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DTSTART;TZID=America/New_York:20211115T120000
DTEND;TZID=America/New_York:20211115T130000
DTSTAMP:20260406T124919
CREATED:20210913T141548Z
LAST-MODIFIED:20210913T141548Z
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SUMMARY:PSOC@Penn Seminar: "Cell Learning" (Jeremy Gunawardena)
DESCRIPTION:Room: Towne 225/Raisler Lounge \nFor zoom link\, contact manu@seas.upenn.edu.
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-jeremy-gunawardena/
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:20211116T100000
DTEND;TZID=America/New_York:20211116T110000
DTSTAMP:20260406T124919
CREATED:20211105T200314Z
LAST-MODIFIED:20211105T200314Z
UID:10006958-1637056800-1637060400@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Flying Modular Robots: From Self-Assembling Structures in Midair to Embedding Grasping Capabilities"
DESCRIPTION:Flying modular robots offer a suitable autonomous platform for multiple applications such as: search and rescue\, cargo lifting\, and object transportation. In addition\, modular robots in a swarm can use their own bodies as building units to assemble large structures. This thesis introduces ModQuad\, the self-assembly structure that can cooperatively fly based on autonomous modules. With these modules it is possible to assemble structures with rigid connections in multiple configurations. In contrast to related work\, instead of assembling on the ground or on water\, a midair approach to assemble structures is proposed. Docking modules in midair offer relevant advantages by the cost of the complexity to adapt the conglomerate controller at each docking step. Assembling structures in midair usually requires a relative localization system in between modules. A vision-based self-assembly method is proposed with structures composed of two modules. Scaling these flying modular robotic structures is a challenging problem usually limiting the benefits of modularity. A novel yaw actuation for quadrotor-based modules using individuals rolling angles by a one degree of freedom cage design is proposed for a more effective controllability around the structure z-axis. The resulting implementation enlarges the configuration space in a line configuration. Expanding the one degree of freedom cage design to arbitrary configurations allowed the development of algorithms capable of generating optimal and near-optimal configurations through a computational efficient search that first classifies and groups modules within the structure. Lastly\, structures composed of non-rigid connections are explored leading the whole conglomerate to change its shape dynamically in-flight. Instead of adding extra components and mechanisms\, versatility of modularity is utilized to embed grasping capabilities through a shape change addressed to a four-bar linkage configuration.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-flying-modular-robots-from-self-assembling-structures-in-midair-to-embedding-grasping-capabilities/
LOCATION:Zoom – Email MEAM for Link\, peterlit@seas.upenn.edu
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:20211116T120000
DTEND;TZID=America/New_York:20211116T130000
DTSTAMP:20260406T124919
CREATED:20211112T181029Z
LAST-MODIFIED:20211112T181029Z
UID:10006966-1637064000-1637067600@seasevents.nmsdev7.com
SUMMARY:PICS Alumni Spotlight: Dr. Xuran Wang\, Postdoctoral Researcher at Carnegie Mellon University
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/pics-alumni-spotlight-dr-xuran-wang-postdoctoral-researcher-at-carnegie-mellon-university/
LOCATION:Zoom – email kathom@seas.upenn.edu
CATEGORIES:Alumni
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211116T150000
DTEND;TZID=America/New_York:20211116T161500
DTSTAMP:20260406T124919
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
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20211117T110000
DTEND;TZID=America/New_York:20211117T120000
DTSTAMP:20260406T124920
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:20211117T163000
DTEND;TZID=America/New_York:20211117T173000
DTSTAMP:20260406T124920
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:20211118T120000
DTEND;TZID=America/New_York:20211118T133000
DTSTAMP:20260406T124920
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:20211118T153000
DTEND;TZID=America/New_York:20211118T163000
DTSTAMP:20260406T124920
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:20211118T153000
DTEND;TZID=America/New_York:20211118T163000
DTSTAMP:20260406T124920
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:20211119T100000
DTEND;TZID=America/New_York:20211119T120000
DTSTAMP:20260406T124920
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:20211119T103000
DTEND;TZID=America/New_York:20211119T114500
DTSTAMP:20260406T124920
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:20211119T133000
DTEND;TZID=America/New_York:20211119T143000
DTSTAMP:20260406T124920
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:20211120T150000
DTEND;TZID=America/New_York:20211120T160000
DTSTAMP:20260406T124920
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
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