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X-ORIGINAL-URL:https://coe.northeastern.edu
X-WR-CALDESC:Events for Northeastern University College of Engineering
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20201015
DTEND;VALUE=DATE:20201231
DTSTAMP:20260421T003829
CREATED:20201015T142444Z
LAST-MODIFIED:20201015T142444Z
UID:22804-1602720000-1609372799@coe.northeastern.edu
SUMMARY:Meet Your Graduate Student Ambassadors!
DESCRIPTION:Meet your Student Ambassadors! Prospective and Admitted Graduate Students are invited to meet their Student Ambassador via Unibuddy.
URL:https://coe.northeastern.edu/event/meet-your-graduate-student-ambassadors/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201202T080000
DTEND;TZID=America/New_York:20201202T090000
DTSTAMP:20260421T003829
CREATED:20201103T160131Z
LAST-MODIFIED:20201103T160131Z
UID:23029-1606896000-1606899600@coe.northeastern.edu
SUMMARY:IEM-sponsored virtual event: Discussion: Spring Semester\, What to Expect?
DESCRIPTION:December 2: IEM-sponsored virtual event: Discussion: Spring Semester\, What to Expect? \n8:00 AM EST \nJoin link: This event will be run via Unibuddy. Connect with our ambassadors + learn the platform here. \nAudience: All admits for Spring\, 2021 including deferrals from a previous term.
URL:https://coe.northeastern.edu/event/iem-sponsored-virtual-event-discussion-spring-semester-what-to-expect/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201202T100000
DTEND;TZID=America/New_York:20201202T110000
DTSTAMP:20260421T003829
CREATED:20201116T203509Z
LAST-MODIFIED:20201116T203509Z
UID:23195-1606903200-1606906800@coe.northeastern.edu
SUMMARY:ECE PhD Dissertation Defense: Leili Hayati
DESCRIPTION:PhD Dissertation Defense: Ceramic Magnetic Wires at Wireless Communication Frequencies \nLeili Hayati \nLocation: Online \nAbstract: Ferrite magnetic devices play an important role in modern wireless telecommunication systems. They generally require permanent magnets in order to magnetically polarize the ferrite material component used in these devices. The permanent magnets are bulky and take up most of the size and weight of a magnetic circuit. The aim of this research is to do away with permanent magnet bias circuits as utilized in circulators and ferrite planar devices\, especially in wireless communication systems operating below 2 GHz. Recently\, ferromagnetic nanowires (NWs) have been embedded into porous templates\, are used to design various microwave magnetic and electronics devices. The main advantage of magnetic NWs is that in zero magnetic field\, the microwave absorption frequency can be easily tuned over a large range of frequencies. Clearly\, the metallic nature of the magnetic NWs contributed to the high loss. It is expected that insulating magnetic NWs will improve the insertion loss sufficiently to produce viable ferrite devices at wireless communication frequencies below 2GHz and at higher frequencies. There are no pure insulating magnetic materials. However\, there are ferrites that are nearly insulating and are ferrimagnetic. Their saturation magnetization is much lower than the metallic ferromagnetic counterpart. This is a desirable property for magnetic device operating below 2 GHz. Of all the ferrite materials yttrium iron garnet (YIG) exhibits the lowest FMR linewidth ever measured and low saturation magnetization. In this work\, an array of high-purity YIG NWs embedded in a porous silicon membrane\, were synthesized using sol-gel method and the magnetic properties of the pure YIG Nanoparticles and the composite substrate were characterized by utilizing vibrating sample magnetometer (VSM) technique. From the ferromagnetic resonance (FMR) spectra\, it has been found that the measurements are characterized by a uniaxial magnetic anisotropy energy due to the high aspect ratio of the NWs. Based on the magnetic parameters of the composite substrate and characterizing YIG NWs\, a coplanar waveguide was designed by HFSS software. By applying a small external magnetic field and changing the internal magnetic H field by ±8%\, the phase of S21 parameter shifts up to 30̊ degrees near 1.7GHz.
