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DTSTART;TZID=America/New_York:20211209T110000
DTEND;TZID=America/New_York:20211209T120000
DTSTAMP:20260406T145444
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UID:10006983-1639047600-1639051200@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium Seminar - "Data Compression: From Classical to Modern"
DESCRIPTION:Lossy data compression is a vital\, if hidden\, enabling technology. This virtual seminar would be impossible without data compression!  Existing compression standards for images and audio rely on a “classical” theory of compression that models sources as stationary Gaussian processes. This theory is quite mature\, and it provides remarkable insights into how to compress Gaussian sources in a variety of settings\, including those in which the data to be compressed is distributed among multiple users\, as occurs in federated learning. At the same time\, compressors based on artificial neural networks (ANNs) have recently begun to outperform those based on the classical theory for images and other practical sources. Given that the classical methods are provably near-optimal for Gaussian sources\, it is evident that ANNs are able to exploit non-Gaussianity in the data and that a new theory of data compression is required to explain their performance. I will present recent results on both fronts\, specifically the latest advances on distribution compression of Gaussian sources and some first steps toward the development of a “modern” theory. No background in data compression or information theory will be assumed. \nThe talk contains results obtained in collaboration with Omer Bilgen and Johannes Ballé.
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-seminar-data-compression-from-classical-to-modern/
LOCATION:Zoom – Meeting ID 968 2448 5695
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211207T120000
DTEND;TZID=America/New_York:20211207T130000
DTSTAMP:20260406T145444
CREATED:20211202T131922Z
LAST-MODIFIED:20211202T131922Z
UID:10006984-1638878400-1638882000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: “Synthetic Data: Anonymisation Groundhog Day”
DESCRIPTION:Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that synthetic data drawn from generative models preserves the statistical properties of the original dataset but\, at the same time\, provides perfect protection against privacy attacks. In this work\, we present the first quantitative evaluation of the privacy gain of synthetic data publishing and compare it to that of previous anonymisation techniques. \nOur evaluation of a wide range of state-of-the-art generative models demonstrates that synthetic data either does not prevent inference attacks or does not retain data utility. In other words\, we empirically show that synthetic data does not provide a better tradeoff between privacy and utility than traditional anonymisation techniques. \nFurthermore\, in contrast to traditional anonymisation\, the privacy-utility tradeoff of synthetic data publishing is hard to predict. Because it is impossible to predict what signals a synthetic dataset will preserve and what information will be lost\, synthetic data leads to a highly variable privacy gain and unpredictable utility loss. In summary\, we find that synthetic data is far from the holy grail of privacy-preserving data publishing.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-synthetic-data-anonymisation-groundhog-day/
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:20211207T110000
DTEND;TZID=America/New_York:20211207T120000
DTSTAMP:20260406T145444
CREATED:20211202T193540Z
LAST-MODIFIED:20211202T193540Z
UID:10006986-1638874800-1638878400@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium Seminar - "Alpha-loss: A Tunable Class of Loss Functions for Robust Learning"
DESCRIPTION:Machine learning has dramatically enhanced the role of automated decision making across a variety of domains. There are three ingredients that are at the heart of designing of sound ML algorithms: data\, learning architectures\, and loss functions. In this talk\, we focus on loss functions and the role of information theory in understanding the choice of loss functions in learning. We introduce alpha-loss as a parameterized class of loss functions that resulted from operationally motivating information-theoretic measures. Tuning the parameter alpha from 0 to infinity allows continuous interpolation between known and oft-used losses: log-loss (alpha=1)\, exponential loss (alpha=1/2)\, and 0-1 loss (alpha=infinity). \nBeginning with the classification properties of alpha-loss and its information-theoretic interpretations\, we will focus on a specific model\, namely the logistic model\, and quantify the optimization landscape of the average loss as viewed through the lens of Strict-Local-Quasi-Convexity. We discuss how different regimes of the parameter alpha enables the practitioner to tune the sensitivity of their algorithm towards two emerging challenges in learning: robustness and fairness. Finally\, we comment on ongoing and future work on different applications of alpha-loss including GANs and boosting
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-seminar-alpha-loss-a-tunable-class-of-loss-functions-for-robust-learning/
LOCATION:Zoom – Meeting ID 916 0331 6605
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211207T100000
DTEND;TZID=America/New_York:20211207T113000
DTSTAMP:20260406T145444
CREATED:20211129T142523Z
LAST-MODIFIED:20211129T142523Z
UID:10006981-1638871200-1638876600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Continuum Mechanics of Non-equilibrium Phenomena: A Journey Through Space and Time Scales"
DESCRIPTION:The fascinating diversity of material behavior at the macroscopic scale\, including plasticity\, phase transformations\, viscoelasticity or diffusion\, can only emerge from the underlying atomistic or particle behavior. Yet\, the direct connection between these two scales for non-equilibrium phenomena remains an extremely challenging quest from both a theoretical and computational perspective. This knowledge gap currently hinders predictive simulations and material discovery\, and leads to large economic losses and barriers to innovation in many industrial sectors. In this talk\, we will discuss several advances in the predictive modeling of non-equilibrium mechanics\, by combining tools from continuum mechanics\, statistical physics\, applied mathematics\, as well as machine learning and data-driven strategies.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-continuum-mechanics-of-non-equilibrium-phenomena-a-journey-through-space-and-time-scales/
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:20211203T150000
DTEND;TZID=America/New_York:20211203T170000
DTSTAMP:20260406T145444
CREATED:20211115T161436Z
LAST-MODIFIED:20211115T161436Z
UID:10006970-1638543600-1638550800@seasevents.nmsdev7.com
SUMMARY:Keeping Up the Good Work: Honoring 40 Years of Excellence in Diversity
