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DTSTAMP:20240503T123125
DTSTART;TZID=America/Detroit:20240418T140000
DTEND;TZID=America/Detroit:20240418T150000
SUMMARY:Careers / Jobs:International Students Career Chat with Ashley Chen\, incoming Data Analyst at Apple
DESCRIPTION:Come to this virtual office hour to speak with Ashley Chen\, current MBAn Business Analytics\, Incoming Data Analyst at Apple. If you are interested in the industry and role\, come and have a 15-minute 1:1 conversation with Ashley to learn more about her job search experience as an international student! Staff members from the University Career Center willalso be present during this session. If you have questions about campus resources that can support international students job search\, feel free tosign up and attend the session! If you are interested in attending\, please sign up through this form: https://forms.gle/GTmrLRan4wQwTkHQ6! Spots come on a first come first serve basis.
UID:121316-21846385@events.umich.edu
URL:https://events.umich.edu/event/121316
CLASS:PUBLIC
STATUS:CONFIRMED
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BEGIN:VEVENT
DTSTAMP:20240503T123121
DTSTART;TZID=America/Detroit:20240418T140000
DTEND;TZID=America/Detroit:20240418T143000
SUMMARY:Careers / Jobs:Women In Supply Chain Panel with MoLo Solutions
DESCRIPTION:You’re invited to MoLo Solutions' virtual event: Women In Supply Chain Panel! Join us to hear directly from the leaders of our Women In Supply Chain employee resource group. This informational session will also allow you to learn more about MoLo Solutions\, the Third-Party Logistics industry\, as well as our full-time and internship opportunities. RSVP today to attend our virtual event Women In Supply Chain Panel with MoLo Solutions!
UID:121188-21845965@events.umich.edu
URL:https://events.umich.edu/event/121188
CLASS:PUBLIC
STATUS:CONFIRMED
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BEGIN:VEVENT
DTSTAMP:20240408T121916
DTSTART;TZID=America/Detroit:20240418T150000
DTEND;TZID=America/Detroit:20240418T160000
SUMMARY:Livestream / Virtual:899 Seminar Series: Lei Ying
DESCRIPTION:Presenter Bio:\n\nLei Ying is currently a Professor at the Electrical Engineering and Computer Science Department of the University of Michigan\, Ann Arbor\, an IEEE Fellow\, and an Editor-at-Large for the IEEE/ACM Transactions on Networking. His research is broadly in the interplay of complex\nstochastic systems and big data\, including reinforcement learning\, large-scale communication/computing systems\, private data marketplaces\, and large-scale graph mining. He won the Young Investigator Award from the Defense Threat Reduction Agency (DTRA) in 2009 and the NSF CAREER Award in 2010. He was the Northrop Grumman Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University from 2010 to 2012. His papers have received the best paper award at IEEE INFOCOM 2015\, the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS/IFIP Performance 2016 and the WiOpt’18 Best Student Paper Award\; his papers have also been selected in ACM TKDD Special\nIssue “Best Papers of KDD 2016”\, Fast-Track Review for TNSE at IEEE INFOCOM 2018 (7 out of 312 accepted papers were invited)\, and Best Paper Finalist at MobiHoc 2019.\n\nAbstract:\nData-driven learning and decision-making in complex systems are often subject to a variety of operational constraints such as safety\, fairness\, and budget constraints. The problem becomes particularly challenging when the constraints are unknown\, sometimes adversarial\,\nand must be learned while making decisions. This talk presents some of our recent results on this topic\, focusing on solving unknown CMDPs using model-free approaches.
UID:121230-21846069@events.umich.edu
URL:https://events.umich.edu/event/121230
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:899 Seminar Series,Industrial And Operations Engineering,Lecture
LOCATION:Industrial and Operations Engineering Building - 2717
CONTACT:
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