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DTSTART;TZID=America/New_York:20220321T103000
DTEND;TZID=America/New_York:20220321T113000
DTSTAMP:20260406T031531
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:20260406T031531
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:20260406T031531
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:20260406T031531
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
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220322T110000
DTEND;TZID=America/New_York:20220322T120000
DTSTAMP:20260406T031531
CREATED:20220314T191356Z
LAST-MODIFIED:20220314T191356Z
UID:10007120-1647946800-1647950400@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Advancing Precision Medicine and Precision Health with CMOS-enabled Continuous Monitoring of Molecules\, Cells\, and Beyond"
DESCRIPTION:“Continuous” monitoring of specific biomarkers in real-time offers longitudinal information that can enable not only rapid medical decision-making but also early disease detection. As opposed to the current end-point diagnostics approaches\, such a continuous-monitoring capability introduces a new dimension in achieving precision medicine and precision health. In this talk\, I will present my research contributions toward this goal. Specifically\, my research harvests the power of CMOS integrated circuits\, applied physics\, and advanced biotechnology to address biosensing requirements on sensitivity\, specificity\, throughput\, multiplexing\, device miniaturization\, and system scaling. I will focus on two developed technology platforms: (1) an electrochemical-sensing wireless implant for in vivo monitoring of small molecules using reagentless structure-switching “aptamers” and (2) a cytometry-on-CMOS platform for high-throughput studies of the electromagnetic signatures at GHz frequencies. The former has broad applications including precision drug dosing and early disease detection whereas the later has the potentials for sensing circulating-tumor-cells in blood. I will address their critical needs as well as circuits and systems design challenges. I will also present my recent activity in developing high-resolution intraoperative imaging tools\, circuit techniques to overcome density constraints in neural-recording probes\, sensing platform for “distributed” diagnosis\, and low-power heart-rate-sensing wearables.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-advancing-precision-medicine-and-precision-health-with-cmos-enabled-continuous-monitoring-of-molecules-cells-and-beyond/
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:20220322T153000
DTEND;TZID=America/New_York:20220322T163000
DTSTAMP:20260406T031531
CREATED:20220221T190904Z
LAST-MODIFIED:20220221T190904Z
UID:10007095-1647963000-1647966600@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: “Verifiable Machine Learning for Security”
DESCRIPTION:In recent years\, machine learning techniques have been increasingly applied to many critical problems in the cybersecurity domain\, including detecting malware\, spam\, online fraud\, hate speech\, etc. However\, there are many challenges to reliably deploy these solutions for security applications\, since real-world adversaries are constantly trying to evade machine learning systems. My research focuses on solving this problem by increasing the cost for attackers to succeed. \nIn this talk\, I will discuss methods to train security classifiers with verified robustness properties. Robustness properties are security guarantees of the classifier that can eliminate certain classes of evasion attacks. I will show how to use security domain knowledge and economic cost measurement studies to formulate robustness properties to capture general classes of evasion strategies that are inexpensive for attackers. Then\, I will describe new algorithms to train security classifiers to satisfy these properties. I will show how to apply the methods to detect PDF malware\, Twitter spam\, and Cryptojacking\, and demonstrate that it is not only sound but also practical. My key result is\, enforcing robustness properties can increase the economic cost of evasion. In the future\, I want to integrate new machine learning models as a fundamental part to solve hard problems in security.