DESCRIPTION:This year marks the 40th anniversary of Penn Engineering’s diversity efforts and we invite you to join us on Friday\, December 3\, at 3:00 p.m. EST to celebrate Penn Engineering’s new Office of Diversity\, Equity\, and Inclusion (ODEI)\, formerly known as the Office of Minority Programs.\n\nWe plan to meet in Heilmeier Hall (Towne 100) from 3:00-3:30 p.m. for remarks and we will then move upstairs to 211 Towne to officially unveil and tour the brand new ODEI Suite.\n\nThe new suite that will be unveiled honors and builds upon the remarkable work of Ms. Cora Ingrum\, ODEI’s former Director and her Administrative Assistant\, Ms. Donna Hampton. Over the years\, the office has been instrumental in identifying and retaining diverse engineering talent and helping students successfully transition into graduate and professional programs as well as productive professional careers. ODEI has a legacy of rich programs and partnerships with academia and industry that has continued to be strengthened under the leadership of Dr. Laura Stubbs\, the current Director of ODEI.\n\n\nThe recording of this event is posted here for your viewing.\nhttps://youtu.be/y7-cTd03e3Y\n\n\n  \n\n\n 
URL:https://seasevents.nmsdev7.com/event/keeping-up-the-good-work-honoring-40-years-of-excellence-in-diversity/
LOCATION:Heilmeier Hall (Room 100)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Faculty,Graduate,Student,Master's,Postdoctoral,Alumni,Undergraduate,Diversity, Equity and Inclusion,Staff
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211203T140000
DTEND;TZID=America/New_York:20211203T150000
DTSTAMP:20260406T145444
CREATED:20210920T160029Z
LAST-MODIFIED:20210920T160029Z
UID:10006912-1638540000-1638543600@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: "Computational and Experimental Modeling of Membrane Distillation"
DESCRIPTION:Abstract: \nComputational fluid dynamics simulations and experiments were conducted to study the performance of distillation membrane process for water treatment and desalination applications. Polarizations and fouling/scaling in a direct contact membrane distillation module were examined. Laminar and turbulent flow regimes in the feed and permeate channels were considered. The hydrophobic membrane separates feed and permeate channels. The membrane is treated as a functional surface where the permeate flux is modeled as a function of local temperature\, concentration using the Dusty-Gas diffusion model. The combination of Knudsen and viscous diffusion governs the vapor transport through the membrane. Vaporization occurs in the feed channel at the entrance of pores of the membrane due to the well-known confinement (surface tension) effect. Vapor is pushed through the membrane by the partial pressure difference created by the temperature concentration difference across the membrane. The permeability (resistance) of the membrane depends strongly on the membrane thickness\, porosity\, pore size\, and tortuosity. Mitigation of polarizations and fouling/scaling and the optimization of module design will be presented and discussed.
URL:https://seasevents.nmsdev7.com/event/pics-colloquium-computational-and-experimental-modeling-of-membrane-distillation/
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:20211203T103000
DTEND;TZID=America/New_York:20211203T114500
DTSTAMP:20260406T145444
CREATED:20211110T144715Z
LAST-MODIFIED:20211110T144715Z
UID:10006964-1638527400-1638531900@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: "Toward Object Manipulation Without Explicit Models"
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.  \nThe prevalent approach to object manipulation is based on the availability of explicit 3D object models. By estimating the pose of such object models in a scene\, a robot can readily reason about how to pick up an object\, place it in a stable position\, or avoid collisions. Unfortunately\, assuming the availability of object models constrains the settings in which a robot can operate\, and noise in estimating a model’s pose can result in brittle manipulation performance. In this talk\, I will discuss our work on learning to manipulate unknown objects directly from visual (depth) data. Without any explicit 3D object models\, these approaches are able to segment unknown object instances\, pickup objects in cluttered scenes\, and re-arrange them into desired configurations. I will also present recent work on combining pre-trained language and vision models to efficiently teach a robot to perform a variety of manipulation tasks. I’ll conclude with our initial work toward learning implicit representations for objects.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-toward-object-manipulation-without-explicit-models/
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:20211202T153000
DTEND;TZID=America/New_York:20211202T163000
DTSTAMP:20260406T145444
CREATED:20211202T132732Z
LAST-MODIFIED:20211202T132732Z
UID:10006985-1638459000-1638462600@seasevents.nmsdev7.com
SUMMARY:CIs Seminar: "Modeling cancer progression with neural networks"
DESCRIPTION:The exponential growth of biological datasets in recent years has increased the dependency of cancer research on AI and computational analysis. Cancer evolves through the accumulation of genetic events over time\, which are represented through different types of data. Integration of machine learning methods with temporal modeling and genomic methods has the potential to improve our understanding and treatment of cancer. In this talk\, we will discuss emerging data science challenges for cancer research and opportunities to address these challenges using integrated AI frameworks.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-modeling-cancer-progression-with-neural-networks/
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:20211202T140000
DTEND;TZID=America/New_York:20211202T150000
DTSTAMP:20260406T145444
CREATED:20211124T170430Z
LAST-MODIFIED:20211124T170430Z
UID:10006978-1638453600-1638457200@seasevents.nmsdev7.com
SUMMARY:Fall 2021 GRASP Seminar: Gregory S. Chirikjian\, "Robot Imagination: Affordance-Based Reasoning about Unknown Objects"
DESCRIPTION:Today’s robots are very brittle in their intelligence. This follows from a legacy of industrial robotics where robots pick and place known parts repetitively. For humanoid robots to function as servants in the home and in hospitals they will need to demonstrate higher intelligence\, and must be able to function in ways that go beyond the stiff prescribed programming of their industrial counterparts. A new approach to service robotics is discussed here. The affordances of common objects such as chairs\, cups\, etc.\, are defined in advance. When a new object is encountered\, it is scanned and a virtual version is put into a simulation wherein the robot “imagines’’ how the object can be used. In this way\, robots can reason about objects that they have not encountered before\, and for which they have no training using. Videos of physical demonstrations will illustrate this paradigm\, which the presenter has developed with his students Hongtao Wu\, Meng Xin\, Sipu Ruan\, and others.
