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DTSTART;TZID=America/New_York:20230502T100000
DTEND;TZID=America/New_York:20230502T110000
DTSTAMP:20260513T152132
CREATED:20230405T134856Z
LAST-MODIFIED:20230405T134856Z
UID:36467-1683021600-1683025200@coe.northeastern.edu
SUMMARY:Co-op Student Spotlight: Data Architecture and Management and Software Engineering Systems
DESCRIPTION:The College of Engineering is excited to host a Co-op Student Spotlight: Data Architecture and Management and Software Engineering Systems event on May 2\, 2023\, at 10:00am ET. We’d love to see you there. \nAll qualified Graduate School of Engineering students are encouraged to participate in Northeastern’s cooperative education program. Students who complete co-ops can work in the industry for 4\, 6\, or 8 months during the academic program. During this webinar\, participants will learn more about the co-op program from co-op faculty with a spotlight on Software Engineering Systems and Data Architecture and Management students.    \nTopics this event will cover include: \n\nParticipating in Co-op: Each student is supported by co-op faculty who help to make the process easy for students while they participate. \nCo-op Partners and Opportunities: The College of Engineering has over 1000 co-op industry partners across the United States and around the globe. \nCurrent Student Highlights: Current students will share their current experiences including their co-op journey\, their specific opportunity\, and the support they received on co-op.\n\nReserve your spot today and join us on May 2\, 2023\, at 10:00am ET.
URL:https://coe.northeastern.edu/event/co-op-student-spotlight-data-architecture-and-management-and-software-engineering-systems/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230502T100000
DTEND;TZID=America/New_York:20230502T180000
DTSTAMP:20260513T152132
CREATED:20230424T194620Z
LAST-MODIFIED:20230424T194620Z
UID:36822-1683021600-1683050400@coe.northeastern.edu
SUMMARY:Intellectual Property Awareness Summit (IPAS)
DESCRIPTION:The sixth annual Intellectual Property Awareness Summit® (IPAS 2023) will be held on May 2nd in Boston\, in conjunction with Northeastern University’s Center for Research Innovation (CRI). \nIPAS is a gathering of IP owners\, creators\, educators\, lawyers\, organizations and investors\, all with a common goal – to explore ways to make the benefits of IP rights\, and the issues surrounding them\, more apparent to people and society. \n​In Person Registration \nVirtual Registration
URL:https://coe.northeastern.edu/event/intellectual-property-awareness-summit-ipas/
ORGANIZER;CN="Center for Research Innovation":MAILTO:cri@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230504T160000
DTEND;TZID=America/New_York:20230504T170000
DTSTAMP:20260513T152132
CREATED:20230510T204755Z
LAST-MODIFIED:20230510T204755Z
UID:36991-1683216000-1683219600@coe.northeastern.edu
SUMMARY:Building Habits for Professional Success:  A CommLab Workshop Series
DESCRIPTION:Join the CommLab for our Building Habits for Professional Success\, where we’ll focus on building positive habits. Developing good habits can be a powerful tool for achieving success in various areas of life\, whether it’s improving your career\, increasing productivity\, or enhancing your wellbeing. Don’t miss this opportunity to gain valuable insights and practical tools for creating lasting positive changes in your daily routine. Join us every other week for an engaging and informative workshop!
URL:https://coe.northeastern.edu/event/building-habits-for-professional-success-a-commlab-workshop-series/2023-05-04/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230509
DTEND;VALUE=DATE:20230512
DTSTAMP:20260513T152132
CREATED:20230419T180635Z
LAST-MODIFIED:20230419T180635Z
UID:36755-1683590400-1683849599@coe.northeastern.edu
SUMMARY:ODSC East Data Science and AI Conference
DESCRIPTION:Join COE Graduate Admissions representatives at the ODSC East Data Science and AI Conference. Learn about our graduate Engineering programs and receive an application fee waiver code for attending and asking one of our reps a question.
