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DTSTART;TZID=America/New_York:20221114T100000
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DTSTAMP:20260405T142349
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UID:10007355-1668420000-1668427200@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Analysis and Control of Neural Network Dynamical Systems"
DESCRIPTION:Integrating machine learning and control systems has achieved remarkable success in controlling complex dynamical systems such as autonomous vehicles. However\, the resulting controlled system often has a neural network (NN) in the loop which represents the system dynamics\, control policy\, or perception. The nonlinearity and large scale of NNs make it challenging to provide formal safety or stability guarantees for such learning-enabled systems. This thesis focuses on developing specialized numerical tools for efficiently analyzing NN dynamical systems and a novel robust model predictive control (MPC) framework that is promising for controlling NN dynamical systems with safety guarantees. In the first part of the thesis\, I demonstrate how to build a hierarchy of verification methods for isolated output range analysis of NNs\, closed-loop reachability analysis\, and closed-loop stability analysis of NN dynamical systems. In the second part\, I present a novel robust MPC method for uncertain linear dynamical systems with significantly reduced conservatism compared with existing baselines and discuss the possibility of combining NN verification tools and robust MPC for safe control of complex dynamical systems.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-analysis-and-control-of-neural-network-dynamical-systems/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
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:20221114T150000
DTEND;TZID=America/New_York:20221114T160000
DTSTAMP:20260405T142349
CREATED:20220930T205411Z
LAST-MODIFIED:20220930T205411Z
UID:10007314-1668438000-1668441600@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Enabling Ultra-Low Viscosity Lubricants Through Fundamental Understanding of ZDDPs Anti-Wear Additives and their Tribofilm Growth Mechanisms: An In-Situ Study"
DESCRIPTION:Lubricants with low viscosity have the potential to improve fuel efficiency in engines due to friction reduction. However\, a reduction in viscosity increases the likelihood of wear. Zinc dialkyldithiophosphate (ZDDP)\, the most widely used antiwear additive in engine oils\, has been extensively studied over the last few decades. ZDDP forms surface-bound tribofilms at sliding contacts that prevent surface wear. Recent studies reveal that mechanochemical reactions drive tribofilm growth via stress and temperature. However\, the individual effects of shear stress\, compressive stress\, and temperature on tribofilm growth are not yet fully understood. \nIn this study\, we investigate the kinetic of ZDDP tribofilm formation on both microscale and nanoscale. In the microscale\, we studied the driving factors separately by using different compositions of a high-viscosity\, high-traction fluid mixed with a polyalphaolefin (PAO) basestock with a ball-on-disc tribometer in the elastohydrodynamic lubrication regime. In addition\, we presented a new approach\, the strip analysis method\, to deconvolute the mechanisms under one single contact more effectively and efficiently. In the nanoscale\, we used an atomic force microscope (AFM) to simulate a single asperity contact sliding on an iron oxide surface with droplets containing alkylated naphthalene (AN)\, PAO\, and ZDDP. This enables us to investigate the mechanochemistry of ZDDP tribofilm formation in the boundary lubrication regime with a well-controlled contact.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-enabling-ultra-low-viscosity-lubricants-through-fundamental-understanding-of-zddps-anti-wear-additives-and-their-tribofilm-growth-mechanisms-an-in-situ-study/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Dissertation or Thesis Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221115T100000
DTEND;TZID=America/New_York:20221115T113000
DTSTAMP:20260405T142349
CREATED:20221018T132327Z
LAST-MODIFIED:20221018T132327Z
UID:10007335-1668506400-1668511800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Cell Packings and Tissue Flows in Developing Embryos"
DESCRIPTION:During embryonic development\, groups of cells reorganize into functional tissues with complex form and structure. Tissue reorganization can be rapid and dramatic\, often occurring through striking embryo-scale flows that are mediated by the coordinated actions of hundreds or thousands of cells. In Drosophila\, cell rearrangements in the embryonic epithelium rapidly narrow and elongate the tissue\, producing a tissue flow that doubles the length of the body axis in just 30 minutes. These types of tissue movements can be driven by internal forces generated by the cells themselves or by external forces. While much is known about the molecules involved in these cell and tissue movements\, it is not yet clear how these molecules work together to coordinate cell behaviors\, give rise to emergent tissue mechanics\, and generate coherent flows at the embryo scale. To gain mechanistic insight into this problem\, my lab combines genetic and biophysical approaches with emerging optogenetic technologies for manipulating molecular and mechanical activities inside cells with high precision. I will discuss some of our recent findings on how cellular properties and mechanical forces are regulated in the Drosophila embryo to allow (or prevent) rapid cell rearrangements and tissue flows during specific events in embryonic development.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-cell-packings-and-tissue-flows-in-developing-embryos/
