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DTSTART;TZID=America/New_York:20190506T120000
DTEND;TZID=America/New_York:20190506T130000
DTSTAMP:20260408T230113
CREATED:20190110T204334Z
LAST-MODIFIED:20190110T204334Z
UID:10006137-1557144000-1557147600@seasevents.nmsdev7.com
SUMMARY:PSOC Spring 2019 Seminar Series: Parag Mallick\, Ph.D.
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/psoc-spring-2019-seminar-series-parag-mallick-ph-d/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
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DTSTART;TZID=America/New_York:20190509T103000
DTEND;TZID=America/New_York:20190509T123000
DTSTAMP:20260408T230113
CREATED:20190430T141928Z
LAST-MODIFIED:20190430T141928Z
UID:10006216-1557397800-1557405000@seasevents.nmsdev7.com
SUMMARY:Doctoral Dissertation Defense: "Automated analysis of experience-dependent sensory response behavior in Caenorhabditis elegans"
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Christopher Fang-Yen are pleased to announce the Doctoral Dissertation Defense of Patrick McClanahan.\n\nTitle: Automated analysis of experience-dependent sensory response behavior in Caenorhabditis elegans\n\nDate: Thursday\, May 9th\, 2019\nTime: 10:30 AM\nLocation: Moore 212\n\nThe public is welcome to attend
URL:https://seasevents.nmsdev7.com/event/doctoral-dissertation-defense-automated-analysis-of-experience-dependent-sensory-response-behavior-in-caenorhabditis-elegans/
LOCATION:Moore 212
CATEGORIES:Doctoral,Student,Dissertation or Thesis Defense
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DTSTART;TZID=America/New_York:20190509T110000
DTEND;TZID=America/New_York:20190509T120000
DTSTAMP:20260408T230113
CREATED:20190423T184824Z
LAST-MODIFIED:20190423T184824Z
UID:10006214-1557399600-1557403200@seasevents.nmsdev7.com
SUMMARY:ESE & GRASP Seminar: "Efficient Computing for AI and Robotics"
DESCRIPTION:Computing near the sensor is preferred over the cloud due to privacy and/or latency concerns for a wide range of applications including robotics/drones\, self-driving cars\, smart Internet of Things\, and portable/wearable electronics. However\, at the sensor there are often stringent constraints on energy consumption and cost in addition to the throughput and accuracy requirements of the application. In this talk\, we will describe how joint algorithm and hardware design can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning\, computer vision\, autonomous navigation/exploration and video/image processing. We will show how energy-efficient techniques that exploit correlation and sparsity to reduce compute\, data movement and storage costs can be applied to various tasks including image classification\, depth estimation\, super-resolution\, localization and mapping.
URL:https://seasevents.nmsdev7.com/event/ese-seminar-efficient-computing-for-ai-and-robotics/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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