URL:https://coe.northeastern.edu/event/ece-phd-dissertation-defense-leili-hayati/
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DTSTART;TZID=America/New_York:20201202T100000
DTEND;TZID=America/New_York:20201202T110000
DTSTAMP:20260421T003829
CREATED:20201118T212728Z
LAST-MODIFIED:20201118T212728Z
UID:23232-1606903200-1606906800@coe.northeastern.edu
SUMMARY:ECE PhD Dissertation Defense: Bilgehan Donmez
DESCRIPTION:PhD Dissertation Defense: Topology Error Detection in Power System State Estimation \nBilgehan Donmez \nLocation: Teams Link \nAbstract: Growth of renewable energy\, changes in weather patterns\, and increases in cyber- and physical-attacks are examples of recent challenges in power system operation. To keep up with these rapid transformations\, it is imperative to improve the tools used in modern-day control centers.\nAs the centerpiece of system operations\, improvements in state estimation (SE) accuracy would result in better situational awareness for system operators. The state estimate can often be compromised when there are errors in the assumed topology of the network. Therefore\, topology error detection plays a key role in SE. In the first part of this dissertation\, topology errors in the external systems\, which are the neighboring control areas\, are investigated. When a subset of measurements coming from an external area is lost\, some parts of the system can become unobservable. Since SE cannot be carried out for the unobservable portion of the system\, the topology of the external system cannot be tracked in its usual way. This dissertation offers a computationally efficient external line outage detection algorithm that uses only the internal bus phase angles\, any available phasor measurement units (PMUs)\, and the pre-contingency system topology of the system. Coupled with a post-verification step\, this method is shown to be effective in detecting external line outages.\nThe second part of the dissertation focuses on topology errors in the internal system. The conventional SE implementations use the simplified bus-branch (BB) electrical network provided by the topology processor (TP). When the status of circuit breakers are not reported correctly to the TP\, the electrical equivalent it creates will be inaccurate. Therefore\, topology errors usually result in SE convergence problems or yield significantly biased estimates. To properly detect these types of errors\, rather than using the typical BB representation\, the network model is expanded to include circuit breakers and other switching devices in substations. SE is then reformulated to work with this detailed node-breaker (NB) model.\nAlthough the expansion of the model introduces operational and computational challenges\, several strategies are employed to counter these issues. The proposed innovations include the formulations of two separate equality-constrained SE algorithms\, the development of optimal meter placement algorithms\, and utilization of parallel processing. As demonstrated through the simulations conducted\, the methods developed in this dissertation are practical enough for adaptation to real-world systems.
URL:https://coe.northeastern.edu/event/ece-phd-dissertation-defense-bilgehan-donmez/
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DTSTART;TZID=America/New_York:20201202T120000
DTEND;TZID=America/New_York:20201202T130000
DTSTAMP:20260421T003830
CREATED:20200930T184350Z
LAST-MODIFIED:20200930T184350Z
UID:22484-1606910400-1606914000@coe.northeastern.edu
SUMMARY:BioE Seminar Series Presents: Jessica Wagenseil
DESCRIPTION:Jessica Wagenseil\, Ph.D. \nAssociate Professor\, Department of Mechanical Engineering and Materials Science\, Washington University\, St. Louis MO \n“Elastin mechanobiology in aortic development” \nABSTRACT:   \nThe extracellular matrix protein\, elastin\, provides reversible extensibility to the aorta that is critical for proper function of the cardiovascular system. Elastin is deposited during late embryonic and early postnatal growth\, at the same time that blood pressure and flow are increasing. This relationship suggests that mechanobiological signals for elastin deposition are linked to hemodynamic forces. I will discuss how reduced or absent elastin affects aortic mechanics\, cardiovascular hemodynamics\, and aortic wall development in genetically modified mouse models. I will also discuss how altered hemodynamics\, specifically reduced blood flow\, affects elastin amounts\, aortic mechanics\, and wall development in developing chick embryos. I will introduce mathematical models that we use to better understand the cause and effect relationships between elastin amounts and cardiovascular hemodynamics. The combination of experimental work in diverse animal models and mathematical modeling will advance our understanding of how the aortic wall is constructed to provide appropriate extensibility for normal cardiovascular function. The knowledge will aid in designing tissue-engineered arteries and in the treatment of cardiovascular diseases associated with elastin defects \nBIOGRAPHY: \nDr. Wagenseil joined the Mechanical Engineering and Materials Science Department at Washington University in 2013. She was previously in the Biomedical Engineering Department at Saint Louis University. She got her B.S. at UC San Diego and did her doctoral and postdoctoral training at Washington University. Dr. Wagenseil studies vascular mechanics focusing on the extracellular matrix in development and disease. Dr. Wagenseil received the 2020 Renato Iozzo Award from the American Society for Matrix Biology \nIf interested in attending\, please email Elizabeth Chesley at e.chesley@northeastern.edu for the Zoom link.
