND;TZID=America/New_York:20220302T160000
DTSTAMP:20260406T033636
CREATED:20220301T164637Z
LAST-MODIFIED:20220301T164637Z
UID:10007106-1646233200-1646236800@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Ted Xiao\, Robotics at Google\, "A Panorama of End-to-end Robot Learning"
DESCRIPTION:In recent years\, a variety of approaches to robotic control have gained popularity as robots play an increasingly larger role in our everyday lives. In this talk I will give an introduction to modern-day robot learning\, covering engineering and research challenges. After establishing the foundations of popular methods\, I will present why I believe that end-to-end Machine Learning is the scalable approach for solving robotics problems. Finally\, I will talk about some interesting open problems and how data-driven methods can learn efficiently in the real world on a large set of tasks with less supervision.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-ted-xiao-university-of-california-berkeley-a-panorama-of-end-to-end-robot-learning/
LOCATION:Levine 512
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220302T153000
DTEND;TZID=America/New_York:20220302T163000
DTSTAMP:20260406T033636
CREATED:20220114T040056Z
LAST-MODIFIED:20220114T040056Z
UID:10007014-1646235000-1646238600@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Spying on Sugar Transporters: Kinetic Studies of Biomolecular Sensors"
DESCRIPTION:Abstract \nThe allocation of sugars from photosynthetic leaves to storage tissues in seeds\, fruits\, and tubers is an essential determinant of crop yields. In plants\, transporters play critical roles in allocating carbon to different organs. Transgenic modifications of plant membrane transporters have been shown to enhance crop yield and increase plants’ resistance to biotic and abiotic stresses. Yet\, quantitative\, systems-level models to support this effort are lacking. \nRecently\, biosensors gained traction for collecting spatio-temporally resolved information on cell physiology and to validate computational models. In this talk\, we report the design and use of genetically encoded biosensors to measure the activity of SWEETs\, the only known family of sugar transporters that facilitate the cellular release of sugar in plants. We created a SweetTrac sensor by inserting circularly-permutated GFP into a SWEET transporter\, resulting in a chimera that translate substrate-triggered conformational rearrangements during the transport cycle into detectable changes in fluorescence intensity. We demonstrate that a combination of cell sorting and bioinformatics can be applied as a general approach to accelerate the design of biosensors for in vivo biochemistry. \nFinally\, mass action kinetics analysis of the sensor’s response suggests that SWEETs are low-affinity\, near-symmetric transporters that can rapidly equilibrate intra- and extracellular concentrations of sugars. These types of models provide new insight into the working of sugar transporters and can help realize multiscale\, dynamic simulations of metabolite allocation to guide crop improvement.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-spying-on-sugar-transporters-kinetic-studies-of-biomolecular-sensors/
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:20220302T163000
DTEND;TZID=America/New_York:20220302T163000
DTSTAMP:20260406T033636
CREATED:20220211T021334Z
LAST-MODIFIED:20220211T021334Z
UID:10007081-1646238600-1646238600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Theoretical Foundations of Pre-trained Models"
DESCRIPTION:A pre-trained model refers to any model trained on broad data at scale and can be adapted (e.g.\, fine-tuned) to a wide range of downstream tasks. The rise of pre-trained models (e.g.\, BERT\, GPT-3\, CLIP\, Codex\, MAE) transforms applications in various domains and aligns with how humans learn. Humans and animals first establish their concepts or impressions from different data domains and data modalities. The learned concepts then help them learn specific tasks with minimal external instructions. Accordingly\, we argue that a pre-trained model follows a similar procedure through the lens of deep representation learning. 1) Learn a data representation that filters out irrelevant information from the training tasks; 2) Transfer the data representation to downstream tasks with few labeled samples and simple models.\nThis talk establishes some theoretical understanding for pre-trained models under different settings\, ranging from supervised pretraining\, meta-learning\, and self-supervised learning to domain adaptation or domain generalization. I will discuss the sufficient (and sometimes necessary) conditions for pre-trained models to work based on the statistical relation between training and downstream tasks. The theoretical analyses partly answer how they work\, when they fail\, guide technical decisions for future work\, and inspire new methods in pre-trained models.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-theoretical-foundations-of-pre-trained-models/
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:20220303T110000
DTEND;TZID=America/New_York:20220303T120000
DTSTAMP:20260406T033636
CREATED:20220223T151151Z
LAST-MODIFIED:20220223T151151Z
UID:10007101-1646305200-1646308800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Learning to Interact With the World: When Generality Meets Precision"