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:20221115T103000
DTEND;TZID=America/New_York:20221115T113000
DTSTAMP:20260405T142349
CREATED:20221104T165639Z
LAST-MODIFIED:20221104T165639Z
UID:10007352-1668508200-1668511800@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium - "Using Information Geometry to Find Simple Models of Complex Processes"
DESCRIPTION:Effective theories play a fundamental role in how we reason about the world. Although real physical processes are very complicated\, useful models abstract away the irrelevant degrees of freedom to give parsimonious representations. In contrast\, overly complex models can be difficult to evaluate\, suffer from numerical instabilities\, and may overfit data. They also obscure useful insights into the relationship among different physical systems. I use information geometry to explore the role of simplicity in scientific explanation. I interpret a multi-parameter model as a manifold embedded in the space of all possible data\, with a metric induced by statistical distance. These manifolds are often bounded and very thin\, so they are well-approximated by a low-dimensional\, simple model. For many types of models\, there is a hierarchy of natural approximations that reside on the manifold’s boundary. These approximations are not black-boxes. They remain expressed in terms of the relevant combinations of mechanistic parameters and reflect the physical principles on which the complicated model was built. They can also be constructed systematically using computational differential geometry\, as I illustrate with examples from physics and systems biology
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-using-information-geometry-to-find-simple-models-of-complex-processes/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221115T120000
DTEND;TZID=America/New_York:20221115T133000
DTSTAMP:20260405T142349
CREATED:20221111T214536Z
LAST-MODIFIED:20221111T214536Z
UID:10007359-1668513600-1668519000@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense - "Learning and Control of Network Phenomena"
DESCRIPTION:The intersection of dynamical systems and networks are used to model a huge variety of phenomena such as the spread of disease\, multi-agent systems\, opinions in social networks\, and more. Many properties of these network phenomena can be understood by examining the eigenvalue spectrum of a matrix representation of the underlying graph. Using this intuition\, this thesis explores the learning and control of network phenomena. First\, I present techniques for matching individuals across correlated networks and learning the spectra of a graph matrix using only the sparse output measurements of a networked dynamical system with periodic inputs. Next\, I present a data-driven framework for multi-task learning and non-linear control of epidemics. Finally\, I propose a new architecture for signal processing on higher-order graphs\, along with a new transferability bound on the performance of graph neural networks via spectral similarity. This transferability result is valid for arbitrary graphs regardless of their structure\, resulting in the first bound on the transferability of a machine learning approach for higher-order graphs.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-learning-and-control-of-network-phenomena/
LOCATION:Room 401B\, 3401 Walnut\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
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:20221115T153000
DTEND;TZID=America/New_York:20221115T163000
DTSTAMP:20260405T142349
CREATED:20221101T190036Z
LAST-MODIFIED:20221101T190036Z
UID:10007349-1668526200-1668529800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Generative multitask learning mitigates target-causing confounding"
DESCRIPTION:We propose a simple and scalable approach to causal representation learning for multitask learning. Our approach requires minimal modification to existing ML systems\, and improves robustness to prior probability shift. The improvement comes from mitigating unobserved confounders that cause the targets\, but not the input. We refer to them as target-causing confounders. These confounders induce spurious dependencies between the input and targets. This poses a problem for the conventional approach to multitask learning\, due to its assumption that the targets are conditionally independent given the input. Our proposed approach takes into account the dependency between the targets in order to alleviate target-causing confounding. All that is required in addition to usual practice is to estimate the joint distribution of the targets to switch from discriminative to generative classification\, and to predict all targets jointly. Our results on the Attributes of People and Taskonomy datasets reflect the conceptual improvement in robustness to prior probability shift.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-generative-multitask-learning-mitigates-target-causing-confounding/
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:20221116T100000
DTEND;TZID=America/New_York:20221116T110000
DTSTAMP:20260405T142349
CREATED:20221103T143130Z
LAST-MODIFIED:20221103T143130Z
UID:10007350-1668592800-1668596400@seasevents.nmsdev7.com
SUMMARY:Fall 2022 GRASP SFI: Yasuo Kuniyoshi\, University of Tokyo\, "Behavior and Cognition Emerge and Develop From Embodiment - A Constructive Study of Human Fetus/Infant"
