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X-WR-CALDESC:Events for Northeastern University College of Engineering
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DTSTART;TZID=America/New_York:20230201T080000
DTEND;TZID=America/New_York:20230215T170000
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UID:35615-1675238400-1676480400@coe.northeastern.edu
SUMMARY:Call for Abstracts! AEESP 2023
DESCRIPTION:We are thrilled to share the news that Northeastern will be hosting the 2023 Association of Environmental Engineering and Science Professors (AEESP) Conference\, the preeminent professional gathering on all things environmental that is hosted biannually at a US university.We will be welcoming 700-800 of our colleagues to campus this June for a 4-day event that will target topics under the theme “Responding Together to Global Challenges”.  This theme is well aligned with the research we do here at Northeastern\, and we would love to see big representation from our student community!\n———————————————————————–\nCALL FOR ABSTRACTS:  Due February 15\, 2023\n———————————————————————–\nAbstracts for oral/poster presentation on any topic of interest to the community will be considered\, with conference sessions organized around major global challenges\, including: \n\nA changing climate\nCurrent and emerging threats to environmental quality and human health\nNew education and workforce demands\nAging infrastructure and risks to lifeline systems\nMarginalization of communities\nEmerging topics (to be added based on submissions received)\n\nFor more information on the conference and abstract submission please see the attached flyer and the conference website:  https://aeesp2023.sites.northeastern.edu/ \nAnd you can send questions to anyone on the Planning Committee – or drop by to chat! \n2023 AEESP Conference Planning Committee \n\nMatt Eckelman\, Science Committee Chair\nm.eckelman@northeastern.edu\nPhil Larese-Casanova\, Conference Chair\nP.LareseCasanova@northeastern.edu\nAmy Mueller\, Conference co-Chair\na.mueller@northeastern.edu
URL:https://coe.northeastern.edu/event/call-for-abstracts-aeesp-2023/
ORGANIZER;CN="Civil & Environmental Engineering":MAILTO:civilinfo@coe.neu.edu
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DTSTART;TZID=America/New_York:20230215T113000
DTEND;TZID=America/New_York:20230215T123000
DTSTAMP:20260629T055222
CREATED:20230210T160554Z
LAST-MODIFIED:20230210T160554Z
UID:35734-1676460600-1676464200@coe.northeastern.edu
SUMMARY:Yiyue Jiang's PhD Proposal Review
DESCRIPTION:“FPGA-based Accelerator of Neural Networks for Digital Predistortion” \nCommittee: \nProf. Miriam Leeser (Advisor) \nProf. John Dooley \nProf. Stefano Basagni \nAbstract: \nPower Amplifiers (PAs) are an essential part of wireless communications. \nAs wireless standards evolve and become more demanding\,  the requirements for PAs change as well.  Specifically\, PAs need to balance linearity and energy efficiency while adhering to 5G wireless standards and beyond. PA behaviors differ based on several criteria\, including the type of PA\, power levels\, and the environment. To overcome the nonlinear behavior of a PA\, a flexible system to achieve digital predistortion (DPD) is required that can rapidly adapt to its environment. \nIn many situations\, traditional methods such as the memory polynomial model cannot adapt to all these factors. Neural networks have been used for some years in RF and microwave engineering. Early work demonstrated the suitability of neural networks to model complicated active device characteristics. Current neural network based DPD systems all do the training offline and are therefore not real-time systems. To reduce the cost to upgrade hardware and to provide more flexibility to different power amplifiers’ linearization needs\, a specific neural network based reconfigurable\, adaptive\, and real-time digital predistortion system is proposed. This system targets Zynq All Programmable System on Chip (SoC) devices which feature an ARM processor and FPGA together with RF frontend on the same chip. The system proposed in this research combines real-time DPD with on-chip training. Furthermore\, most research on FPGA based inference accelerators targets classification problems with probability output. There is no accelerator working on the signal processing problem focusing on sample-by-sample output. Our proposed system is optimized in both algorithm and implementation targeting sample-by-sample processing with high accuracy and real-time efficiency. \n 
URL:https://coe.northeastern.edu/event/yiyue-jiangs-phd-proposal-review/
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DTSTART;TZID=America/New_York:20230215T120000
DTEND;TZID=America/New_York:20230215T124500
DTSTAMP:20260629T055222
CREATED:20230126T212542Z
LAST-MODIFIED:20230126T212542Z
UID:35271-1676462400-1676465100@coe.northeastern.edu
SUMMARY:Library Webinar: 10 Advanced EndNote Features
DESCRIPTION:Learn how you can use EndNote’s advanced features to make the most of this high-level citation tool. \nNote: use of Northeastern’s institutional EndNote subscription requires a Northeastern or NCH London username and password. This webinar is not open to non-Northeastern users. \nRegistration is required. Register here. \nAll the times of the webinars are in EST. \nRelated LibGuide: Citations and Bibliographies
URL:https://coe.northeastern.edu/event/library-webinar-10-advanced-endnote-features-3/
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DTSTART;TZID=America/New_York:20230215T173000
DTEND;TZID=America/New_York:20230215T183000
DTSTAMP:20260629T055222
CREATED:20230109T145512Z
LAST-MODIFIED:20230109T145512Z
UID:34963-1676482200-1676485800@coe.northeastern.edu
SUMMARY:Gordon Institute Virtual Information Session
DESCRIPTION:Learn how you can earn a Graduate Certificate in Engineering Leadership as a stand-alone certificate or in combination with one of twenty Master of Science degrees offered through Northeastern’s College of Engineering\, College of Science\, or Khoury College of Computer Sciences.  \nThe National Academy of Engineering recognized The Gordon Institute of Engineering Leadership (GIEL) for its innovative curriculum that combines technical education\, leadership capabilities\, and the “Challenge Project”: an opportunity for students to receive master’s level credit while working in industry.  \nBy aligning technical proficiency with leadership capabilities\, GIEL accelerates the development of high-potential engineers and prepares them to lead complex projects early in their careers. Upon completing the program\, more than 88% of the 2021 class reported increased leadership responsibility\, while more than 50% of the 2021 class reported being promoted within one year of graduation.  \nOur Director of Admissions will answer your application questions for Fall 2023.  \nYou will have the opportunity to hear from Alumni on how The Gordon Institute propelled their engineering careers. Program professors will also be present to answer curriculum questions. 
URL:https://coe.northeastern.edu/event/gordon-institute-virtual-information-session-11/
ORGANIZER;CN="Gordon Engineering Leadership program":MAILTO:gordonleadership@northeastern.edu
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