DESCRIPTION:Robotics stands as one of the most impactful and promising endeavors of our times. Learning to interact with the world is fundamental for solving some of our most pressing societal challenges: from taking care of our aging population and aiding with labor-intensive jobs to assisting in climate-related disasters and rescue emergencies. In this talk\, I will argue that such a level of autonomy and performance requires robots that can excel across diverse settings while remaining accurate and reliable. \nMy talk will focus on how we can develop learning algorithms that foster robotic generalization while ensuring the desired task performance. First\, I will present a learning approach to pose estimation for novel objects based on visuo-tactile sensing that doesn’t rely on real data and results in accurate pose distributions. Then\, I will demonstrate how this approach enables precise robotic pick-and-place using task-aware grasping. The robotic system reasons over the models for grasping\, planning\, and perception in order to optimize its actions based only on simulated data. In real experiments\, we demonstrate that our approach learned purely in simulation\, allows robots to successfully manipulate new objects and perform highly accurate placements.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-learning-to-interact-with-the-world-when-generality-meets-precision/
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:20220303T153000
DTEND;TZID=America/New_York:20220303T163000
DTSTAMP:20260406T033636
CREATED:20220211T022112Z
LAST-MODIFIED:20220211T022112Z
UID:10007082-1646321400-1646325000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar:"Privacy and Scalability for Decentralized Cryptographic Systems"
DESCRIPTION:Our existing digital infrastructure requires trust in a small number of centralized entities. The poor fault-tolerance and auditability of this architecture has motivated interest in systems like Ethereum that *decentralize trust across many nodes* by having every node re-execute computations to check their correctness. However\, this strategy leads to poor *privacy* and *scalability* guarantees. \nIn this talk\, I will show how to obtain decentralized trust systems that achieve strong privacy and scalability properties by relying on *efficient cryptographic proofs* (zkSNARKs). In particular\, I will present ZEXE\, a system for *decentralized private computation* where all transactions are indistinguishable from one another\, irrespective of the underlying computation. I will then briefly describe a new paradigm for constructing concretely efficient and easy-to-deploy zkSNARKs.
URL:https://seasevents.nmsdev7.com/event/cis-seminarprivacy-and-scalability-for-decentralized-cryptographic-systems/
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:20220304T103000
DTEND;TZID=America/New_York:20220304T114500
DTSTAMP:20260406T033636
CREATED:20220119T201306Z
LAST-MODIFIED:20220119T201306Z
UID:10007027-1646389800-1646394300@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Shai Revzen\, University of Michigan\, Ann Arbor\, “Multi-legged slipping is simpler than you think”
DESCRIPTION: Multi-contact sliding mechanics in general and multilegged slipping in particular have long been considered difficult to model.  As a consequence roboticists have avoided building multilegged systems and designing motion plans which include intentional slipping.  I present a series of experiments and mathematical advances that demonstrate how these problems become easier with more contacts.  These advances have allowed us to create fast learning algorithms that identify highly predictive models for the interaction physics of multi-contact gaits from a few dozen cycles of motion.  The consequences are multifold: gait optimization algorithms for slipping and soft robots\, speeding up simulations from linear to logarithmic dependence in the planning horizon\, a deeper understanding of the relationship between Coulomb and Viscous friction\, and perhaps some tantalizing hints as to the evolutionary origins of animals’ motor control. The work presented was funded by the NSF CMMI 1825918\, ARO W911NF-14-1-0573\, ARO W911NF-17-1-0306\, and the D. Dan and Betty Kahn Michigan-Israel Partnership for Research and Education Autonomous Systems Mega-Project.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-multi-legged-slipping-is-simpler-than-you-think/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220304T140000
DTEND;TZID=America/New_York:20220304T150000
DTSTAMP:20260406T033636
CREATED:20220224T134910Z
LAST-MODIFIED:20220224T134910Z
UID:10007102-1646402400-1646406000@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Mechanics of Polymeric Gels"
DESCRIPTION:This talk discusses recent and ongoing research on the multiphysics response of polymeric gels. A polymeric gel is a polymeric material swollen by a fluid\, and the intake or out-flow causes large deformations. Also\, many gels respond to environmental stimuli such as temperature\, electric and magnetic fields\, pH\, and more. The responsiveness of polymeric gels to environmental stimuli has been widely employed in soft robotics\, and the poten-tial applications of soft robots are vast. The fast emerging development of gel-based soft robots makes understanding the mechanics of this class of material an important task for simulating their operation. \n\nThe talk begins with recent experimental observations on the mechanical behavior of polymeric gels. Then a continuum level model for the coupled deformation-diffusion re- sponse of gels that incorporates anisotropy and inelasticity is summarized. That is followed by model calibration and attempts for validation on relatively simple gels. Numerical sim-ulations are performed to show the behavior of the model\, and qualitative comparisons are made to experiments of a soft robotic gripper. Results show that the behavior of polymeric gels is even more dependent on fluid uptake than previously thought.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-mechanics-of-polymeric-gels/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220307T120000