DESCRIPTION:This is a hybrid event with in-person attendance in Raisler Lounge (Towne 225) and virtual attendance via Zoom. This talk will NOT be recorded\, please make sure to arrive on time. \nABSTRACT\nIn this talk\, I will first show that physics of human-like body in action already provide certain information structure which can set the natural basis of categorization and meaning. \nThen\, I will show a principle of autonomous exploration that reveals the embodied information structure\, aka. body affordances. Coordinated motor patterns consistent with the embodiment emerge from multiple chaotic elements coupled through body-environment physics. \nIn humans\, the above principle may drive early motor development. And the resulting sensory-motor information can be captured by self-organizing neural circuits\, forming the basis of cognitive structures. \nIn order to investigate this hypothetical scenario\, we constructed a simulation model of a human fetus. It consists of a musculo-skeletal body\, whole body cutaneous receptors (tactile)\, uterus and amniotic fluid\, neuronal model of spine and medulla\, and a whole neocortex model with self-organizing neural network. \nWith very little “innate” functional neural circuits\, the model acquired various behavior patterns that comply with its embodiment\, and the neural model self organizes to capture the embodied information structure. It exhibits spontaneous motor development and sensory-motor map organization comparable to human data. Also\, by changing the model parameters\, we can simulate “atypical” development. \nOur series of experiments shows that sensory-motor experiences in the fetal period can be crucial to the formation of body representations and multi-modal sensory integration\, which are significantly affected under “preterm birth” conditions\, providing new insights about the developmental origins of social cognition and autism spectrum disorders.\nImplications for the next generation AI/robotics will also be discussed if time allows.
URL:https://seasevents.nmsdev7.com/event/fall-2022-grasp-sfi-yasuo-kuniyoshi-university-of-tokyo-behavior-and-cognition-emerge-and-develop-from-embodiment-a-constructive-study-of-human-fetus-infant/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221116T120000
DTEND;TZID=America/New_York:20221116T133000
DTSTAMP:20260405T142349
CREATED:20220909T155422Z
LAST-MODIFIED:20220909T155422Z
UID:10007267-1668600000-1668605400@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: Building Safe Autonomous Systems\, Rahul Mangharam (University of Pennsylvania)
DESCRIPTION:ABSTRACT: \nBalancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular\, autonomous racing is a domain that penalizes safe but conservative policies\, highlighting the need for robust\, adaptive strategies. Current approaches either make simplifying assumptions about other agents or lack robust mechanisms for online adaptation. In this talk we will explore research themes on perception\, planning and control at the limits of performance. We explore (1) How to generate the most competitive agents who dynamically balance safety and assertiveness by using distributionally robust online adaptation; (2) How to build the most efficient autonomous racecar with Multi-domain optimization across vehicle design\, planning and control; (3) How to combine previous system designs to auto-complete new designs with new requirements\, and (4) Understand the value of Cooperation in Multi-Agent Games. We realize all our research in the https://f1tenth.org autonomous racecar platform that is 10th the size\, but 10x the fun! The main takeaway from this talk is how you can get involved in very exciting research on safe autonomous systems.  I will also present projects on AV Gokart that we are doing in the Autoware Center of Excellence for Autonomous Driving at Pennovation.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-building-safe-autonomous-systems-rahul-mangharam-university-of-pennsylvania/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221117T103000
DTEND;TZID=America/New_York:20221117T233000
DTSTAMP:20260405T142349
CREATED:20221028T134231Z
LAST-MODIFIED:20221028T134231Z
UID:10007347-1668681000-1668727800@seasevents.nmsdev7.com
SUMMARY:MSE Seminar: “Advanced Microscopy Techniques for Understanding Dislocation Interactions & Damage in Complex Microstructures”
DESCRIPTION:Microstructurally and compositionally complex alloys (MCCA) such as Nickel-Aluminum-Bronze (NAB) are important to Navy and maritime applications due to their high strength\, toughness\, and fatigue resistance\, as well as excellent corrosion resistance. NAB’s are widely used in many naval applications including ship propellers\, underwater fasteners\, pumps\, and valves. Traditional sand cast NAB alloys tend to have a large amount of waste material\, and reduced complexity in component geometry due to the limitations of the casting processing.  As a result\, NAB alloys are emerging as a viable alloy for additive manufacturing (AM) and therefore provides a new space to establish fundamental relationships between AM processing\, structure and properties. Of the additive processes\, wire arc additive manufacturing (WAAM) is an evolving technology for fabricating large-scale\, near net shape NAB components. It is understood that the high cooling rates achieved in WAAM prevent the precipitation of coarse rosette-like kI phase which usually form during the latter stages of solidification during the casting process. In this work\, the dislocation interactions with interfaces such as grain boundaries and precipitates will be used to understand fatigue life and crack initiation and growth behavior in these alloys during low-cycle and high-cycle fatigue.
