BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240313T150000
DTEND;TZID=America/New_York:20240313T160000
DTSTAMP:20260403T173601
CREATED:20240307T231327Z
LAST-MODIFIED:20240307T231327Z
UID:10918-1710342000-1710345600@seasevents.nmsdev7.com
SUMMARY:Spring 2024 GRASP SFI: Joseph DelPreto\, Massachusetts Institute of Technology\, "Using Sensing and AI to Enrich Human Interactions with Machines and Nature"
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nCoupling advanced wearable and environmental sensors with dynamic AI frameworks has the potential to transform how we engage with machines and with the natural world.  By co-developing intelligent sensors and deployable machine learning pipelines\, we can unlock the power of data to address impactful challenges in fields ranging from human-robot collaboration to environmental science.  Realizing this vision will require a multifaceted approach including networks that extract insights from large streams of continuous data\, algorithms that adapt to new subjects or environments from limited examples\, unobtrusive sensing with embedded autonomy\, scalable multimodal dataset curation\, and paradigms for fluid human interactions with AI systems.  Moving towards these goals\, this talk will present approaches to creating more intelligent and fluid human-robot interactions by leveraging wearable sensors for brain\, muscle\, and motion activity combined with adaptive learning pipelines.  It will explore how these techniques can scale to curate multimodal datasets of human behavior that aim to support foundational models of physical intelligence.  To help improve sensing capabilities\, it will also discuss techniques for creating soft wearable sensors with embedded learning pipelines.  Finally\, recent results of using wearable and deployable sensors to study non-human species will be introduced; combining robust wearable sensor tags\, drones\, and new machine learning pipelines can reveal exciting insights into the language and culture of sperm whales.
URL:https://seasevents.nmsdev7.com/event/spring-2024-grasp-sfi-joseph-delpreto/
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
END:VEVENT
END:VCALENDAR