BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Pacific BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240327T192616Z UID:7379CD44-3ACD-4457-893C-6EE940F0BB23 DTSTART;TZID=US/Pacific:20240320T183000 DTEND;TZID=US/Pacific:20240320T203000 DESCRIPTION:Event Details\n\nNeural networks are becoming a central compone nt of a broad range of applications. However\, the complexity of the tasks \, the diversity of operating contexts\, as well as channel and computing resource scarcity challenge the effective deployment of neural models in m any relevant scenarios. In this talk\, I will provide an overview of the t echniques and frameworks that my research group developed to allow flexibl e\, efficient and resilient distributed neural computing for robotic perce ption and autonomous navigation. Our approaches deeply integrate system an d machine learning to obtain practical solutions deployable on real-world hardware platforms and applications.\n\nAbout the Speaker Marco Levorato\n \n[Marco Levorato](https://www.linkedin.com/in/marco-levorato-424a967/) is a Professor in the Computer Science department at the University of Calif ornia\, Irvine. He completed the PhD in Electrical Engineering at the Univ ersity of Padova\, Italy\, in 2009. Between 2010 and 2012\, he was a postd octoral researcher with a joint affiliation at Stanford and the University of Southern California. His research interests are focused on distributed computing over unreliable wireless systems\, especially for autonomous ve hicles and robotic applications. His work received the best paper award at IEEE GLOBECOM (2012). In 2016 and 2019\, he received the UC Hellman Found ation Award and the Dean mid-career research award\, respectively. His res earch is funded by the National Science Foundation\, the Department of Def ense\, Intel and Cisco. In 2020-2021\, he was the vice chair of the IEEE T echnical Committee on Smart Grid Communications. He serves in the TPC of I EEE Infocom\, IEEE Secon\, IEEE Percom\, IEEE ICDCS and ACM MobiHoc\, is a n associate editor of the IEEE Transactions on Communications and was part of the organizing committee of several IEEE and ACM conferences\, includi ng IEEE Secon 2022 and 2017\, ACM MobiSys 2015 and ACM MobiCom 2015 and 20 14. He delivered the keynote speech at IEEE HealthCom 2022 and IEEE MedCom Net 2023.\n\nNOTE: This is an IN PERSON meeting. To receive a link to the event's recording\, complete the survey referenced in the header or footer .\n\nCo-sponsored by: OC ACM [Actual Host] and Knobbe Martens\, a Intellec tual Property & technology law firm [Physical Host Donor]\n\nAgenda: \n6:3 0 PM Networking at physical meeting location\n7:00 PM Announcements and Pr esentation with Q&A\n8:00 PM Follow-up quesitons for presenter and network ing\n8:30 PM Meeting Adjourned\n\n2040 Main St \, Ste 14\, Irvine\, Califo rnia\, United States LOCATION:2040 Main St \, Ste 14\, Irvine\, California\, United States ORGANIZER:AWBrown@USC.edu SEQUENCE:6 SUMMARY:"Dynamic Distributed Computing for Autonomous Vehicles in 5G Infras tructures" IEEE OCCS & OC ACM Mtg URL;VALUE=URI:https://events.vtools.ieee.org/m/410284 X-ALT-DESC:Description: <br /><p><span style="text-decoration: underline\;" ><strong>Event</strong> <strong>Details</strong></span><strong> &nbsp\;</s trong></p>\n<p>Neural networks are becoming a central component of a broad range of applications. However\, the complexity of the tasks\, the divers ity of operating contexts\, as well as channel and computing resource scar city challenge the effective deployment of neural models in many relevant scenarios. In this talk\, I will provide an overview of the techniques and frameworks that my research group developed to allow flexible\, efficient and resilient distributed neural computing for robotic perception and aut onomous navigation. Our approaches deeply integrate system and machine lea rning to obtain practical solutions deployable on real-world hardware plat forms and applications.</p>\n<p><strong><span style="text-decoration: unde rline\;">About the Speaker</span> </strong>Marco Levorato&nbsp\;</p>\n<p>< a href="https://www.linkedin.com/in/marco-levorato-424a967/">Marco Levorat o</a> is a Professor in the Computer Science department at the University of California\, Irvine. He completed the PhD in Electrical Engineering at the University of Padova\, Italy\, in 2009. Between 2010 and 2012\, he was a postdoctoral researcher with a joint affiliation at Stanford and the Un iversity of Southern California. His research interests are focused on dis tributed computing over unreliable wireless systems\, especially for auton omous vehicles and robotic applications. His work received the best paper award at IEEE GLOBECOM (2012). In 2016 and 2019\, he received the UC Hellm an Foundation Award and the Dean mid-career research award\, respectively. His research is funded by the National Science Foundation\, the Departmen t of Defense\, Intel and Cisco. In 2020-2021\, he was the vice chair of th e IEEE Technical Committee on Smart Grid Communications. He serves in the TPC of IEEE Infocom\, IEEE Secon\, IEEE Percom\, IEEE ICDCS and ACM MobiHo c\, is an associate editor of the IEEE Transactions on Communications and was part of the organizing committee of several IEEE and ACM conferences\, including IEEE Secon 2022 and 2017\, ACM MobiSys 2015 and ACM MobiCom 201 5 and 2014. He delivered the keynote speech at IEEE HealthCom 2022 and IEE E MedComNet 2023.&nbsp\;</p>\n<p><span style="text-decoration: underline\; "><strong>NOTE:</strong></span>&nbsp\; This is an IN PERSON meeting.&nbsp\ ; To receive a link to the event's recording\, complete the survey referen ced in the header or footer.</p><br /><br />Agenda: <br /><p><span class=" aBn" tabindex="0" data-term="goog_557201553"><span class="aQJ">6:30 PM Net working at physical meeting location<br></span></span><span class="aBn" ta bindex="0" data-term="goog_557201553"><span class="aQJ">7:00 PM</span></sp an> Announcements and Presentation with Q&amp\;A<br>8:00 PM Follow-up ques itons for presenter and networking<br>8:30 PM Meeting Adjourned</p> END:VEVENT END:VCALENDAR