URL:https://seasevents.nmsdev7.com/event/mse-seminar-advanced-microscopy-techniques-for-understanding-dislocation-interactions-damage-in-complex-microstructures/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221117T123000
DTEND;TZID=America/New_York:20221117T133000
DTSTAMP:20260405T142349
CREATED:20221104T144409Z
LAST-MODIFIED:20221104T144409Z
UID:10007351-1668688200-1668691800@seasevents.nmsdev7.com
SUMMARY:ESE Fall Colloquium - "Micro- and Nanoscale Electro-fluidics: From Basic Research to Translational Medicine"
DESCRIPTION:In this talk\, I will discuss my group’s work on fabricating micro- and nanosensing platforms for health monitoring. My group has developed novel electronic sensing modalities and has demonstrated their use for both in vitro with human clinical samples and in vivo in animals. In the first part of my talk\, I will discuss sensor fabrication\, characterization\, and benchmarking against the gold standard\, along with the role that these sensors can play in monitoring various chronic and acute inflammatory conditions. I will also discuss a new class of wirelessly powered nanobiosensors for immune monitoring. Finally\, I will discuss challenges in translation of biosensing and microfluidic technologies beyond the lab\, my personal experience\, and potential solutions.
URL:https://seasevents.nmsdev7.com/event/ese-fall-colloquium-micro-and-nanoscale-electro-fluidics-from-basic-research-to-translational-medicine/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221117T150000
DTEND;TZID=America/New_York:20221117T170000
DTSTAMP:20260405T142349
CREATED:20221114T204428Z
LAST-MODIFIED:20221114T204428Z
UID:10007364-1668697200-1668704400@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense - "Accelerating HLS Autotuning of Large\, Highly-Parameterized Reconfigurable SoC Mappings"
DESCRIPTION:High-level synthesis has accelerated the adoption of autotuners to explore design spaces. Design-space size increases exponentially in the number of design parameters\, and synthesizing a single configuration for a device-scale application easily consumes hours\, so existing autotuners are frequently demonstrated with small kernels and few configurations to render the problem tractable. This dissertation shows that exploration of applications with more than 25 parameters mapped on reconfigurable SoCs exceeding 200K LUTs becomes feasible using the model-based approach we refine. We explore various techniques to reduce the tuning time. At the heart of our tuner are multi-fidelity models\, which enable discontinuation of unpromising builds in multi-stage CAD flows. We rearranged the build resources in a pipeline to improve the tuning performance and increase the utilization of build resources. Build failures and underperforming configurations are avoided using latency\, area\, critical path delay\, congestion\, error probability\, and build time prediction models. Next\, we introduce a novel model that combines the preexisting hierarchical and multi-fidelity models. The hierarchical model enables the decomposition of design spaces into exponentially smaller subspaces that can be explored faster. Also novel is the use of out-of-context compilation to lower the build time further. A tree-based model alleviates the long training times of Gaussian process models. To validate our approach\, we injected 29 – 44 parameters\, varying from compiler pragmas to CAD tool parameters\, in the Rosetta benchmarks. Compared to non-pipelined multi-fidelity Bayesian optimization\, our tuner succeeds 20% more often at finding mappings on the ZCU102\, and tuning runs are on average at least 2.2x shorter. Moreover\, it locates 3.6x faster solutions within 24 hours.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-accelerating-hls-autotuning-of-large-highly-parameterized-reconfigurable-soc-mappings/
LOCATION:Room 35\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
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:20221117T153000
DTEND;TZID=America/New_York:20221117T163000
DTSTAMP:20260405T142349
CREATED:20220812T145111Z
LAST-MODIFIED:20220812T145111Z
UID:10007226-1668699000-1668702600@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "Developments in Stem Cell-Derived Islets for Diabetes Cell Replacement Theory" (Jeffrey R. Millman\, Washington University School of Medicine)