DTEND;TZID=America/New_York:20220307T130000
DTSTAMP:20260406T033636
CREATED:20220207T143311Z
LAST-MODIFIED:20220207T143311Z
UID:10007067-1646654400-1646658000@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: “Smart Immune Receptor Sequencing in Single Cells" (Michael Malone)
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-smart-immune-receptor-sequencing-in-single-cells-michael-malone/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral,Graduate,Student
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220308T110000
DTEND;TZID=America/New_York:20220308T120000
DTSTAMP:20260406T033636
CREATED:20220302T133953Z
LAST-MODIFIED:20220302T133953Z
UID:10007109-1646737200-1646740800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Dynamics and Control of Quantum Systems"
DESCRIPTION:In practice\, quantum systems of interest are never isolated. The presence of noise or the interaction with an environment can radically change a system’s dynamics\, typically destroying resources such as quantum coherence and entanglement – that is\, destroying the resources that are necessary to benefit from quantum phenomena in applications of quantum science. \nI will present a general framework to study the dynamics of realistic quantum systems from first principles. More specifically\, I will show bounds on the speed with which open-quantum and classical-stochastic systems evolve. In certain regimes\, these bounds correctly capture dynamics in a range of fields\, from quantum and classical thermodynamics to evolutionary biology. \nIn the last part of the talk\, I will introduce a mechanism to control the dynamics of open quantum systems by exploiting measurement feedback from continuous monitoring. I will show how this can\, in turn\, be used to mitigate the effects of the interaction with an environment.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-dynamics-and-control-of-quantum-systems/
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:20220310T110000
DTEND;TZID=America/New_York:20220310T120000
DTSTAMP:20260406T033636
CREATED:20220301T175806Z
LAST-MODIFIED:20220301T175806Z
UID:10007107-1646910000-1646913600@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Quantum Device Benchmarking from Many-Body Quantum Chaos"
DESCRIPTION:Recently\, there has been remarkable progress towards the development of large-scale quantum devices through advances in quantum science and technology. This progress opens new doors for proof-of-principle demonstrations of quantum simulations as well as practically useful applications\, such as quantum-enhanced metrology. However\, these applications require first quantifying how well a quantum device produces a desired target state\, which is currently experimental challenging as existing methods for the quantitative verification of a quantum device require fine-tuned control and substantial experimental resources. In this talk\, I will present a simple and efficient benchmarking protocol to estimate the fidelity of large-scale quantum devices. Our protocol relies only on time evolution of a quantum system undergoing Hamiltonian dynamics\, followed by simple measurements without any sophisticated control and readout. Fundamentally\, this simplification stems from a universal phenomenon associated with many-body chaos from generic\, strongly interacting quantum systems. We demonstrate our benchmarking protocol experimentally for an analog quantum simulator based on a Rydberg atom array\, and numerically for other quantum platforms such as superconducting qubits\, trapped ions\, and itinerant particles in optical lattices.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-quantum-device-benchmarking-from-many-body-quantum-chaos/
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:20220310T153000
DTEND;TZID=America/New_York:20220310T163000
DTSTAMP:20260406T033636
CREATED:20220131T152543Z
LAST-MODIFIED:20220131T152543Z
UID:10007054-1646926200-1646929800@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "The Interface between man and machine | Neural Interfacing for Sensory Feedback and Neuroprosthetic control" (Shriya Srinivasan)
DESCRIPTION:This seminar will be held live and broadcast on zoom – check email for zoom link or contact ksas@seas.upenn.edu. \nDespite immense technological and scientific advancements in prosthetic technologies\, patients rarely use advanced prosthetic devices\, as communicating to these devices is cumbersome and frustrating.  This talk will elucidate new strategies in reconstructive surgical design and neural interfacing that enable amputees to better communicate prostheses as well as receive proprioceptive and cutaneous sensory feedback\, by carefully rewiring mechanoreceptors in the peripheral limbs. Through preclinical and clinical validation\, these interfaces demonstrate restored afferent feedback in the peripheral and central nervous systems\, improved phantom limb sensations\, decreased phantom limb pain and enhanced motor control. Beyond the peripheral limbs\, this talk will explore the neural interfacing of gastric mechanoreceptors through ingestible electronics. These approaches give way to a new design framework that can optimize and eventually dissolve the interface between man and machine.