URL:https://seasevents.nmsdev7.com/event/fall-2021-grasp-seminar-gregory-s-chirikjian-robot-imagination-affordance-based-reasoning-about-unknown-objects/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211202T123000
DTEND;TZID=America/New_York:20211202T133000
DTSTAMP:20260406T145444
CREATED:20211118T211608Z
LAST-MODIFIED:20211118T211608Z
UID:10006974-1638448200-1638451800@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: "Data-driven materials design in the quantum regime: motif-centric learning framework and local-symmetry-guided material discovery"
DESCRIPTION:Materials design in the quantum regime call for the integration of multi-tier materials information that go beyond atomic structures. Especially\, many quantum behaviors are greatly controlled by local symmetries and local bonding environments. In this talk\, motivated by Pauling’s rules\, Dr. Yan will show that local bonding environments (motifs) can be incorporated in a graph-based machine learning architecture to make reliable property predictions for solid-state quantum materials including complex metal oxides. The proposed atom-motif dual network model demonstrates the feasibility to incorporate beyond-atom materials information in a graph network framework and achieves the state-of-the-art performance in predicting the electronic structure properties of complex metal oxides. As an example of quantum material design by local bonding symmetry\, he will discuss how data-driven material science can be combined with symmetry-based physical principles to guide the search for quantum defects in two-dimensional (2D) materials for quantum information processing and quantum computing. The use of local bonding symmetry (irreducible representations) as a material design hypothesis enables the identification of anion antisite defects as promising spin qubits and quantum emitters in six monolayer transition metal dichalcogenides. The work creates a technically accessible 2D platform for the fabrication of defect-based multi-qubit systems for quantum computing. At the end of the talk\, he will discuss the continued development of machine learning models that embrace symmetries and symmetry-based interactions and the discovery of quantum defects in a vast space of 2D material systems.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-data-driven-materials-design-in-the-quantum-regime-motif-centric-learning-framework-and-local-symmetry-guided-material-discovery/
LOCATION:Auditorium\, LRSM Building\, 3231 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211201T153000
DTEND;TZID=America/New_York:20211201T163000
DTSTAMP:20260406T145444
CREATED:20210831T004042Z
LAST-MODIFIED:20210831T004042Z
UID:10006871-1638372600-1638376200@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "From Molecular Simplicity to Supramolecular Complexity: Low Symmetry Packings of Ionic Spherical Micelles"
DESCRIPTION:Abstract \nA delicate balance of noncovalent interactions drives hydrated molecular amphiphiles to self-assemble into lyotropic liquid crystals (LLCs) of varied topologies\, the exquisite nanodomain structures of which suggest applications as separations membranes\, mesoporous materials synthesis templates\, and therapeutic delivery vehicles. Based on hard sphere colloidal crystals\, spherical micelles are intuitively expected to form high symmetry face-centered cubic (FCC) and hexagonally close-packed (HCP) LLCs. However\, we recently discovered that ionic surfactant micelles also form a zoo of low symmetry\, tetrahedrally close-packed Frank-Kasper (FK) phases that mimic the structures of elemental metals and their alloys. The emergence of complex FK s\, A15\, C14\, and C15 LLCs arises from a frustrated non-covalent force balance that minimizes local variations in amphiphile solvation\, while maximizing electrostatic cohesion in the ionic micelle ensemble. We describe how chemical features of the amphiphiles and the path-dependent processing of their aqueous dispersions drive LLC sphere packing symmetry selection\, culminating in our discovery of the ability of oil-swollen ionic micelles to aperiodically order into lyotropic dodecagonal quasicrystals (DDQCs). Thus\, engineering molecular frustration into simple amphiphiles begets high fidelity\, (a)periodic pattern formation at length scales far exceeding those of their constituent molecular and supramolecular building blocks.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-from-molecular-simplicity-to-supramolecular-complexity-low-symmetry-packings-of-ionic-spherical-micelles/
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:20211201T150000
DTEND;TZID=America/New_York:20211201T160000
DTSTAMP:20260406T145444
CREATED:20211129T201637Z
LAST-MODIFIED:20211129T201637Z
UID:10006982-1638370800-1638374400@seasevents.nmsdev7.com
SUMMARY:Fall 2021 GRASP SFI: Lucas Manuelli\, NVIDIA\, “Robot Manipulation with Learned Representations”
DESCRIPTION:We would like to have robots which can perform useful manipulation tasks in real-world environments. This requires robots that can perceive the world with both precision and semantic understanding\, methods for communicating desired tasks to these systems\, and closed loop visual feedback controllers for robustly executing manipulation tasks. This is hard to achieve with previous methods: prior work hasn’t enabled robots to densely understand the visual world with sufficient precision to perform robotic manipulation or endowed them with the semantic understanding needed to perform tasks with novel objects. This limitation arises partly from the object representations that have been used\, the challenge in extracting these representations from the available sensor data in real-world settings\, and the manner in which tasks have been specified. The talk will have two sections. In the first section I will focus on object-centric representations and will present a family of approaches that leverage self-supervision\, both in the visual domain and for learning physical dynamics\, to enable robots to perform manipulation tasks. Specifically we (i) demonstrate the novel application of dense visual object descriptors to robotic manipulation and provide a fully self-supervised robot system to acquire them (ii) introduce the concept of category-level manipulation tasks and develop a novel object representation based on semantic 3D keypoints along with a task specification that uses these keypoints to define the task for all objects of a category\, including novel instances\, (iii) utilize our dense visual object descriptors to quickly learn new manipulation skills through imitation and (iv) use our visual object representations to learn data-driven models that can be used to perform closed loop feedback control in manipulation tasks. The second part of the talk will discuss an alternative action-centric approach that enables the incorporation of language-instructions in our manipulation pipelines.