URL:https://coe.northeastern.edu/event/odsc-east-data-science-and-ai-conference/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230509T160000
DTEND;TZID=America/New_York:20230509T170000
DTSTAMP:20260513T152132
CREATED:20230509T202453Z
LAST-MODIFIED:20230509T202453Z
UID:36960-1683648000-1683651600@coe.northeastern.edu
SUMMARY:CommLab Linked In Workshop Series
DESCRIPTION:Join the CommLab’s interactive LinkedIn workshop where we’ll be optimizing your profile and learning how to effectively connect with people on the platform to build a strong professional network.  This workshop meets every other Tuesday on Zoom or in 206 Egan.  Drop-in’s welcome!
URL:https://coe.northeastern.edu/event/commlab-linked-in-workshop-series/2023-05-09/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230511T160000
DTEND;TZID=America/New_York:20230511T170000
DTSTAMP:20260513T152132
CREATED:20230509T202350Z
LAST-MODIFIED:20230509T203000Z
UID:36963-1683820800-1683824400@coe.northeastern.edu
SUMMARY:Using LaTeX for CV/Resumes: A CommLab Workshop Series
DESCRIPTION:Looking to create a standout CV or resume that showcases your skills and experience in a professional way? Join the CommLab’s LaTeX workshop! Our workshop provides support in CV/resume building using LaTeX\, and will give you a better and clearer understanding of different aspects of the LaTeX code. You’ll learn how to customize templates\, incorporate graphics and images\, and create tables and bibliographies. Plus\, you’ll have the opportunity to connect with a community of like-minded individuals who are interested in LaTeX and its potential applications. Don’t miss this chance to support\, learn\, and grow with The CommLab! Register to join us virtually on Zoom or in person in 206 Egan.  This is a reoccurring community of practice and will meet every other Thursday.
URL:https://coe.northeastern.edu/event/using-latex-for-cv-resumes-a-commlab-workshop-series/2023-05-11/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230516T100000
DTEND;TZID=America/New_York:20230516T110000
DTSTAMP:20260513T152132
CREATED:20230405T134637Z
LAST-MODIFIED:20230405T134658Z
UID:36472-1684231200-1684234800@coe.northeastern.edu
SUMMARY:Research Spotlight: Chemical Engineering
DESCRIPTION:The College of Engineering is excited to host a Research Spotlight: Chemical Engineering event on May 16\, 2023\, at 10:00am ET.  We’d love to see you there. \nAs a Research 1 university\, Northeastern University students are exposed to some of the highest-quality research offerings in the United States. In this webinar\, our Chemical Engineering faculty members will walk you through their current research projects and offer insight on how current students may have the opportunity to be involved in those research projects during their time in the program.   \n  Topics this event will cover include: \n\nFaculty Introduction:  Faculty will have the opportunity to introduce themselves and their role with graduate students.\nFaculty Projects:  Faculty will introduce their projects and outline the works of their labs with specific attention to their research thrusts. \nHow to Participate: Attendees will learn how they can be involved in research at the academic and co-curricular levels.\n\nReserve your spot today and join us on May 16\, 2023\, at 10:00am ET.  
URL:https://coe.northeastern.edu/event/research-spotlight-chemical-engineering/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230516T160000
DTEND;TZID=America/New_York:20230516T170000
DTSTAMP:20260513T152132
CREATED:20230515T134625Z
LAST-MODIFIED:20230515T134625Z
UID:36998-1684252800-1684256400@coe.northeastern.edu
SUMMARY:Data Visualization by Coding: A CommLab Workshop Series
DESCRIPTION:Join the CommLab to work on visualizing your data using different coding methods.  We will use Python as well as other methods.  Join us to tell us which methods you are interested in working on.