URL:https://seasevents.nmsdev7.com/event/be-seminar-the-interface-between-man-and-machine-neural-interfacing-for-sensory-feedback-and-neuroprosthetic-control-shriya-srinivasan/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Postdoctoral
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T120000
DTEND;TZID=America/New_York:20220314T130000
DTSTAMP:20260406T033636
CREATED:20220207T143502Z
LAST-MODIFIED:20220207T143502Z
UID:10007068-1647259200-1647262800@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: Christina Hueschen
DESCRIPTION:Physical Sciences in Oncology Center PSOC@Penn \nSpring 2022 Hybrid-Seminar Series \nTowne 225 / Raisler Lounge @ Noon (EST) \nFor Zoom link \, please contact manu@seas.upenn.edu
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-christina-hueschen/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Postdoctoral
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T140000
DTEND;TZID=America/New_York:20220314T160000
DTSTAMP:20260406T033636
CREATED:20220309T192949Z
LAST-MODIFIED:20220309T192949Z
UID:10007115-1647266400-1647273600@seasevents.nmsdev7.com
SUMMARY:CBE PhD Dissertation Defense | "Surface Modification of Solid Oxide Cell Electrodes to Improve the Electrochemical Performance"
DESCRIPTION:Abstract: \n“Solid Oxide Fuel Cells are high temperature\, solid-state\, electrochemical devices that can convert fuels into electricity or produce fuels from excess electricity. Oxygen is reduced at the cathode to oxygen ions which move through the ceramic to the anode. These oxygen ions are used to oxidize fuels at the anode compartment\, producing heat and electrons that will move through an external circuit to produce power.\nAt the cathode the sluggish oxygen reduction kinetics impede the performance of the electrode. A common approach to enhance the cathode performance is infiltration. Often the performance of a cathode is enhanced after the addition of a variety of metal-oxide materials. The common claim is that the infiltrated materials enhance catalytic activity or conductivity. With infiltration however\, it is impossible to control for changes in surface area or conductivity. Atomic Layer Deposition (ALD) was employed to change the surface chemistry of the electrode\, without changing the conductivity\, or surface area of the electrode.\nPerovskite anodes are of interest due to their resistance to many of the issues that plague Ni-cermet (ceramic metal) anode. Their catalytic activity is often lacking\, and as such a variety of methods are employed to enhance this. The most efficient approach is surface modification which allows for increases in activity with minimal metal loadings. ALD was employed to deposit highly disperse oxidation catalysts in order to minimize the metal loadings while maximizing performance. \n\nAt the Ni-cermet anode\, undesirable reactions\, such as carbon fiber formation and Ni oxidation to NiO\, limit the lifetime of the electrode. Surface modification approaches are often employed to protect the Ni surface against these processes. We investigated the use of CeO2 ALD to overcome these challenges. \n\nPerovskites with exclusively 2 + cations (Ba and Sr) in the A-site and Fe in the B-site have recently exhibited great performance as SOFC anodes. The reasoning behind the high catalytic activity of these anodes has not been thoroughly studied. To elucidate the origin of the high activity of these anodes\, the performance and thermodynamics of Ba0.5Sr0.5FeO3 (BSF) anodes was investigated.”