DESCRIPTION:This is a hybrid seminar which will be held in Glandt Forum (Singh Center) and via Zoom (link coming soon). \n“Developments in Stem Cell-Derived Islets for Diabetes Cell Replacement Theory” \nCellular and tissue engineering promises new therapeutic options for people suffering from a wide range of diseases. Differentiation of stem cells is a powerful renewable source of these functional replacement cells and tissues that can be grown in the laboratory. Diabetes is cause by the death or dysfunction of insulin-secreting islets\, which are a tissue type found in the pancreas that contain β cells and other endocrine cell types. We have recently developed approaches combining modulating the actin cytoskeleton and signal transduction pathways during differentiation to produce stem cell-derived islets (SC-islets) capable of undergoing glucose-stimulated insulin secretion\, their primary function. We have further expanded this approach to make SC-islets from patients with diabetes and used CRISPR-Cas9 to correct their diabetes-causing mutations. Upon transplantation into mice with severe pre-existing diabetes\, these SC-islets rapidly restore normoglycemia and can maintain this functional cure for a year. Our hope is that one day this technology can be used to replace unhealthy islets in patients for therapy and provide a better disease-in-a-dish model to discover new drugs to prevent\, stop\, or reverse diabetes progression.
URL:https://seasevents.nmsdev7.com/event/be-seminar-developments-in-stem-cell-derived-islets-for-diabetes-cell-replacement-theory-jeffrey-r-millman-washington-university-school-of-medicine/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221117T153000
DTEND;TZID=America/New_York:20221117T170000
DTSTAMP:20260405T142349
CREATED:20221025T143056Z
LAST-MODIFIED:20221025T143056Z
UID:10007341-1668699000-1668704400@seasevents.nmsdev7.com
SUMMARY:A Celebration of the Life of Dr. Max Mintz
DESCRIPTION:The CIS Department and GRASP Lab invite you to please join us on Thursday\, November 17th\, at 3:30pm as we celebrate the life and legacy of Dr. Max Mintz\, Professor of Computer and Information Science. \nMax joined Penn as an assistant professor of Systems Engineering (now part of ESE) in 1974. He changed his primary appointment to Computer and Information Science in 1986\, and he was an important part of CIS undergraduate education and advising for 36 years. His research in Penn’s GRASP Lab focused on developing robust algorithms for decision-making under uncertainty with applications to machine perception and robotics. Max was a legendary teacher\, an extraordinary advisor\, and an inspiration to his students\, encouraging them to go well beyond their comfort level in their academic preparation and homework. He won numerous awards including the S. Reid Warren\, Jr. Award\, the University’s Lindback Award\, and the Ford Motor Company Award for Distinguished Advising.  \nA memorial celebration will be held in the Wu and Chen Auditorium of Levine Hall\, followed by a reception. We hope you can attend. \n*If you would like to attend\, please RSVP here!\n*If you’d like to submit photos of Dr. Mintz to be shared during the event\, please upload them here!\n*To attend virtually\, please join via Zoom here.\n*Full details on the schedule and event may be found here. \n\n~~~~~~~~~~~~~~~~~~~~~~ \n \n\nABOUT Dr. Max Mintz:\nMax Mintz was born on September 4th\, 1942\, and grew up outside of New York City.  He received bachelor’s and master’s degrees in Electrical Engineering at Cornell University and then completed a Ph.D. in Systems Theory in 1968. He then joined Yale University\, first as a post-doc and then as an Assistant Professor in Control Theory and Electrical Engineering.  He subsequently taught at the University of Illinois for two years before joining the Systems Engineering department (now part of Electrical and Systems Engineering) at the University of Pennsylvania in 1974.  In 1984\, at the invitation of Ruzena Bajcsy\, he joined the GRASP Lab\, and in 1986 he switched his primary affiliation to the Department of Computer and Information Science. \nAs an integral member of the GRASP Lab\, Dr. Mintz’s research focused on control theory with stochastic systems.  He developed robust algorithms for decision-making under uncertainty with applications to machine perception and robotics\, combining ideas from mathematics\, physics\, and game theory.  Later in his career\, he turned his attention to quantum computing\, and especially how to teach it in a way that was accessible to undergraduates. \nDr. Mintz was a legendary teacher\, an extraordinary advisor\, and an inspiration to his students\, encouraging them to go well beyond their comfort level in their academic preparation and homework. He played an important part of CIS undergraduate education and advising for 36 years\, winning numerous awards for these efforts\, including the S. Reid Warren\, Jr. Award\, the University’s Lindback Award\, and the Ford Motor Company Award for Distinguished Advising. \n*Full details on the schedule and event may be found here.