URL:https://coe.northeastern.edu/event/data-visualization-by-coding-a-commlab-workshop-series/2023-05-16/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230517T170000
DTEND;TZID=America/Los_Angeles:20230517T190000
DTSTAMP:20260513T152132
CREATED:20230227T183331Z
LAST-MODIFIED:20230227T183331Z
UID:36002-1684342800-1684350000@coe.northeastern.edu
SUMMARY:Northeastern in Seattle: Build Your Tech Talent
DESCRIPTION:Whether you’re entirely new to computer science or have dabbled in coding\, you can advance your career with Northeastern University in Seattle’s monthly Build Your Tech Talent workshops. These free events give anyone looking to develop coding skills the chance to learn from industry experts. \nOur upcoming May workshop includes: \nThematic Analysis of Song Lyrics with Shanu Sushmita (on campus) \n\n\n\nDate: Wednesday\, May 17\, 2023\nTime: 5:00 p.m. – 7:00 p.m. PT\n\n\n\nRegister
URL:https://coe.northeastern.edu/event/northeastern-in-seattle-build-your-tech-talent-4/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230517T173000
DTEND;TZID=America/New_York:20230517T183000
DTSTAMP:20260513T152132
CREATED:20230120T201817Z
LAST-MODIFIED:20230120T201817Z
UID:35154-1684344600-1684348200@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-13/
ORGANIZER;CN="Gordon Engineering Leadership program":MAILTO:gordonleadership@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230518T160000
DTEND;TZID=America/New_York:20230518T170000
DTSTAMP:20260513T152132
CREATED:20230515T134515Z
LAST-MODIFIED:20230515T134515Z
UID:37002-1684425600-1684429200@coe.northeastern.edu
SUMMARY:Designing a Research Poster:  A CommLab Series
DESCRIPTION:Join the CommLab to work on your research poster.  Whether you are designing\, editing or delivering a poster\, this series will help you through whichever stage you are in.  May 18th will focus on design\, May 25 and June 1 will focus on editing and June 8 will focus on presenting.  This series will be hybrid.  Join us in 335 Curry Student Center or on Zoom.
URL:https://coe.northeastern.edu/event/designing-a-research-poster-a-commlab-series/2023-05-18/
LOCATION:335 CSC\, 360 Huntington Ave\, CSC\, Boston\, MA\, 02115\, United States
GEO:42.339110916473;-71.087682620746
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230522T103000
DTEND;TZID=America/New_York:20230522T113000
DTSTAMP:20260513T152132
CREATED:20230522T171916Z
LAST-MODIFIED:20230522T171916Z
UID:37073-1684751400-1684755000@coe.northeastern.edu
SUMMARY:Mengting Yan's PhD Dissertation Defense
DESCRIPTION:“Integrated Circuit Design Methods for Temperature-based Hardware Trojan Detection and Parametric Frequency Division in Next-Generation Systems-on-a-Chip” \nCommittee Members:\nProf. Marvin Onabajo (Advisor)\nProf. Yong-bin Kim\nProf. Yunsi Fei \nAbstract:\nNew needs for next-generation systems-on-a-chip (SoC) are emerging as the trend of globalization in the semiconductor industry becomes increasingly ubiquitous and the demand for low-power Internet-of-Things (IoT) devices continues to soar. Among various research directions\, this dissertation focuses on enhancing hardware security and on providing low-noise frequency sources for next-generation SoCs. Within this scope\, the described research addresses the challenge to improve on-chip anomaly detection capabilities\, and separately lays a foundation for the design of circuits to reduce the phase noise of on-chip oscillators. \nIn the first part of this dissertation\, an on-chip temperature-based Hardware Trojan (HT) detection system is introduced. The approach to detect inserted HTs relies on thermal profiling of the circuit under test (CUT) and side-channel analysis of the obtained temperature data. On-chip electrothermal coupling is modeled as part of a simulation technique that associates local thermal activities with circuit-level power consumption using a standard electrical simulator. To monitor the thermal profiles on chips with high sensitivity to local temperature changes as well as to enhance the resilience to flicker noise\, a fully-differential temperature sensor equipped with a chopping mechanism has been designed in 130-nm complementary metal-oxide-semiconductor (CMOS) technology\, which has a sensitivity of 840 V/◦C. The simulated temperature sensor output in the presence of noise and process variations is quantized by an analog-to-digital converter (ADC) model and processed using principal component analysis (PCA)\, which allows to determine the minimum detectable Trojan power and the design requirements for the on-chip ADC. With a modeled 8-bit ADC\, simulations of the HT detection system reveal a detection rate of 100% with a Trojan power down to 2.4 μW within the thermal profile of a CUT consuming 508 μW. A prototype 8-bit 1 MS/s successive approximation register (SAR) ADC for such a system was designed in 130-nm CMOS technology\, fabricated\, and tested. The measured effective number of bits (ENOB) is 7.27 bits up to the Nyquist frequency\, with a power consumption of 103.2 μW from a 1.2 V supply. Furthermore\, a 3-step analog