URL:https://seasevents.nmsdev7.com/event/cbe-phd-dissertation-defense-surface-modification-of-solid-oxide-cell-electrodes-to-improve-the-electrochemical-performance/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220314T153000
DTEND;TZID=America/New_York:20220314T163000
DTSTAMP:20260406T033636
CREATED:20220219T204302Z
LAST-MODIFIED:20220219T204302Z
UID:10007091-1647271800-1647275400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Unleashing the Potential of In-Network Computing"
DESCRIPTION:Recent advances in programmable networking hardware create a new computing paradigm called in-network computing. This new paradigm allows functionality that has been served by commodity servers\, ranging from network middleboxes to components of distributed systems\, to be performed in the network. I argue that to fully unleash its potential\, we need resource elasticity and fault resiliency via higher-level abstractions.\n\nIn this talk\, I demonstrate that in-network computing can be elastic and resilient by designing high-level abstractions and runtime systems that enable us to leverage compute and memory resources available outside of a single type of device — e.g.\, programmable switches — while hiding the complexities of dealing with device heterogeneity. I begin by introducing TEA\, a framework that provides elastic memory by enabling memory-intensive in-switch applications\, such as cloud-scale load balancers\, to leverage DRAM on remote servers via virtual table abstraction. Then I present ExoPlane and RedPlane\, frameworks that support evolving in-network computing workloads and requirements — i.e.\, serving multiple concurrent applications and making them fault-tolerant — via infinite switch resource and one big fault-tolerant switch abstractions. Several systems in the industry are now adopting some of the technologies presented in this talk.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-unleashing-the-potential-of-in-network-computing/
LOCATION:Room 307\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220315T153000
DTEND;TZID=America/New_York:20220315T163000
DTSTAMP:20260406T033636
CREATED:20220219T205447Z
LAST-MODIFIED:20220219T205447Z
UID:10007092-1647358200-1647361800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Towards Scalable Representation Learning for Visual Recognition"
DESCRIPTION:A powerful biological and cognitive representation is essential for humans’ remarkable visual recognition abilities. Deep learning has achieved unprecedented success in a variety of domains over the last decade. One major driving force is representation learning\, which is concerned with learning efficient\, accurate\, and robust representations from raw data that are useful for a downstream classifier or predictor. \nA modern deep learning system is composed of two core and often intertwined components: 1) neural network architectures and 2) representation learning algorithms. In this talk\, we will present several studies in both directions. On the neural network modeling side\, we will examine modern network design principles and how they affect the scaling behavior of ConvNets and recent Vision Transformers. Additionally\, we will demonstrate how we can acquire a better understanding of neural network connectivity patterns through the lens of random graphs. In terms of representation learning algorithms\, we will discuss our recent efforts to move beyond the traditional supervised learning paradigm and demonstrate how self-supervised visual representation learning\, which does not require human annotated labels\, can outperform its supervised learning counterpart across a variety of visual recognition tasks. The talk will encompass a variety of vision application domains and modalities (e.g. 2D images and 3D scenes). The goal is to show existing connections between the techniques specialized for different input modalities and provide some insights about diverse challenges that each modality presents. Finally\, we will discuss several pressing challenges and opportunities that the “big model era’’ raises for computer vision research.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-towards-scalable-representation-learning-for-visual-recognition/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220316T110000
DTEND;TZID=America/New_York:20220316T120000
DTSTAMP:20260406T033636
CREATED:20220110T152626Z
LAST-MODIFIED:20220110T152626Z
UID:10007002-1647428400-1647432000@seasevents.nmsdev7.com
SUMMARY:CEMB Future Leaders: "Multiscale computational modeling of vascular adaptation and homeostasis"
DESCRIPTION:Launched in May 2021\, the Future Leaders in Mechanobiology is a monthly seminar series featuring up-and-coming leaders in mechanobiology–PhD students and postdocs from a wide range of fields\, backgrounds\, and institutions. By providing an international stage to share one’s work and opportunities to interact with researchers at all career stages\, we aim to create an inclusive and valuable series for early-stage researchers and the mechanobiology community as a whole. \nRegister HERE for access to the Zoom link and visit the CEMB website for more information.
URL:https://seasevents.nmsdev7.com/event/cemb-future-leaders-multiscale-computational-modeling-of-vascular-adaptation-and-homeostasis/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="Center for Engineering MechanoBiology (CEMB)":MAILTO:annjeong@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220316T110000
DTEND;TZID=America/New_York:20220316T120000
DTSTAMP:20260406T033636
CREATED:20220219T213104Z
LAST-MODIFIED:20220219T213104Z
UID:10007093-1647428400-1647432000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Statistical Machine learning for genetics and health: multi-modality\, interpretability\, mechanism"
DESCRIPTION:Genomic and medical data are available at unprecedented scales. This is due\, in part\, to improvements and developments in data collection\, high throughput sequencing\, and imaging technologies. How can we extract lower dimensional representations from these high dimensional data in a way that retains fundamental biological properties across different scales? Three main challenges arise in this context: how to aggregate information across different experimental modalities\, how to enforce that such representations are interpretable\, and how to leverage prior dynamical knowledge to provide new insight into mechanism. I will present my work on developing statistical machine learning models and algorithms to answer this question and address these challenges. First\, I will present a generative model for learning representations that jointly model information from gene expression and tissue morphology in a population setting. Then\, I will describe a method for making multi-modal representations interpretable using a label-aware compressive classification approach for gene panel selection in single cell data. Finally\, I will discuss inference methods for models which encode mechanistic assumptions\, a need that arises naturally in gene regulatory networks\, predator-prey systems\, and electronic health care records. Throughout this work\, recent advances in machine learning and statistics are harnessed to bridge two worlds — the world of real\, messy biological data and that of methodology and computation. This talk describes the importance of domain knowledge and data-centric modeling in motivating new statistical venues and introduces new ideas that touch upon improving experimental design in biomedical contexts.
