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DTSTART;TZID=America/New_York:20240305T100000
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DTSTAMP:20260403T192135
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SUMMARY:MEAM Seminar: "Dexterous Decision-Making for Real-World Robotic Manipulation"
DESCRIPTION:For a robot to prepare a meal or clean a room\, it must make a large array of decisions\, such as what objects to clean first\, where to grasp each ingredient and tool\, how to open a heavy\, overstuffed cabinet\, and so on. To enable robots to tackle these tasks\, I decompose the problem into two interdependent layers: generating a series of subgoals (i.e.\, a strategy) and solving for the robot behavior that achieves each of these subgoals. Critically\, to accomplish a rich set of manipulation tasks\, these subgoal solvers must account for force\, motion\, deformation\, contact\, uncertainty and partial observability. \nMy research contributes models and algorithms that enable robots to reason over both the geometry and physics of the world in order to solve long-horizon manipulation tasks. In this talk\, I will first discuss how this approach has enabled robots to perform tasks that require reasoning over and exerting force\, like opening a childproof medicine bottle with a single arm. Next\, I will present an abstraction for the complex physics of frictional pushing and demonstrate its application within the context of in-hand manipulation. Finally\, I will illustrate how robots can make robust choices in the face of uncertainty. For example\, this empowers robots to reliably chop up fruit of unknown ripeness!
URL:https://seasevents.nmsdev7.com/event/meam-seminar-dexterous-decision-making-for-real-world-robotic-manipulation/
LOCATION:Towne 337
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
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DTSTART;TZID=America/New_York:20240307T100000
DTEND;TZID=America/New_York:20240307T113000
DTSTAMP:20260403T192135
CREATED:20240229T202200Z
LAST-MODIFIED:20240229T202200Z
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SUMMARY:MEAM Seminar: "Active Materials and Devices for Biomedical Applications"
DESCRIPTION:In this talk\, I will discuss our recent work in materials fabrication\, manipulation\, assembly\, and manufacturing tailored towards biomedical and environmental applications. The focus is on active materials and devices enabled by materials control across a wide range of length scales. At the nanoscale\, I will discuss 3D electrokinetic tweezers\, an ultra-precision tool developed in my lab\, which can be used to manipulate nanowires in room-temperature aqueous solutions. With this technique\, designed nanostructures are maneuvered as untethered robotic tools for probing single biological cells; the precision reaches 20 nm in position and 0.5° in orientation in water solution with a standard microscope. At a slightly larger\, chip-scale\, I will describe a recent innovation that permits the light-controlled patterning of soft actuators made of microbubbles\, which assemble large arrays of nanoparticles in parallel. The co-assembly of nanosensor-cell hybrids can be further achieved that detect metabolites of bacterial cells. Finally\, I will present a rational scheme for developing large-scale\, hierarchically porous superstructures for applications in monitoring human health and public-health relevant water treatment.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-active-materials-and-devices-for-biomedical-applications/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240307T153000
DTEND;TZID=America/New_York:20240307T163000
DTSTAMP:20260403T192135
CREATED:20240108T172031Z
LAST-MODIFIED:20240108T172031Z
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SUMMARY:BE Seminar: "Charting the future of RNA and protein sequence-structure exploration" (Kalli Kappel\, MIT/Harvard)
DESCRIPTION:RNA and protein sequences dictate their structures\, spanning multiple length scales\, from molecular conformations to patterns of subcellular localization. In turn\, these structures govern biological function. Characterizing sequence-structure relationships is critical for gaining mechanistic understanding\, but conventional techniques can be slow and low-throughput. We have developed integrated computational and experimental methods to overcome these limitations and have applied them to resolve the three-dimensional structures of a wide range of RNA molecules and RNA-protein complexes\, and to systematically reveal the protein sequence features that drive condensate formation in cells. This work paves the way for the development of transformative predictive models of RNA and protein sequence-structure relationships.
URL:https://seasevents.nmsdev7.com/event/be-seminar-kalli-kappel-mit-harvard/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240308T140000
DTEND;TZID=America/New_York:20240308T150000
DTSTAMP:20260403T192135
CREATED:20240301T205716Z
LAST-MODIFIED:20240301T205716Z
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SUMMARY:Spring 2024 GRASP Seminar: Yutong Bai\, Johns Hopkins University\, "Listening to the Data: Visual Learning from the Bottom Up"
DESCRIPTION:*This seminar will be held in-person in Levine 307 with virtual attendance via Zoom.  \nABSTRACT\nWe introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data. To do this\, we define a common format\, “visual sentences”\, in which we can represent raw images and videos as well as annotated data sources such as semantic segmentations and depth reconstructions without needing any meta-knowledge beyond the pixels. Once this wide variety of visual data (comprising 420 billion tokens) is represented as sequences\, the model can be trained to minimize a cross-entropy loss for next token prediction. By training across various scales of model architecture and data diversity\, we provide empirical evidence that our models scale effectively. Many different vision tasks can be solved by designing suitable visual prompts at test time.
URL:https://seasevents.nmsdev7.com/event/spring-2024-grasp-seminar-yutong-bai-johns-hopkins-university-listening-to-the-data-visual-learning-from-the-bottom-up/
LOCATION:Levine 307\, 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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