URL:https://seasevents.nmsdev7.com/event/fall-2021-grasp-sfi-lucas-manuelli-nvidia-robot-manipulation-with-learned-representations/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211130T153000
DTEND;TZID=America/New_York:20211130T163000
DTSTAMP:20260406T145444
CREATED:20211116T184503Z
LAST-MODIFIED:20211116T184503Z
UID:10006972-1638286200-1638289800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Tackling climate change with machine learning"
DESCRIPTION:Machine learning can be a powerful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this talk\, we will explore opportunities and challenges in AI-for-climate\, from optimizing electrical grids to monitoring crop yield\, and how these impactful problems can also drive methodological innovations in machine learning.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-tackling-climate-change-with-machine-learning/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211130T110000
DTEND;TZID=America/New_York:20211130T120000
DTSTAMP:20260406T145444
CREATED:20211124T222730Z
LAST-MODIFIED:20211124T222730Z
UID:10006979-1638270000-1638273600@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium Seminar -  "Bits and Brains: Ultra-low Power\, Neuro-inspired Edge-AI for Autonomous Systems"
DESCRIPTION:As we march towards the age of “ubiquitous intelligence”\, we note that AI and Machine learning are progressively moving from the Cloud to the Edge devices. The success of Edge-AI is pivoted on innovative circuits and hardware that can enable inference and limited learning\, in hardware-constrained ultra-low-power (uW to mW) systems – an area of active research. In this talk\, I will discuss the promises and outlook of Edge-AI and their applications in Autonomous Systems; and elaborate on some of our recent work on enabling such systems in sensor nodes and robotics. While some of these systems extend our understanding of statistical machine learning\, a large class of circuits and systems are inspired by the information representation in the brain. I will talk about the design of such circuits and systems with an emphasis on the impact of mixed-signal circuits\, near-memory and in-memory compute architectures\, non-CMOS (RRAM-based) compute macros\, as well as algorithm-hardware co-design to realize the most energy-efficient Edge-AI ASICs for the next generation of smart and autonomous systems.
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-seminar-bits-and-brains-ultra-low-power-neuro-inspired-edge-ai-for-autonomous-systems/
LOCATION:Zoom – Meeting ID 912 5944 4192
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211130T100000
DTEND;TZID=America/New_York:20211130T113000
DTSTAMP:20260406T145444
CREATED:20211013T130316Z
LAST-MODIFIED:20211013T130316Z
UID:10006928-1638266400-1638271800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Predictive Simulations of High-rise Building Peak Wind Pressure Loads"
DESCRIPTION:Computational fluid dynamics (CFD) can inform sustainable design of buildings and cities in terms of optimizing pedestrian wind comfort\, air quality\, thermal comfort\, energy efficiency\, and resiliency to extreme wind events. An important challenge is that the accuracy of CFD results can be compromised by the large natural variability and complex physics that are characteristic of urban flow problems. In this talk\, I will present an investigation of the potential of large-eddy simulations (LES) towards predicting peak wind pressure loads on high rise-buildings. First\, the sensitivity of LES results to the turbulence in the incoming boundary layer wind is quantified and the results are validated against wind tunnel experiments. Next\, high resolution LES are employed to gain a better understanding of the flow physics that govern small-scale extreme suction events observed in specific locations on the façade. Finally\, a multi-fidelity simulation strategy\, aimed at reducing the overall computational cost of LES-based cladding load predictions\, is explored. The talk will conclude with an overview of ongoing work on full-scale wind pressure measurements on high-rise buildings for future validation and uncertainty quantification studies.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-predictive-simulations-of-high-rise-building-peak-wind-pressure-loads/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211129T120000
DTEND;TZID=America/New_York:20211129T130000
DTSTAMP:20260406T145444
CREATED:20210913T141946Z
LAST-MODIFIED:20210913T141946Z
UID:10006893-1638187200-1638190800@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: “Tissues fluidification in Invasive breast cancer” (Giorgio Scita)
DESCRIPTION:Room: Towne 225/Raisler Lounge \nFor zoom link\, contact manu@seas.upenn.edu.