URL:https://seasevents.nmsdev7.com/event/6397/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220316T150000
DTEND;TZID=America/New_York:20220316T160000
DTSTAMP:20260406T033636
CREATED:20220225T175024Z
LAST-MODIFIED:20220225T175024Z
UID:10007103-1647442800-1647446400@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Shuran Song\, Columbia University\, “The Reasonable Effectiveness of Dynamic Manipulation for Deformable Objects”
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nFrom unfurling a blanket to swinging a rope; high-velocity dynamic actions play a crucial role in how people interact with deformable objects. In this talk\, I will discuss how we can get robots to learn to dynamically manipulate deformable objects\, where we embrace high-velocity dynamics rather than avoid them (e.g.\, exclusively using slow pick and place actions). With robots that can fling\, swing\, or blow with air\, our experiments show that these interactions are surprisingly effective for many classically hard manipulation problems and enable new robot capabilities.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-shuran-song-columbia-university-the-reasonable-effectiveness-of-dynamic-manipulation-for-deformable-objects/
LOCATION:Levine 512
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220317T110000
DTEND;TZID=America/New_York:20220317T120000
DTSTAMP:20260406T033636
CREATED:20220311T213813Z
LAST-MODIFIED:20220311T213813Z
UID:10007118-1647514800-1647518400@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Surpassing Fundamental Limits through Time Varying Electromagnetics"
DESCRIPTION:Surpassing the fundamental limits that govern all electromagnetic structures\, such as reciprocity and the delay-bandwidth-size limit\, will have a transformative impact on all applications based on electromagnetic circuits and systems. For instance\, violating principles of reciprocity enables non-reciprocal components such as isolators and circulators\, which find application in full-duplex wireless radios\, radar\, bio-medical imaging\, and quantum computing systems. Overcoming the delay-bandwidth-size limit enables ultra-broadband yet extremely-compact devices whose size is not fundamentally related to the wavelength at the operating frequency. \nThe focus of my talk will be on using time-variance as a new toolbox to overcome these fundamental limits and re-imagine circuit design. Specifically\, I will focus on CMOS-integrated time-varying circuits and systems that have enabled: (i) integrated non-reciprocal components operating across frequencies ranging from RF to millimeter waves with multi-watt power handling\, (ii) reconfigurable microwave passive components with 100-1000× form-factor reduction\, (iii) integrated full-duplex wireless radios with wideband self-interference cancellation\, and (iv) the first non-reciprocal Floquet electromagnetic topological insulator with an ultra-wide bandgap. Our prototypes achieve the stringent performance envelopes that are required by practical wireless applications\, thus bringing the fields of integrated non-reciprocity and synthetic topological insulators to real-world applications. \nI will also briefly cover my future research plans on harmonic-tuned\, higher-order N-path filters and cross-disciplinary collaborative research on using time-varying circuits and CMOS based ICs in cryogenic quantum computing applications.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-surpassing-fundamental-limits-through-time-varying-electromagnetics/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220317T123000
DTEND;TZID=America/New_York:20220317T133000
DTSTAMP:20260406T033636
CREATED:20220311T142141Z
LAST-MODIFIED:20220311T142141Z
UID:10007117-1647520200-1647523800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Forward and Inverse Causal Inference in a Tensor Framework"
DESCRIPTION:Developing causal explanations for correct results or for failures from mathematical equations and data is important in developing a trustworthy artificial intelligence\, and retaining public trust.  Causal explanations are germane to the “right to an explanation” statute\, i.e.\, to data-driven decisions\, such as those that rely on images.  Computer graphics and computer vision problems\, also known as forward and inverse imaging problems\, have been cast as causal inference questions consistent with Donald Rubin’s quantitative definition of causality\, where “A causes B” means “the effect of A is B”\, a measurable and experimentally repeatable quantity. Computer graphics may be viewed as addressing analogous questions to forward causal inference that addresses the “what if” question\, and estimates a change in effects given a delta change in a causal factor. Computer vision may be viewed as addressing analogous questions to inverse causal inference that addresses the “why” question which we define as the estimation of causes given a forward causal model\, and a set of observations that constrain the solution set.  Tensor factor ananlysis also known as structural equations with multimode latent variables is a suitable and transparent framework for modeling the mechanism that generates observed data.  Tensor factor analysis has been employed in representing the causal factor structure of data formation in econometrics\, psychometric\, and chemometrics since the 1960s.  More recently\, tensor factor analysis has been successfully employed to represent cause-and-effect in computer vision\, and computer graphics\, or for prediction and dimensionality reduction in machine learning tasks.   