URL:https://seasevents.nmsdev7.com/event/6412/
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:20220323T150000
DTEND;TZID=America/New_York:20220323T160000
DTSTAMP:20260406T031531
CREATED:20220315T182009Z
LAST-MODIFIED:20220315T182009Z
UID:10007123-1648047600-1648051200@seasevents.nmsdev7.com
SUMMARY:Spring 2022 GRASP SFI: Scott Guan\, Georgia Institute of Technology\, "Toward Scalability in Multi-Agent Decision Making"
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom \nWhile machine learning algorithms have led to tremendous improvements in many multi-agent domains\, scalability remains one of the major challenges for multi-agent decision-making. In this talk\, we will focus on two aspects of the scalability challenge: (i) number of agents\, and (ii) large state space. We will propose possible approaches to remedy both challenges. In the first part\, we introduce the mean-field approximation\, which simplifies the interactions among a large population of agents. We will present theoretical analysis and convergence results on a class of entropy-regularized mean-field games with optimality bounds. In the second part\, we address the large state space issue using two ideas: first\, the use of hierarchical decomposition to decompose the original game to a number of smaller games; and second\, the approximation of expensive operators (e.g.\, minimax) to reduce computation time in multi-agent reinforcement learning. Convergence analysis and application to pursuit-evasion games will also be discussed.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-scott-guan-georgia-institute-of-technology-toward-scalability-in-multi-agent-decision-making/
LOCATION:Levine 512
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220323T153000
DTEND;TZID=America/New_York:20220323T163000
DTSTAMP:20260406T031531
CREATED:20220114T043044Z
LAST-MODIFIED:20220114T043044Z
UID:10007015-1648049400-1648053000@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Too Small is Never Too Small: Utilizing Advanced Path Sampling Techniques to Probe the Kinetics and Mechanism of Rare Events\, From Atmospheric Ice Nucleation to Ion Transport”
DESCRIPTION:Abstract \nMore often than not\, scientists are challenged with the daunting problem of measuring or computing astronomically small quantities that are related to the occurrence of rare events. A phenomenon is called a rare event when the amount of time that elapses before its occurrence is orders of magnitude longer than the time needed for its completion. Rare events are ubiquitous in nature and span a wide range of phenomena such as earthquakes\, telecommunication and power grid failures\, protein folding\, genetic mutations\, and crystallization. Capturing the statistical nature of such events is key in many applications\, including materials synthesis\, climate modeling\, bioengineering and medicine. Unfortunately\, achieving this with conventional experiments or simulations is inefficient at best as the waiting times for observing a single rare event can surpass the experimentally or computationally accessible timescales by several orders of magnitude. This becomes an almost impossible undertaking when the rate of occurrence of a rare event is astronomically small. Under such circumstances\, specialized sampling techniques are necessary for capturing the statistical features of the corresponding rare event. \nThis presentation will be dedicated to showcasing our work on characterizing rare events using an advance sampling technique known as forward flux sampling (FFS)\, alongside a brief discussion of a novel variant of FFS recently developed in my group suited for studying aggregation phenomena such as nucleation. I will\, in particular\, discuss our application of FFS to probe the kinetics and microscopic mechanism of two scientifically and practically important rare events\, namely ice nucleation under atmospherically relevant conditions\, and ion and solute transport through semipermeable nanoporous membranes. An emphasis will be put on not only the ability of FFS to characterize their kinetics\, but also its power to provide molecular insights into the underlying mechanisms of these processes.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-too-small-is-never-too-small-utilizing-advanced-path-sampling-techniques-to-probe-the-kinetics-and-mechanism-of-rare-events-from-atmospheric-ice-nucleation-to-ion-transport/
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:20220323T153000
DTEND;TZID=America/New_York:20220323T163000
DTSTAMP:20260406T031531
CREATED:20220221T191740Z
LAST-MODIFIED:20220221T191740Z
UID:10007096-1648049400-1648053000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Reasoning and Learning in Interactive Natural Language Systems"