calibration loop has been designed to compensate for the voltage offsets within the sensor circuits in the presence of device mismatches and process-temperature variations. The calibration loop settles within 300 μs to complete the offset calibration\, such that the input-referred offset has a standard deviation of 5.86 μV based on Monte Carlo simulations. \nIn the second part of this dissertation\, the on-chip realization of a parametric frequency divider (PFD) is explained. The low-power 2:1 frequency division at sub-6 GHz plays a critical role in on-chip phase noise reduction systems that exhibit nonlinear operations\, indicating promise for future integration into radio frequency (RF) SoCs. In particular\, the first current-driven PFD with an output frequency of 2.4 GHz is introduced\, which consists of three major blocks: (1) a custom PFD driver stage with a buffer to ease input driving\, (2) a purely passive PFD core with inductor-capacitor (LC) resonators\, and (3) an output driving stage with embedded band-pass filtering that suppresses undesirable output harmonics. A prototype PFD chip was fabricated in standard 65-nm CMOS technology\, and the corresponding measurement results are presented to characterize the performance of the new PFD. The minimum required supply voltage for the PFD driver is 1.4 V with an input frequency of 4.8 GHz\, whereas the PFD has an operating frequency range from 4.5 GHz to 5.1 GHz with a supply voltage of 1.5 V. To the best of the author’s knowledge\, the proposed PFD is the first on-chip CMOS implementation for sub-6 GHz applications\, which balances the trade-offs among frequency range\, power consumption\, and chip area constraints.
URL:https://coe.northeastern.edu/event/mengting-yans-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230526T090000
DTEND;TZID=America/New_York:20230526T100000
DTSTAMP:20260513T152132
CREATED:20230522T171659Z
LAST-MODIFIED:20230522T171659Z
UID:37075-1685091600-1685095200@coe.northeastern.edu
SUMMARY:Yuezhou Liu's PhD Proposal Review
DESCRIPTION:Committee Members:\nProf. Edmund Yeh (Advisor)\nProf. Stratis Ioannidis\nProf. Lili Su\nProf. Carlee Joe-Wong \nAbstract:\nSignificant advances in edge and mobile computing capabilities enable machine learning to occur at geographically diverse locations in networks\, e.g.\, cloud\, edge\, and mobile devices. The training data needed in those learning tasks may not be fully generated locally. Moreover\, some promising distributed learning paradigms enable devices to collaboratively train a model\, which requires communication among the devices for exchanging necessary information. Thus\, optimizing network strategies for the transmission/exchange of ML/AI ingredients (e.g.\, input data\, model parameters\, gradients) is important for facilitating efficient in-network distributed ML. While there exist many works that use ML to optimize network operation strategies\, few works study optimized networks that boost ML performance. This dissertation tries to fill the gap by studying several network optimization problems for distributed ML. Different from classic network optimization problems for data delivery or edge computing that optimize energy consumption\, delay\, throughput\, etc.\, we also pay attention to ML-related metrics such as model accuracy and training convergence time. \nWe first propose an experimental design network paradigm\, wherein learner nodes train possibly different ML models via consuming data streams generated by data source nodes over a network. We formulate this problem as a social welfare optimization problem in which the global objective is defined as the sum of experimental design objectives of individual learners\, and the decision variables are the data transmission strategies subject to network constraints. We show that\, assuming Bayesian linear regression models and Poisson data streams in steady state\, the global objective is continuous DR-submodular\, which enables the design of efficient approximate algorithms with approximation guarantees. We will further extend our framework to incorporate more practical ML applications\, such as ML with arbitrary nonlinear models. \nThe second half of this dissertation studies network optimization for Federated learning (FL)\, a distributed paradigm for collaboratively learning models without having clients disclose their private data. We propose to use caching for improving FL efficiency concerning the total model training time for convergence. Instead of having all clients download the latest global model from a parameter server\, we select a subset of clients to access\, with smaller delays\, a somewhat stale global model stored in caches. We propose CacheFL — a cache-enabled variant of FedAvg\, and provide theoretical convergence guarantees in the general setting where the local data is imbalanced and heterogeneous. With this result\, we determine the caching strategies that minimize total wall-clock training time at a given convergence threshold for both stochastic and deterministic communication/computation delays.