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-giorgio-scita/
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:20211123T153000
DTEND;TZID=America/New_York:20211123T163000
DTSTAMP:20260406T145444
CREATED:20211102T174315Z
LAST-MODIFIED:20211102T174315Z
UID:10006954-1637681400-1637685000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "From Seeing to Doing: Understanding and Interacting with the Real World"
DESCRIPTION:Visual intelligence is a cornerstone of intelligence\, for both humans and machines. In this talk\, I go over a number of research work by our group on the topics of visual perception and robotic learning. The guiding principle of our work is inspired by the Gibsonian belief that perceptual and robotic learning should be based on an ecology approach\, solving tasks and problems approximating the real-world setting and scale.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-from-seeing-to-doing-understanding-and-interacting-with-the-real-world/
LOCATION:PA
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211123T110000
DTEND;TZID=America/New_York:20211123T120000
DTSTAMP:20260406T145444
CREATED:20211115T141126Z
LAST-MODIFIED:20211115T141126Z
UID:10006969-1637665200-1637668800@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium Seminar - "New Materials for Three Dimensional Ferroelectric Microelectronics"
DESCRIPTION:In the last decade\, there have been major changes in the families of ferroelectric materials available for integration with CMOS electronics.  These new materials\, including Hf1-xZrxO2\, Al1-xScxN\, Al1-xBxN and Zn1-xMgxO\, offer the possibility of new functionalities. This talk will discuss the possibility of exploiting the 3rd dimension in microelectronics for functions beyond interconnects\, enabling 3D non-von Neumann computer architectures exploiting ferroelectrics for local memory\, logic in memory\, digital/analog computation\, and neuromorphic functionality. This approach circumvents the end of Moore’s law in 2D scaling\, while simultaneously overcoming the “von Neumann bottleneck” in moving instructions and data between separate logic and memory circuits. Computing accounts for 5 – 15% of worldwide energy consumption. In the U.S.\, data centers alone are projected to consume approximately 73 billion kWh in 2020. While recent efficiency gains in hardware have partially mitigated the rising energy consumption of computing\, major gains are achievable in a paradigm shift to 3D computing systems\, especially those that closely couple memory and logic.  The talk will cover the relevant materials\, their deposition conditions\, and what is known about the wake-up\, fatigue\, and retention processes.
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-seminar-new-materials-for-three-dimensional-ferroelectric-microelectronics/
LOCATION:Zoom – Meeting ID 954 7393 2132\, PA\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211122T153000
DTEND;TZID=America/New_York:20211122T170000
DTSTAMP:20260406T145444
CREATED:20211122T153336Z
LAST-MODIFIED:20211122T153336Z
UID:10006976-1637595000-1637600400@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Computer-aided Clinical Trials for Medical Devices"
DESCRIPTION:Life-critical medical devices require robust safety and efficacy to treat patient populations with\npotentially large inter-patient and intra-patient variability. Today\, the de facto standard for evaluating medical devices is the randomized clinical trial. However\, even after years of device development many clinical trials fail. For example\, in the Rhythm ID Goes Head to Head Trial (RIGHT) the risk for inappropriate therapy actually increased relative to control treatments.\nWith recent advances in physiological modeling and devices incorporating more complex software components\, population-level device outcomes can be obtained with large-scale simulations. Consequently\, there is a need to explore alternative approaches to evaluate devices within a clinical trial context. \nThis work presents a framework to utilize computer modeling and simulation to improve the evaluation of medical device software\, such as the algorithms in  implantable cardioverter defibrillators (ICD). Within this framework\, virtual cohorts are generated and combined with real data to evaluate the efficacy of ICD algorithms while also quantifying the uncertainty due to the simulation. Results predicting the outcome of RIGHT and the improvement in statistical power while reducing the sample size are presented. Next\, an approach to improving the performance of the device with Bayesian optimization is presented. Devices can degrade in performance when deployed to populations initially excluded in a clinical trial. For example\, ICDs have shown increased rates of inappropriate therapy in patients with congenital heart disease. Bayesian optimization can be used to automate the adjustment of device parameters and fine-tune performance for a given cohort with minimal intervention. Our approach  identifies parameters which improve the performance of the device with outcomes aligned with the Multicenter Automatic Defibrillator Implantation Trial–Reduce Inappropriate Therapy (MADIT-RIT) clinical trial.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-computer-aided-clinical-trials-for-medical-devices/
LOCATION:Zoom – Meeting ID 916 4694 2571
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:20211122T120000
DTEND;TZID=America/New_York:20211122T130000
DTSTAMP:20260406T145444
CREATED:20211025T142239Z
LAST-MODIFIED:20211025T142239Z
UID:10006940-1637582400-1637586000@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: "Elucidating the role of cell-environment interactions in somatic cell acquisition of stemness” (Timothy L. Downing)
DESCRIPTION:Room: Towne 225/Raisler Lounge \nFor zoom link\, contact manu@seas.upenn.edu.