DESCRIPTION:Systems that support expressive\, situated natural language interactions are essential for expanding access to complex computing systems\, such as robots and databases\, to non-experts. Reasoning and learning in such natural language interactions is a challenging open problem. For example\, resolving sentence meaning requires reasoning not only about word meaning\, but also about the interaction context\, including the history of the interaction and the situated environment. In addition\, the sequential dynamics that arise between user and system in and across interactions make learning from static data\, i.e.\, supervised data\, both challenging and ineffective. However\, these same interaction dynamics result in ample opportunities for learning from implicit and explicit feedback that arises naturally in the interaction. This lays the foundation for systems that continually learn\, improve\, and adapt their language use through interaction\, without additional annotation effort. In this talk\, I will focus on these challenges and opportunities. First\, I will describe our work on modeling dependencies between language meaning and interaction context when mapping natural language in interaction to executable code. In the second part of the talk\, I will describe our work on language understanding and generation in collaborative environments\, focusing on learning to recover from errors and on continual learning from explicit and implicit user feedback.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-reasoning-and-learning-in-interactive-natural-language-systems/
LOCATION:Room 307\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220324T110000
DTEND;TZID=America/New_York:20220324T120000
DTSTAMP:20260406T031531
CREATED:20220314T200454Z
LAST-MODIFIED:20220314T200454Z
UID:10007122-1648119600-1648123200@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Next Generation Bioelectronic Medicine: Wireless Microelectronic Systems"
DESCRIPTION:The ability to understand living systems in the body and attain therapeutic effects at target organs promises to transform therapies for complex diseases and conditions that cannot be treated adequately with drug-based therapies alone. The last decade has seen rapid advances in implantable medical devices (implants)\, ranging from new materials to increased implant sophistication and beyond. Despite these advances\, existing implant technologies are heavily reliant on wires and batteries\, creating problems for chronic use\, while emerging wireless implant systems lack the size scalability necessary to minimize tissue damage and hence enable chronic use of the implant. My research focuses on addressing the challenges related to miniaturization to realize safe\, chronic\, scalable wireless microelectronic systems based on ultra-miniature implants with complex sensory and actuation functions for future bioelectronic medicine; these systems can seamlessly interface with the human body and operate at both shallow and deep tissue depths. \nIn this talk\, I will present the first minimally invasive wireless system to monitor deep-tissue oxygenation. Spanning from the development of oxygen sensor implant enabled by custom integrated circuit and microsystems technologies to a wireless power/data transmission strategy\, I will discuss the design of each fundamental component and show how we integrate these components to build the complete system. System-level in vivo and ex vivo demonstrations in this work highlight the enormous capabilities of wireless implant systems. I will also present our work in the extreme miniaturization of ultrasonic implants\, and a new class of electro-optic sensors that will enable large-scale\, high-density wireless neural interfaces. I will conclude by discussing research directions that I would like to pursue in the future.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-next-generation-bioelectronic-medicine-wireless-microelectronic-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:20220324T150000
DTEND;TZID=America/New_York:20220324T180000
DTSTAMP:20260406T031531
CREATED:20220322T003023Z
LAST-MODIFIED:20220322T003023Z
UID:10007124-1648134000-1648144800@seasevents.nmsdev7.com
SUMMARY:Engineering Student Activities Council Jumble Sale
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/engineering-student-activities-council-jumble-sale/
LOCATION:Lobby and Mezzanine\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220324T153000
DTEND;TZID=America/New_York:20220324T163000
DTSTAMP:20260406T031531
CREATED:20220131T152932Z
LAST-MODIFIED:20220131T152932Z
UID:10007055-1648135800-1648139400@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Designer Matrices and Measurements of Cell-Matrix Remodeling" (Sarah Heilshorn)
DESCRIPTION:UPDATE: This seminar will be virtual only via zoom – check email for zoom link or contact ksas@seas.upenn.edu. \nCell-induced matrix remodeling is a hallmark of tissue development\, disease\, and regeneration. My lab has been developing biomaterials and matrix characterization methods to study these dynamic cell-matrix interactions. In designing our biomaterials\, we employ protein engineering methods to create biomimetic extracellular matrices with the direct ability to tune the matrix mechanics including stiffness and stress relaxation rate. We have identified matrix remodeling as a key property in the design of xeno-free matrices that support the growth of patient-derived primary tissue organoids. In a complementary project\, we have developed a micro-rheology strategy that uses dynamic light scattering to characterize the mechanical properties of dynamic biomaterials over time. We have used this method to measure the changes in matrix stiffness in cultures of breast cancer cells. Interestingly\, we discovered that the cells stiffen the matrix at short time-scales\, while simultaneously fluidizing the matrix at long time-scales. This seemingly paradoxical stiffening and fluidization are a consequence of active cell forces that result in matrix remodeling. Our results suggest a mechanism whereby breast cancer cells reconcile the seemingly contradictory requirements for both tension and malleability in the matrix during invasion by differential alteration of matrix mechanics across different time-scales.
