BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Northeastern University College of Engineering - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Northeastern University College of Engineering
X-ORIGINAL-URL:https://coe.northeastern.edu
X-WR-CALDESC:Events for Northeastern University College of Engineering
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:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200203
DTEND;VALUE=DATE:20200306
DTSTAMP:20260424T135322
CREATED:20200129T144506Z
LAST-MODIFIED:20200129T144506Z
UID:19430-1580688000-1583452799@coe.northeastern.edu
SUMMARY:Call for submissions for Research: Art or Science? Exhibition!
DESCRIPTION:Submit an image of your research to the third annual Research: Art or Science? Exhibition for a unique opportunity to have your work displayed on campus and win a cash prize! Visit Art or Science? for more information and to submit.
URL:https://coe.northeastern.edu/event/call-for-submissions-for-research-art-or-science-exhibition/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200211T100000
DTEND;TZID=America/New_York:20200211T110000
DTSTAMP:20260424T135322
CREATED:20200207T172308Z
LAST-MODIFIED:20200207T172308Z
UID:19710-1581415200-1581418800@coe.northeastern.edu
SUMMARY:Electrical and Computer Engineering Webinar
DESCRIPTION:The webinar will feature a talk by Program Director Masoud Salehi\, who will present information on the Electrical and Computer Engineering program (ECE) at Northeastern University. Located in the booming technology\, medical\, and research hub of Boston\, Northeastern ‘s Department of ECE provides excellent research and learning opportunities for its students and alumni. The ECE faculty and graduate students conduct world-class research in the field. With over 65 full-time and affiliated faculty members\, ECE is home to experts in a variety of disciplines\, including but not limited to information infrastructure and security\, health and biomedical applications of electrical engineering\, brain-computer interface\, nanotechnology\, and nanomaterials. \nWEBINAR DETAILS: \nTopic: Electrical and Computer Engineering\nDate: Tuesday\, February 11\nTime: 10:00 – 11:00 AM EST \nWEBINAR INSTRUCTIONS \nRSVP and let us know if you will attend. \n 
URL:https://coe.northeastern.edu/event/electrical-and-computer-engineering-webinar/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200211T113000
DTEND;TZID=America/New_York:20200211T123000
DTSTAMP:20260424T135322
CREATED:20200131T144339Z
LAST-MODIFIED:20200131T144339Z
UID:19473-1581420600-1581424200@coe.northeastern.edu
SUMMARY:Electrical and Computer Engineering Seminar: Qing Qu
DESCRIPTION:Location: ISEC 138 \nTitle: Learning Low-complexity Models from the Data – Geometry\, Optimization\, and Applications \nAbstract: \nToday we are collecting a massive amount of data in forms of images and videos\, that we want to learn from the data themselves to extract useful information and to make predictions. The data are high-dimensional\, but often possess certain low-dimensional structures (e.g.\, sparsity). However\, learning these low-complexity models often results in highly nonconvex optimization problems\, where in the past our understandings of solving them were very limited. In the worst case\, optimizing a nonconvex problem is NP-hard. \nIn this talk\, we present global nonconvex optimization theory and guaranteed algorithms for efficient learning of low-complexity models from high-dimensional data. For several important problems in imaging science (i.e.\, sparse blind deconvolution) and representation learning (i.e.\, convolutional/overcomplete dictionary learning)\, we show that the underlying symmetry and low-complexity structures avoid the worst-case scenarios\, leading to benign global geometric properties of the nonconvex optimization landscapes. In particular\, for sparse blind deconvolution that aims to jointly learn the underlying physical model and sparse signals from convolutions\, the geometric intuitions lead to efficient nonconvex algorithms\, with linear convergence to target solutions. Moreover\, we extended our geometric analysis to convolutional dictionary learning based on its similarity with overcomplete dictionary learning\, providing the first global algorithmic guarantees for both problems. Finally\, we demonstrate our methods on several important applications in scientific discovery and draw connections to learning deep neural networks. \nThis talk is mainly based on one paper appeared in NeurIPS’19 (spotlight)\, and two papers accepted by ICLR’20 (one oral). \nBio:  \nQing Qu is a Moore-Sloan data science fellow at the Center for Data Science\, New York University. He received his Ph.D. from Columbia University in Electrical Engineering in Oct. 2018. He received his B.Eng. from Tsinghua University in Jul. 2011\, and an M.Sc.from the Johns Hopkins University in Dec. 2012\, both in Electrical and Computer Engineering. He interned at U.S. Army Research Laboratory in 2012 and Microsoft Research in 2016\, respectively. His research interest lies at the intersection of the foundation of data science\, machine learning\, numerical optimization\, and signal/image processing. His research focuses on developing computational methods for learning low-complexity models/structures from high dimensional data\, leveraging tools from machine learning\, numerical optimization\, and high dimensional probability/geometry. He is also interested in applying these data-driven methods to various engineering problems in imaging sciences\, scientific discovery\, and healthcare. He is the recipient of Best Student Paper Award at SPARS’15 (with Ju Sun and John Wright)\, and the recipient of Microsoft Ph.D. Fellowship 2016-2018 in machine learning.
URL:https://coe.northeastern.edu/event/electrical-and-computer-engineering-seminar-qing-qu/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200211T130000
DTEND;TZID=America/New_York:20200211T133000
DTSTAMP:20260424T135322
CREATED:20200127T192405Z
LAST-MODIFIED:20200127T192405Z
UID:19281-1581426000-1581427800@coe.northeastern.edu
SUMMARY:Basic Soldering
DESCRIPTION:This workshop is an introduction to soldering. Learn how to solder two wires together and apply heat-shrink tubing using a Weller soldering station and an SMD Rework station \nSign up using this link! \nView the Sherman Center Calendar for more events!
URL:https://coe.northeastern.edu/event/basic-soldering-5/
LOCATION:010 Hayden Hall\, 010 Hayden Hall\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
ORGANIZER;CN="Michael J. and Ann Sherman Center for Engineering Entrepreneurship Education":MAILTO:sherman@northeastern.edu
GEO:42.3394629;-71.0885286
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=010 Hayden Hall 010 Hayden Hall 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=010 Hayden Hall\, 360 Huntington Ave:geo:-71.0885286,42.3394629
END:VEVENT
END:VCALENDAR