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-elucidating-the-role-of-cell-environment-interactions-in-somatic-cell-acquisition-of-stemness-timothy-l-downing/
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:20211120T150000
DTEND;TZID=America/New_York:20211120T160000
DTSTAMP:20260406T145444
CREATED:20211116T151915Z
LAST-MODIFIED:20211116T151915Z
UID:10006971-1637420400-1637424000@seasevents.nmsdev7.com
SUMMARY:ODEI Spotlight: SWE Headshots on Smith Walk
DESCRIPTION:SWE Headshots | November 20\, 3-4 pm | On Smith Walk (between Towne and Hayden Hall near the Penn Engineering Banner) \nCome get a professional headshot taken on Saturday\, November 20th (rain date Sunday\, November 21st)! Headshots will be taking place on Smith Walk (between Towne and Hayden Hall near the Penn Engineering Banner) from 3-4pm.
URL:https://seasevents.nmsdev7.com/event/odei-spotlight-swe-headshots-on-smith-walk/
LOCATION:PA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211119T133000
DTEND;TZID=America/New_York:20211119T143000
DTSTAMP:20260406T145444
CREATED:20211111T144843Z
LAST-MODIFIED:20211111T144843Z
UID:10006965-1637328600-1637332200@seasevents.nmsdev7.com
SUMMARY:MEAM PhD Thesis Defense: "High Throughput Immunospecific Detection and Analysis of Subcellular Nanomaterials at the Single Particle Level"
DESCRIPTION:Extracellular vesicles (EVs) have shown great potential in diagnostics\, therapeutics\, and have been discovered to play a key role in intercellular communication. The study of EVs in biological fluids has proven challenging due to the nanoscale size of EVs (30 nm-1 µm diameter)\, the enormous quantity of EVs present in clinical samples (e.g. 10E10/mL)\, and the heterogeneous properties of EVs\, even within those that originate from the same cell. My thesis has developed two distinct\, but related\, technologies to address these challenges. \nThe first half of my thesis focuses on isolation and interpretation of specific subsets of EVs from biological samples\, such as plasma\, based on particular expressions of surface proteins. From these isolated EVs we have demonstrated\, across multiple diseases\, that there are signatures of disease states encoded in the EV RNA cargo\, which we identified using supervised machine learning. To this end\, building on prior work from our group\, we developed a multichannel nanofluidic system that could analyze crude clinical plasma samples with nanoscale precision\, which was coined Track Etched Magnetic Nanopore (TENPO). \nWe evaluated the clinical potential TENPO by first applying it to diagnosing and staging pancreatic cancer\, where current biomarkers have proven elusive to achieve sufficient sensitivity and specificity. In this work\, we algorithmically combined tumor-associated EV mRNA and miRNA\, isolated from plasma using TENPO\, with ccfDNA levels\, KRAS mutation detection\, and CA19-9 via an ensemble machine learning model to form a multi-analyte panel. On an independent\, blinded validation set (N = 136)\, we were able to distinguish patients with pancreatic cancer from those without at an accuracy of 92% (AUC=0.95). Moreover\, among patients with pancreatic cancer\, my model achieved significantly higher accuracy for disease staging (84%) than the current standard imaging method (64%). In addition to pancreatic cancer\, I have also applied this approach to traumatic brain injury and to Alzheimer’s Disease to explored its diagnostic value in neurodegenerative diseases. \nThough TENPO was successful in isolating specific subsets of EVs for downstream analysis\, it was not able to resolve the heterogeneity that is known to exist between individual EVs. Current single EV analysis methods have also been exclusive to platforms that could only analyze a small number of EVs (< 20\,000)\, limiting their ability to evaluate rare EV subsets due to subsampling error when searching for these rare EVs amongst the high EV background present in plasma. To address this challenge\, I have developed a high throughput\, droplet based optofluidic platform to quantify specific single EVs. The key innovation of my platform is parallelization of droplet generation\, processing\, and analysis to achieve a throughput >100x greater than typical in microfluidic systems\, using only simple optics and accessible soft-lithography fabrication. I demonstrated that this improvement in throughput can be leveraged to quantify human neuron derived EVs at a limit of detection LOD = 13 EVs/µL\, a >100x improvement over gold standard single EV characterization methods. Additionally\, I demonstrated the potential of this system for use in clinical samples by detecting EVs in a complex media\, containing up to 4\,000 fold more background EVs\, and achieved an LOD = 48 EVs/µL. \nBeyond extracellular vesicles\, I was also inspired to apply this immunospecific\, nanoscale detection and analysis modality to other subcellular materials\, namely mitochondria. I have developed a pipeline to isolate and amplify single mitochondrion DNA from individual cells with 20x higher yield than with conventional tools. With the improved yield\, we were also able to reveal the pervasive single nucleotide variation on mitochondrion DNA within single cells. We also compared the genomic variation within neuron mitochondria versus that within astrocyte mitochondria\, which is impossible via traditional methodology.