URL:https://seasevents.nmsdev7.com/event/be-seminar-sarah-heilshorn-2/
LOCATION:https://upenn.zoom.us/j/96715197752
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220324T153000
DTEND;TZID=America/New_York:20220324T163000
DTSTAMP:20260406T031531
CREATED:20220221T193142Z
LAST-MODIFIED:20220221T193142Z
UID:10007097-1648135800-1648139400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Formal verification of a concurrent file system"
DESCRIPTION:Bugs in systems software like file systems\, databases\, and operating systems can have serious consequences\, ranging from security vulnerabilities to data loss\, and these bugs affect all the applications built on top. Systems verification is a promising approach to improve the reliability of our computing infrastructure\, since it can eliminate whole classes of bugs through machine-checked proofs that show a system always meets its specification. \nIn this talk\, I’ll present a line of work culminating in a verified\, concurrent file system called DaisyNFS. The file system comes with a proof that shows operations appear to execute correctly and atomically (that is\, all-or-nothing)\, even if the computer crashes and when processing concurrent operations. I’ll describe how a combination of design and verification techniques make it possible to carry out the proof for an efficient implementation.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-formal-verification-of-a-concurrent-file-system/
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:20220325T103000
DTEND;TZID=America/New_York:20220325T114500
DTSTAMP:20260406T031531
CREATED:20220119T191028Z
LAST-MODIFIED:20220119T191028Z
UID:10007024-1648204200-1648208700@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: Cornelia Fermüller\, University of Maryland\, “Bio-inspired Motion Analysis”
DESCRIPTION:Visual motion is a powerful cue that any animal uses\, but computational vision has not fully taken advantage of it. Classically\, Computer Vision and Robotics seeks to reconstruct models of the world by first computing from consecutive video frames the displacement of image points or the optical flow\, and then computing from these measurements 3D motion and scene geometry. Different from this approach\, I have explored the cue of visual motion along three different directions. First\, using neuromorphic event-based sensors which do not record image frames but temporal information about scene changes\, we obtain data in form of point clouds in x-y-t space that approximates continuous motion. By taking advantage of the density of the data at motion boundaries\, we developed algorithms for motion segmentation for the most challenging scenarios. Second\, by changing the classical sequence of computations\, and estimating 3D motion from robust image motion along gradients before introducing regularization constraints for 3D scene reconstruction\, we have developed classical optimization and machine learning algorithms that are more robust and generalize better to new scenarios. Third\, I show experiments on visual illusions that give an indication of the motion computations in the early visual processes in nature and point to directions for improving current motion computations.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-bio-inspired-motion-analysis/
LOCATION:Berger Auditorium (Room 13)\, Skirkanich Hall\, 210 South 33rd 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:20220325T140000
DTEND;TZID=America/New_York:20220325T150000
DTSTAMP:20260406T031531
CREATED:20211209T200449Z
LAST-MODIFIED:20211209T200449Z
UID:10006993-1648216800-1648220400@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Taking a layman's perspective to turbulence modeling"
DESCRIPTION:Abstract: Turbulence is an unsolved problem in classical physics. Its modeling often involves physical\, mathematical\, and numerical concepts that are daunting to even experienced engineers. This makes it very hard for a user to take a turbulence model from the literature and apply it in real-world engineering. This talk will take a layman’s perspective to turbulence modeling. Special attention will be given to near-wall turbulence modeling. We will try to discuss the following two possibilities\, both of which are brought to us by colleagues outside the wall modeling community. First\, the possibility of breaking the speed-accuracy-tradeoff curse and developing a wall model that effortlessly accounts for non-equilibrium effects. Second\, the possibility of giving a layman the ability to make informed decisions as a seasoned engineer when selecting a turbulence model.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-taking-a-laymans-perspective-to-turbulence-modeling/
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
END:VCALENDAR