URL:https://coe.northeastern.edu/event/bioe-seminar-series-presents-jessica-wagenseil/
ORGANIZER;CN="Bioengineering":MAILTO:bioe@northeastern.edu
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DTSTART;TZID=America/New_York:20201202T140000
DTEND;TZID=America/New_York:20201202T150000
DTSTAMP:20260421T003830
CREATED:20201130T151126Z
LAST-MODIFIED:20201130T151212Z
UID:23312-1606917600-1606921200@coe.northeastern.edu
SUMMARY:ECE MS Thesis Defense: Kathan Vyas
DESCRIPTION:MS Thesis Defense: Data-Efficient analysis of Human Behavior by Spatio-Temporal Pose Generation and Inference \nKathan Vyas \nLocation: Zoom Link  \nPasscode: 474462 \nAbstract: Identifying human pose over time provides critical information towards understanding human behavior and their physical interaction with the environment surrounding them. In the past few decades\, the human pose estimation topic has witnessed groundbreaking research in the computer vision field thanks to the powerful deep learning models. These models are trained using several thousands of labeled sample images if not more. Such extensive data requirement posed a fundamental problem for domains (i.e. Small Data domains)\, in which data collection or labeling is expensive or limited due to privacy or security concerns such as healthcare. In this thesis\, we present a data-efficient learning pipeline to address small data problem in a healthcare-related human pose estimation application. In particular\, we infer spatio-temporal human poses to analyze typical vs. atypical behaviors in children with Autism spectrum disorder (ASD). To mitigate data limitation\, we propose two thrusts in our learning pipeline. The first thrust is a data-efficient machine learning approach\, in which a pre-trained (on adult pose images) pose estimation model with deep structure is fine-tuned on a small set of children pose videos\, provided to us by our collaborators. We implement a non-linear particle filter interpolation to deal with any missing body keypoints in the estimated poses and employ a novel PoTion (pose motion) based temporal aggregation technique to evaluate poses over time. The second thrust is a synthetic data augmentation approach\, in which we build a framework to create synthetic 3D humans with articulated bodies in order to render more pose images/videos in our application contexts. We use a novel 3D registration approach based on RANSAC and implement iterative closest point (ICP) to obtain 3D meshes from the scanned point clouds from both adult and kid mannequins\, which is then rigged and articulated in the Blender to generate our human avatars. We then infuse these avatars in various synthetic environments to create contexts similar to the target application\, which is a kid with both typical and atypical behaviors in a home-like environment.
URL:https://coe.northeastern.edu/event/ece-ms-thesis-defense-kathan-vyas/
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DTSTART;TZID=America/New_York:20201202T140000
DTEND;TZID=America/New_York:20201202T160000
DTSTAMP:20260421T003830
CREATED:20201116T145518Z
LAST-MODIFIED:20201116T145518Z
UID:23183-1606917600-1606924800@coe.northeastern.edu
SUMMARY:3 Minute Thesis Competition
DESCRIPTION:The annual GWiSE 3 Minute Thesis Competition 2020 is finally here! The 3MT is an academic competition that challenges Ph.D. students to describe their research within three minutes. This is a great opportunity to practice pitching your research to a non-specialist audience and to improve your science communication. Northeastern GWiSE and the Northeastern University Library have partnered to make 3 Minute Thesis possible with some pretty cool prizes: \n\nFirst place: 100$ Grubhub card\, an interview on the Dean’s podcast\, 100$ credit for 3D printing at the library\nSecond place: 50$ Grubhub card\, an interview on the Dean’s podcast\, 50$ credit for 3D printing at the library\nThird place: 25$ Grubhub card\, an interview on the Dean’s podcast\n\nRSVP to participate here. \nMore details for submission will be sent to those who RSVP. The deadline for video submission is Tuesday\, November 24th via email to gwise.neu@gmail.com. Video requirements\, 3-minute recording over : \n\n1st slide: title and author’s name\n2nd slide: thesis content\n\nThe live event will take place on Wednesday\, December 2nd from 2 PM to 4 PM ET on Zoom! All grad students are welcome to attend and/or present. The event will work in this way: \n\nGWiSE will host the event on Zoom and play prerecorded videos of participants’ explaining their thesis in under 3 minutes\nAfter each video is shown\, the judges will have time to discuss the presentations and assign scores\nGWiSE will proclaim the winners and offer the prizes!\n\nReminder\, please RSVP to participate here. The deadline for video submission is on the 24th of November. To submit your video\, send a video file to gwise.neu@gmail.com. The actual event is on Wednesday\, December 2nd.
URL:https://coe.northeastern.edu/event/3-minute-thesis-competition/
ORGANIZER;CN="GWiSE%3A Graduate Women in Science and Engineering":MAILTO:gwise.neu@gmail.com
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