URL:https://seasevents.nmsdev7.com/event/meam-phd-thesis-defense-high-throughput-immunospecific-detection-and-analysis-of-subcellular-nanomaterials-at-the-single-particle-level/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,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:20211119T103000
DTEND;TZID=America/New_York:20211119T114500
DTSTAMP:20260406T145444
CREATED:20211105T164840Z
LAST-MODIFIED:20211105T164840Z
UID:10006957-1637317800-1637322300@seasevents.nmsdev7.com
SUMMARY:GRASP on Robotics: "Learning and Influencing Conventions in Interactive Robotics"
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.  \nThere have been significant advances in the field of robot learning in the past decade. However\, many challenges still remain when studying how robot learning can advance interactive agents such as robots that collaborate with humans\, and how interactions can enable more effective robot learning. This introduces an opportunity for developing new robot learning algorithms that can help advance the science of interactive autonomy. In this talk\, we will discuss a formalism that learns conventions\, i.e.\, low-dimensional representations sufficient for capturing non-stationary interactions. We demonstrate how we can influence and stabilize these conventions to achieve desirable outcomes in multi-robot coordination. Finally\, we will then talk about some of the challenges of learning such representations when interacting with humans\, and how we can develop data-efficient techniques that can tap into different sources of data such as suboptimal demonstrations or can actively learn human preferences. We will end the talk with a discussion of applications of these techniques in assistive robotics. \n 
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-learning-and-influencing-conventions-in-interactive-robotics/
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:20211119T100000
DTEND;TZID=America/New_York:20211119T120000
DTSTAMP:20260406T145444
CREATED:20211109T154937Z
LAST-MODIFIED:20211109T154937Z
UID:10006963-1637316000-1637323200@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Novel design strategies for engineering biliverdin-binding fluorescent proteins" (Michael Magaraci)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Brian Chow are pleased to announce the Doctoral Dissertation Defense of Michael Magaraci.\n\nTitle: Novel design strategies for engineering biliverdin-binding fluorescent proteins\n\n\nDate: Friday\, November 19\, 2021\nTime: 10:00 AM (EST)\nLocation: Towne 337 and via Zoom at the link below:\n https://upenn.zoom.us/j/98253474334?pwd=MXNQMWR2dWlXU2dZc0ZHb0FhV0Z0Zz09\n\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-novel-design-strategies-for-engineering-biliverdin-binding-fluorescent-proteins-michael-magaraci/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211118T153000
DTEND;TZID=America/New_York:20211118T163000
DTSTAMP:20260406T145444
CREATED:20211112T215653Z
LAST-MODIFIED:20211112T215653Z
UID:10006968-1637249400-1637253000@seasevents.nmsdev7.com
SUMMARY:MSE Thesis Defense: "Ultra-High-Resolution Patterning and Pattern Transfer via Nanocrystal Colloidal Lithography"
DESCRIPTION:The ability to design\, pattern\, and process materials at the nanoscale has enabled vast research opportunities ranging from fundamental science to technological applications and device integration. The continued development of nanoscience and nanotechnology relies upon pushing the limits of nanoscale fabrication capabilities. After decades of development\, this frontier has moved to the sub-10 nm length scale to explore novel physical properties and functionalities for next-generation technology. However\, conventional “top-down” strategies that have carried nanofabrication to this point have severe limitations for practically improving the resolution capabilities of deep nanoscale fabrication. In this dissertation\, we demonstrate ultra-high-resolution patterning and pattern transfer using nanocrystal (NC) colloidal lithography. This innovative nanofabrication platform integrates bottom-up methods\, that combine NC synthesis and self-assembly approaches\, with well-established top-down techniques such as dry etching and thin film deposition. \nWe employ monodisperse NC building blocks with self-assembly methods to establish high-density\, well-ordered patterns\, where the inorganic core of each NC serves as a discrete hard mask used for high-fidelity pattern transfer into a desired substrate material. We demonstrate the use of isotropic NCs to establish various sub-10 nm pattern morphologies and examine the stability of the NC pattern upon dry etching\, comparing NC monolayers and bilayers. We extend the NC colloidal lithography scheme using anisotropic NCs to demonstrate high-density\, anisotropic pattern transfer into various substrate materials down to the sub-5 nm regime. The presented fabrication strategy offers further opportunities to leverage various combinations of NC morphologies and materials afforded by the extensive NC library for more complex pattern design. Additionally\, this approach can be extended to process various substrate material classes at the deep nanoscale. The NC colloidal lithography platform enables broader access to single-digit nanoscale fabrication for the scientific community worldwide\, which could impact various research sectors ranging from integrated circuits to memory devices\, optoelectronics\, metasurfaces\, quantum devices and more.
URL:https://seasevents.nmsdev7.com/event/mse-thesis-defense-ultra-high-resolution-patterning-and-pattern-transfer-via-nanocrystal-colloidal-lithography/
LOCATION:https://upenn.zoom.us/j/96715197752
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211118T153000
DTEND;TZID=America/New_York:20211118T163000
DTSTAMP:20260406T145444
CREATED:20210707T141748Z
LAST-MODIFIED:20210707T141748Z
UID:10006820-1637249400-1637253000@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Ionic Liquid-based Therapeutics" (Samir Mitragotri)
DESCRIPTION:This seminar will be held virtually on zoom – check your email for the link or contact ksas@seas.upenn.edu. \nIonic liquids\, the liquid salts comprising organic anions and cations\, offer exciting opportunities for several therapeutic applications. Their tunable properties offer control over their design and function. Starting with biocompatible ions\, we synthesized a library of ionic liquids and explored them for various drug delivery applications. Ionic liquids provided unique advantages including overcoming the biological transport barriers of skin\, buccal mucosa and the intestinal epithelium. At the same time\, they also stabilized proteins and nucleic acids and enabled the delivery of biologics across these barriers. Ionic liquids also provided unique biological functions including adjuvancy towards vaccines and antimicrobial function. I will present an overview of the design features of ionic liquids and novel biomedical applications enabled by these unique materials.