URL:https://coe.northeastern.edu/event/yuezhou-lius-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230526T123000
DTEND;TZID=America/New_York:20230526T133000
DTSTAMP:20260513T152132
CREATED:20230522T171528Z
LAST-MODIFIED:20230522T171528Z
UID:37077-1685104200-1685107800@coe.northeastern.edu
SUMMARY:Guillem Reus Muns' PhD Dissertation Defense
DESCRIPTION:“AI for communication and sensing in RF environments” \nCommittee Members:\nProf. Kaushik Chowdhury (Advisor)\nProf. Stratis Ioannidis\nProf. Hanumant Singh \nAbstract:\nThe recent growth of Internet of Things (IoT)\, as well as other new\nrevolutionary applications utilizing wireless spectrum are leading the way towards the realization of next-generation wireless systems that jointly utilize communications and sensing. However\, such systems offer many degrees of freedom\, and optimizing them for a specific task is difficult to accomplish with deterministic and classical approaches. For this reason\, data-driven and AI-based methods have been pursued actively by the research community\, as they are able to find solutions that often come close to or exceed the performance of the deterministic counterparts with fractional design complexity. This thesis presents\, through real systems and with experimental validation\, our progressive efforts in four broad areas\, where AI enables the operation of aerial and terrestrial systems that combine sensing and communications. The following key use cases with distinct contributions are investigated: \ni) Sensing-aided communications for air and ground systems. First\, we present a UAV communication method that defines constellation points in space that map to transmitter frequency bands and are detected at the Base Station using millimeter wave sensors. Second\, we explore alternative vehicle-to-infrastructure mmWave beamforming methods\, leveraging a) vehicle position and velocity estimation using in-band standard compliant 802.11ad radar and b) camera images and GPS location information. \nii) Signal classification using communication signals\, where we propose a) a UAV classification method using uniquely UAV-transmitted signals and b) an RF fingerprinting technique that improves class separation by combining triplet loss with regular classification techniques. \niii) ‘SenseORAN’\, a revolutionary architectural design that aims to reuse the cellular infrastructure for sensing purposes in order to address spectrum access challenges in the CBRS band. This is enabled by Open Radio Access Network (O-RAN)\, a cellular architecture concept that promotes virtualized RANs where disaggregated components are connected via open interfaces and supports intelligent controllers running custom logic. iv) ‘AirFC’\, an over-the-air computation method that implements fully connected neural networks inference leveraging multi-antenna wireless systems.
URL:https://coe.northeastern.edu/event/guillem-reus-muns-phd-dissertation-defense/
LOCATION:Admissions Visitor Center (West Village F)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230531T150000
DTEND;TZID=America/New_York:20230531T170000
DTSTAMP:20260513T152132
CREATED:20230523T173145Z
LAST-MODIFIED:20230523T173145Z
UID:37102-1685545200-1685552400@coe.northeastern.edu
SUMMARY:SASE Taiyaki and Trivia
DESCRIPTION:The Society of Asian Scientists and Engineers (SASE) is hosting “Taiyaki and Trivia” to celebrate AAPI Heritage Month. \nJoin us in Snell Quad\, catered by Taiyaki NYC.
URL:https://coe.northeastern.edu/event/sase-taiyaki-and-trivia/
END:VEVENT
END:VCALENDAR