URL:https://seasevents.nmsdev7.com/event/dr-max-mintzs-celebration-of-life/
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:20221118T100000
DTEND;TZID=America/New_York:20221118T120000
DTSTAMP:20260405T142349
CREATED:20221110T165744Z
LAST-MODIFIED:20221110T165744Z
UID:10007358-1668765600-1668772800@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense - "Robustness of Temporal Logics with Applications to Safe Autonomy"
DESCRIPTION:Signal Temporal Logic (STL) is a common way to express a broad range of real-time constraints that can be imposed on control systems. Spatial robustness of STL specifications\, quantifying permissible spatial perturbations\, has been widely studied in the literature. However\, despite the importance of various time-critical systems\, temporal robustness of STL has not yet been studied in depth nor has been used for control design. \nIn the first part of this thesis\, we establish a comprehensive theoretical framework for temporal robustness of STL. We define synchronous and asynchronous temporal robustness and show that these notions quantify the robustness with respect to synchronous and asynchronous time shifts in the predicates of the underlying signal temporal logic specification. We further prove that synchronous temporal robustness upper bounds asynchronous temporal robustness. Moreover\, we show under which conditions these two robustness notions are equivalent. Introduced synchronous and asynchronous notions are directional and consider either left or right perturbations. Due to this reason we additionally define and study the combined temporal robustness which simultaneously considers left and right time shifts. \nIn the second part of this thesis\, we focus on applications of various robustness functions to robust planning and control design questions. We first propose solutions to the temporally-robust control synthesis problem by presenting Mixed-Integer Linear Programming (MILP) encodings for derived temporal robustness notions. Second\, we solve the spatially-robust control synthesis problem and show how to adapt the smooth operator for space robustness maximization. Furthermore\, we propose possible distributed solutions to centralized multi-agent planning problems. Through various simulations\, as well as experiments on actual robotic systems\, we show that our presented solutions are computationally efficient as well as can be used in a wide variety of applications.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-robustness-of-temporal-logics-with-applications-to-safe-autonomy/
LOCATION:Zoom – Meeting ID 564 482 9525
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221118T103000
DTEND;TZID=America/New_York:20221118T114500
DTSTAMP:20260405T142349
CREATED:20220830T155052Z
LAST-MODIFIED:20220830T155052Z
UID:10007238-1668767400-1668771900@seasevents.nmsdev7.com
SUMMARY:Fall 2022 GRASP on Robotics: Julie Adams\, Oregon State University\, "Towards Adaptive Human-Robot Teams: Workload Estimation"
DESCRIPTION:This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom. \n  \nABSTRACT\nThe ability for robots\, be it a single robot\, multiple robots or a robot swarm\, to adapt to the humans with which they are teamed requires algorithms that allow robots to detect human performance in real time. The multi-dimensional workload algorithm incorporates physiological metrics to estimate overall workload and its components (i.e.\, cognitive\, speech\, auditory\, visual and physical). The algorithm is sensitive to changes in a human’s individual workload components and overall workload across domains\, human-robot teaming relationships (i.e.\, supervisory\, peer-based)\, and individual differences. The algorithm has also been demonstrated to detect shifts in workload in real-time in order to adapt the robot’s interaction with the human and autonomously change task responsibilities when the human’s workload is over- or underloaded. Recently\, the algorithm was used to post-hoc analyze the resulting workload for a single human deploying a heterogeneous robot swarm in an urban environment. Current efforts are focusing on predicting the human’s future workload\, recognizing the human’s current tasks\, and estimating workload for previously unseen tasks.