URL:https://seasevents.nmsdev7.com/event/be-seminar-samir-mitragotri/
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:20211118T120000
DTEND;TZID=America/New_York:20211118T133000
DTSTAMP:20260406T145444
CREATED:20211112T212550Z
LAST-MODIFIED:20211112T212550Z
UID:10006967-1637236800-1637242200@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Graph Convolutions for Teams of Robots"
DESCRIPTION:In many applications in robotics\, there exist teams of robots operating in dynamic environments requiring the design of complex communication and control schemes. The problem is made easier if one assumes the presence of an oracle that has instantaneous access to states of all entities in the environment and can communicate simultaneously without any loss. However\, such an assumption is unrealistic especially when there exist a large number of robots. More specifically\, we are interested in decentralized control policies for teams of robots using only local communication and sensory information to achieve high-level team objectives. We first make the case for using distributed reinforcement learning to learn local behaviors by optimizing for a sparse team-wide reward as opposed to existing model-based methods. A central caveat of learning policies using model-free reinforcement learning is the lack of scalability. To achieve large-scale scalable results\, we introduce a novel paradigm where the policies are parametrized by graph convolutions. Additionally\, we also develop new methodologies to train these policies and derive technical insights into their behaviors. Building upon these\, we design perception-action loops for teams of robots that rely only on noisy visual sensors\, a learned history state\, and local information from nearby robots to achieve complex team wide-objectives. We demonstrate the effectiveness of our methods on several large-scale multi-robot tasks.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-graph-convolutions-for-teams-of-robots/
LOCATION:Room 452 C\, 3401 Walnut\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211117T163000
DTEND;TZID=America/New_York:20211117T173000
DTSTAMP:20260406T145444
CREATED:20211101T145003Z
LAST-MODIFIED:20211101T145003Z
UID:10006952-1637166600-1637170200@seasevents.nmsdev7.com
SUMMARY:ODEI and SHPE Celebrate Hispanic and Native American Heritage
DESCRIPTION:On Wednesday November 17 at 4pm\, Penn Engineering will celebrate the Hispanic/Native American Heritage. This celebration of our students\, faculty and staff of Hispanic/Latinx\, and Native American background is in support of our commitment to diversity and inclusion in the School.  Dean Vijay Kumar will give welcome and opening remarks\, followed by student and faculty speakers and cultural presentations by Penn Engineering Students. Food and refreshments will be served. This event is sponsored by ODEI\, Grad. RAS\, and SHPE.
URL:https://seasevents.nmsdev7.com/event/odei-and-shpe-celebrate-hispanic-and-native-american-heritage/
LOCATION:Quain Courtyard
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211117T110000
DTEND;TZID=America/New_York:20211117T120000
DTSTAMP:20260406T145444
CREATED:20210903T163150Z
LAST-MODIFIED:20210903T163150Z
UID:10006878-1637146800-1637150400@seasevents.nmsdev7.com
SUMMARY:CEMB Future Leaders Seminar: "A microviscosimetry toolbox for plant cells + tissue based on molecular rotors"
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-seminar-a-microviscosimetry-toolbox-for-plant-cells-tissue-based-on-molecular-rotors/
LOCATION:https://upenn.zoom.us/j/96715197752
CATEGORIES:Seminar
ORGANIZER;CN="Center for Engineering MechanoBiology (CEMB)":MAILTO:annjeong@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211116T150000
DTEND;TZID=America/New_York:20211116T161500
DTSTAMP:20260406T145444
CREATED:20211108T143508Z
LAST-MODIFIED:20211108T143508Z
UID:10006960-1637074800-1637079300@seasevents.nmsdev7.com
SUMMARY:ESE 2021 Jack Keil Wolf Lecture - "MEMS:  the Transition from “Four-Letter-Word” to “Trendy”"
DESCRIPTION:Thirty years ago\, semiconductor manufacturers (wafer fabs) rolled their eyes and muttered under their breath when they heard the word MEMS.  Micro-Electromechanical Mechanical Systems are minute mechanical devices built on silicon integrated circuit wafers.  They are the microphones\, gravity sensors\, oscillators\, motion sensors\, electronic filters in your cell-phone – and more.  MEMS processes were “weird”.   They required unusual and immature special processing tools and etch chemicals.  MEMS wafers often broke inside traditional semiconductor processing tools\, creating logistical nightmares for the wafer fabs.  Packaging was a terrifying ordeal\, protecting the miniscule mechanical structures from damage.  Even as recently as 15 years ago\, MEMS was considered a four letter word at the larger wafer fabs\, or foundries.  Today\, that has all changed.  Today\, the largest foundries ALL manufacture MEMS devices and they scramble to be the supplier of the latest\, newest MEMS invention.  Today\, MEMS special processing tools are all high precision\, high-throughput\, state-of-the-art equipment.  Today\, many options exist for packaging these bizarre\, but powerful chips.  Today\, everyone wants to manufacture MEMS chips.  Today\, MEMS is “trendy”. \nHow did this happen?  How did MEMS transition from an ugly\, shunned\, four letter status to being fashionable?   My presentation will walk through this astonishing historical transformation\, focusing on the revolutionary devices which are made possible by MEMS technology and how they have radically altered and augmented the way we interact with electronic systems.
URL:https://seasevents.nmsdev7.com/event/ese-2021-jack-keil-wolf-lecture-mems-the-transition-from-four-letter-word-to-trendy/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
END:VCALENDAR