URL:https://seasevents.nmsdev7.com/event/cis-seminar-forward-and-inverse-causal-inference-in-a-tensor-framework/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220317T153000
DTEND;TZID=America/New_York:20220317T163000
DTSTAMP:20260406T033636
CREATED:20220221T185704Z
LAST-MODIFIED:20220221T185704Z
UID:10007094-1647531000-1647534600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Optimizing CPU Efficiency and Tail Latency in Datacenters"
DESCRIPTION:The slowing of Moore’s Law and increased concerns about the environmental impacts of computing are exerting pressure on datacenter operators to use resources such as CPUs and memory more efficiently. However\, it is difficult to improve efficiency without degrading the performance of applications. \nIn this talk\, I will focus on CPU efficiency and how we can increase efficiency while maintaining low tail latency for applications. The key innovation is to reallocate cores between applications on the same server very quickly\, every few microseconds. First I will describe Shenango\, a system design that makes such frequent core reallocations possible. Then I will show how policy choices for core reallocation and load balancing impact CPU efficiency and tail latency\, and present the policies that yield the best combination of both.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-optimizing-cpu-efficiency-and-tail-latency-in-datacenters/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220318T103000
DTEND;TZID=America/New_York:20220318T114500
DTSTAMP:20260406T033636
CREATED:20220304T180229Z
LAST-MODIFIED:20220304T180229Z
UID:10007112-1647599400-1647603900@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Gregory Hager\, Johns Hopkins University\, “Observing\, Learning and Executing Fine-Grained Manipulation Activities”
DESCRIPTION:This seminar will be held in person in Wu and Chen Auditorium as well as virtually via Zoom. \nIn the domain of image and video analysis\, much of the deep learning revolution has been focused on narrow\, high-level classification tasks that are defined through carefully curated\, retrospective data sets. However\, most real-world applications – particularly those involving complex\, multi-step manipulation activities — occur “in the wild” where there is a combinatorial long tail of unique situations that are never seen during training. These systems demand a richer\, fine-grained task representation that is informed by the application context and which supports quantitative analysis and compositional synthesis. As a result\, the challenges inherent in both high-accuracy\, fine-grained analysis and performance of perception-based activities are manifold\, spanning representation\, recognition\, and task and motion planning. \n  \nThis talk will summarize our work addressing these challenges. I’ll first describe DASZL\, our approach to interpretable\, attribute-based activity detection. DASZL operates in both pre-trained and zero shot settings\, and it has been applied to a variety of applications ranging from surveillance to surgery. I will then describe our recent work on “Good Robot”\, a method for end-to-end training of a robot manipulation system. Good Robot achieves state-of-the-art performance in complex\, multi-step manipulation tasks\, and we show it can be refactored to support both demonstration-driven and language-guided manipulation. I’ll close with a summary of some directions related to these technologies that we are currently exploring.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-gregory-hager-johns-hopkins-university-observing-learning-and-executing-fine-grained-manipulation-activities/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220318T140000
DTEND;TZID=America/New_York:20220318T150000
DTSTAMP:20260406T033636
CREATED:20220214T192105Z
LAST-MODIFIED:20220214T192105Z
UID:10007086-1647612000-1647615600@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Computational Image Analysis For Individualized Surgical Treatment Planning of Bicuspid Aortic Valves"
DESCRIPTION:Abstract: \nThe bicuspid aortic valve (BAV) is a congenital heart defect in which the aortic valve has two cusps rather than three. Moderate to severe aortic regurgitation is the most common complication in young adult BAV patients and requires major\, and often repeated\, surgical intervention. BAV repair is an evolving surgical treatment for aortic regurgitation that preserves native valve tissue and circumvents risks and quality of life concerns associated with conventional aortic valve replacement in young adults. Despite promising clinical studies\, however\, BAV repair remains underutilized and there is substantial variability in surgical planning across institutions. In this talk\, we discuss 3D and 4D computational image analysis methodologies that we are developing to gain new insights into valvular regurgitation and surgical treatment of the disease. These methodologies enable pre-operative visualization of valve morphology and motion\, as well as automated quantification of metrics that are used to decide which surgical strategy is optimal for a patient’s valve. We will discuss how the advancement of image analysis\, applied to modalities such as echocardiography and computed tomography\, provides unique opportunities to standardize the surgical planning process and increase the utilization of repair as an alternative to valve replacement in young adults. \n 
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-computational-image-analysis-for-individualized-surgical-treatment-planning-of-bicuspid-aortic-valves/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220321T103000
DTEND;TZID=America/New_York:20220321T113000
DTSTAMP:20260406T033636
CREATED:20220314T200000Z
LAST-MODIFIED:20220314T200000Z
UID:10007121-1647858600-1647862200@seasevents.nmsdev7.com
SUMMARY:ESE Seminar - "Computing Using Time"
DESCRIPTION:The development of computing systems able to address our ever-increasing needs\, especially as we reach the end of CMOS transistor scaling\, requires truly novel methods of computing. My research draws inspiration from biology\, rethinks the digital/analog boundary\, and challenges conventional wisdom\, which typically guides how we perform computation\, by reimagining the role of time. In this talk\, I firstly introduce a computational temporal logic that sets the foundation for temporal computing. Secondly\, I demonstrate how this foundation opens up unique ways in which we can work with sensors and design machine learning systems. Thirdly\, I describe how temporal operators provide answers to several long-lasting problems in pulse-based computing with emerging devices — specifically\, superconducting. Finally\, I touch upon future work with themes ranging from in-sensor online learning to hybrid quantum-classical computing and formally verifiable hardware.