URL:https://seasevents.nmsdev7.com/event/grasp-on-robotics-julie-adams/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221118T113000
DTEND;TZID=America/New_York:20221118T133000
DTSTAMP:20260405T142349
CREATED:20221115T162357Z
LAST-MODIFIED:20221115T162357Z
UID:10007365-1668771000-1668778200@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense - "Modeling and Control of Dynamic Behavior of Spreading Processes on Networks"
DESCRIPTION:Epidemiological spreading processes constitute the core of a large number of disparate networks. In some\, faster spread is desirable\, in others containing the spread is critically important. We focus on understanding the spatio-temporal spread of epidemics over contact networks with the goal of facilitating or containing the spread as the case may be. In this study\, we choose specific systems as exemplars of instances where the spread is desirable (e.g.\, Vehicle-to-Everything; V2X) and others where the spread is harmful (e.g.\, spread of infectious diseases). \nIn transportation systems\, vehicles are expected to exchange messages with each other and with bikers\, pedestrians\, wheelchairs (Vehicle-to-Vehicle; V2V) and with signaling infrastructure on the roadways (Infrastructure-to-Vehicle; I2V) (together\, V2X). We seek to qualitatively understand and subsequently quantitatively model the impact of complex\, various interdependencies between wireless communication (spread of information through evolving links) and vehicular mobility (spatial movements of nodes). Towards this end\, we introduce epidemiological modeling into transportation systems\, a novel concept geared towards V2X\, in which the computations remain tractable even for large\, complex transportation networks. We additionally accommodate arbitrary traffic synchronization patterns corresponding for example to the presence of an arbitrary number of traffic signals. Furthermore\, numerical computations using our mathematical framework reveal several questions that influence the practice of V2X network design and security. \nNext\, suppressing spread of infectious diseases is clearly of critical importance. Recently COVID-19 pandemic has wrecked havoc on lives and livelihoods worldwide. We explore the costs and benefits of a new tracing and testing concept towards containing COVID-19. We propose to preemptively identify the contact chain by testing primary\, secondary\, tertiary or further-off contacts of those who test positive\, more specifically\, the k-hop contacts for a parameter k of choice. We evaluate the costs and benefits of this novel multi-hop testing strategy for various reported disease parameters and on diverse human contact patterns\, and see if the cost-benefit tradeoffs may be substantially enhanced through the deployment of the strategy. Furthermore\, we propose an analytical methodology for evaluating multi-hop contact tracing strategy by combining the multi-hop contact tracing dynamics and the virus transmission mechanism in a single framework using microscopic Markov Chain approach.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-modeling-and-control-of-dynamic-behavior-of-spreading-processes-on-networks/
LOCATION:Greenberg Lounge (Room 114)\, Skirkanich Hall\, 210 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
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:20221118T134500
DTEND;TZID=America/New_York:20221118T151500
DTSTAMP:20260405T142349
CREATED:20221114T145343Z
LAST-MODIFIED:20221114T145343Z
UID:10007361-1668779100-1668784500@seasevents.nmsdev7.com
SUMMARY:MSE Special Seminar: “From sustainable Flooring to Sustainable Business: What you Don’t Learn in School”
DESCRIPTION:In this open conversation\, he will share his experience as a glass-ceiling breaking executive who has successfully built the HMTX from a small retailer to a business of $800M revenue focusing on Manufacturing Efficiency\, Durability\, and Sustainability.
URL:https://seasevents.nmsdev7.com/event/mse-special-seminar-from-sustainable-flooring-to-sustainable-business-what-you-dont-learn-in-school/
LOCATION:David Rittenhouse Lab\, A4\, 209 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221118T140000
DTEND;TZID=America/New_York:20221118T160000
DTSTAMP:20260405T142349
CREATED:20221114T154310Z
LAST-MODIFIED:20221114T154310Z
UID:10007362-1668780000-1668787200@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics" (Nishal Shah)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. David Issadore are pleased to announce the Doctoral Dissertation Defense of Nishal Shah.\n\nTitle:  High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics.\nDate:  November 18\, 2022\nTime: 2:00 pm\nLocation:  Towne 217 ALC\nor via Zoom\, link below\n\n\nhttps://upenn.zoom.us/j/93933189939\n\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-high-throughput-microfluidics-for-ultrasensitive-blood-based-diagnostics-nishal-shah/
LOCATION:towne 217
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
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END:VCALENDAR