URL:https://seasevents.nmsdev7.com/event/ese-seminar-computing-using-time/
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:20220321T120000
DTEND;TZID=America/New_York:20220321T130000
DTSTAMP:20260406T033636
CREATED:20220131T131422Z
LAST-MODIFIED:20220131T131422Z
UID:10007047-1647864000-1647867600@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: Cheng Zhu\, PhD
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-cheng-zhu-phd/
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:20220321T153000
DTEND;TZID=America/New_York:20220321T163000
DTSTAMP:20260406T033636
CREATED:20220311T134352Z
LAST-MODIFIED:20220311T134352Z
UID:10007116-1647876600-1647880200@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Fast and Effective Analytics for Big Multi-Dimensional Data"
DESCRIPTION:Today\, automated processes\, Internet‑of‑Things deployments\, and Web and mobile applications generate an overwhelming amount of high‑dimensional data. Meanwhile\, computational resources remain limited\, and advances in machine learning (ML) create a pressing need to support increasingly expensive and complex analytical tasks. Unfortunately\, traditional data management techniques offer limited support for high‑dimensional data\, ML tasks\, and adaptation to data properties\, often resulting in reduced performance. Similarly\, due to the difficulty of providing invariances to specific data distortions\, applications often resort to inadequate ML methods\, reducing their effectiveness. \nIn my work\, I ask how we can address the lack of task‑aware and data‑driven adaptations in data management and ML methods. Specifically\, I will discuss three solutions for (i) data representations and (ii) computational methods using techniques to exploit similarities\, shapes\, densities\, and distributions in data. Motivated by the ubiquity of high-dimensional time series\, I will first present a similarity-preserving representation to minimize storage footprint and accelerate specific ML analytics for time-series data. Then\, I will discuss a variance-aware quantization method for indexing high-dimensional data. Finally\, I will present a method for anomaly detection in streaming data to account for distribution drifts. In all three examples\, the proposed methods substantially improve performance and accuracy\, demonstrating the benefit of designing task-aware and data-driven solutions for large-scale data science applications.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-fast-and-effective-analytics-for-big-multi-dimensional-data/
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:20220322T100000
DTEND;TZID=America/New_York:20220322T113000
DTSTAMP:20260406T033636
CREATED:20220303T174014Z
LAST-MODIFIED:20220303T174014Z
UID:10007110-1647943200-1647948600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Agile Maneuver with Under-Actuated Millirobots"
DESCRIPTION:Decimeter-scale robots can use a wide range of techniques to maneuver in challenging environments in spite of lacking the actuated degrees of freedom typically seen in larger robots. Agile maneuver for these small robots greatly benefits from a high power-to-weight ratio and mechanical design which can exploit environment interactions\, in addition to explicit control strategies. We have found that many aspects of agile behavior can arise from intrinsic mechanics\, which is particularly useful for under-actuated systems. For these systems\, appendages such as claws and tails greatly improve maneuverability. In addition\, cooperative behavior can be used to increase degrees-of-freedom and agility. The smart composite microstructures (SCM) folding fabrication process\, which combines distinct layers for structure and joints\, has led to high power-to-weight and robust millirobots. In the future\, folding fabrication could be incorporated in robot systems to enable in-situ customization or repair.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-agile-maneuver-with-under-actuated-millirobots/
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
END:VCALENDAR