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DTSTART;VALUE=DATE:20240305
DTEND;VALUE=DATE:20240308
DTSTAMP:20260519T233334
CREATED:20240125T181303Z
LAST-MODIFIED:20240226T160407Z
UID:41684-1709596800-1709855999@coe.northeastern.edu
SUMMARY:Northeastern University Virtual Spring Graduate Open House
DESCRIPTION:Join us for a three-day virtual open house event\, you’ll get a firsthand look into the Northeastern community and see if our top-ranked\, experience-driven education is right for you and your goals. \nDay 1: Connect with the faculty\, admissions department\, and current students from your program of choice\, and learn about our powerful co-op programs. \nDay 2: Meet Northeastern’s dedicated and helpful support staff from Global Student Success\, housing services\, financial services\, career design\, and many more. \nDay 3: Get all your questions about the application and enrollment process answered by our enrollment counselors. These include one-on-one drop-in sessions with a dedicated enrollment counselor you can join throughout the day. \nPlus\, you’ll be able to meet other graduate\, PhD\, and doctoral students from around the country and the globe. \nAnd with our virtual experience\, you’ll be able to customize your schedule to maximize your time and get the specific help and answers you need. \nFill out the form to secure your spot and join us on March 5-7.
URL:https://coe.northeastern.edu/event/northeastern-university-virtual-spring-graduate-open-house/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240305T100000
DTEND;TZID=America/New_York:20240305T110000
DTSTAMP:20260519T233334
CREATED:20240213T213923Z
LAST-MODIFIED:20240215T180413Z
UID:41851-1709632800-1709636400@coe.northeastern.edu
SUMMARY:Chemical Engineering Graduate Programs Open House
DESCRIPTION:You are invited to attend The Chemical Engineering Graduate Programs Open House on Tuesday\, March 5 from 10:00am-11:00am on Zoom! This is an exciting way to learn about the different programs and research areas from our Academic Coordinator and Associate Director of MS Programs. Come explore all the opportunities available in the Chemical Engineering department including co-op\, research\, and student groups! \nIf you are interested in applying\, Graduate School of Engineering admissions representatives can provide you with more information on the Double Husky Scholarship\, a 25% tuition discount for NU alumni\, and the Double Husky Quick Application. When you utilize this application\, you are not required to submit GRE scores\, letters of recommendation\, or an application fee. \nPlease join our Zoom session.
URL:https://coe.northeastern.edu/event/chemical-engineering-graduate-programs-open-house/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240312T180000
DTEND;TZID=America/New_York:20240312T200000
DTSTAMP:20260519T233334
CREATED:20240307T155326Z
LAST-MODIFIED:20240307T155432Z
UID:42682-1710266400-1710273600@coe.northeastern.edu
SUMMARY:IEEE Microsystems Boston Tech Talk: "Systems Based on Ultrasonic MEMS: Commercialization and Future Directions" with Professor David Horsley
DESCRIPTION:Speaker: Prof. David Horsley \nTalk: “Systems Based on Ultrasonic MEMS: Commercialization and Future Directions” \nDate & Time: Tuesday\, 12th March\, 6 – 8pm (Eastern Time) \nLocation:  \nNortheastern University – Innovation Campus\, Burlington\n147 S. Bedford Street\nBuilding 5 Conference Hall\nBurlington\, MA 01803 \nPlease RSVP at your earliest convenience. This will be an in-person meeting. \nAgenda: \n6 – 6:45pm: Networking Dinner\n6:45pm – 7:45pm: Tech Talk \nAbstract:\nThe increasing maturity of thin-film piezoelectric materials and the MEMS manufacturing ecosystem has enabled the rapid development of sensor systems based on piezoelectric micromachined ultrasonic transducers (PMUTs). In this talk\, I will describe work by my research group over the last decade to develop and commercialize PMUT-based systems for consumer electronics applications\, starting with air-coupled PMUTs used for time-of-flight (ToF) range-finding and human presence sensing. These ToF sensors were commercialized by my startup\, Chirp Microsystems (now part of TDK)\, and are used today in various products such as smart-locks\, robot vacuum cleaners\, and laptops. We subsequently developed an ultrasonic fingerprint sensor based on the monolithic integration of PMUTs with CMOS that is used for biometric authentication in consumer products today. A common feature of the ToF sensor and the fingerprint sensor is that they are systems that combine MEMS\, integrated circuits\, and algorithms. The ability to realize a complete ultrasonic system on chip (SoC) opens new research opportunities in areas such as portable medical imaging systems for point-of care ultrasound (POCUS) as well as wearable ultrasonic devices. \nSpeaker Bio:\nDavid A. Horsley is a Professor of Electrical and Computer Engineering at Northeastern University\, where he is co-director of the Institute for NanoSystems Innovation (NanoSI)\, and an Adjunct Professor of Mechanical Engineering at the University of California\, Berkeley\, where he is co-director of the Berkeley Sensor and Actuator Center (BSAC). Dr. Horsley co-founded several deep-tech companies\, most recently Chirp Microsystems (now part of TDK InvenSense)\, a manufacturer of MEMS-based ultrasonic sensors. Dr. Horsley was Co-Chair of the 2016 IEEE Sensors Conference\, Co-Chair of the 2017 Transducers Research Foundation Napa Microsystems Workshop\, and Co-Chair of the 2020 IEEE MEMS Conference. Dr. Horsley is an IEEE Fellow\, a Fellow of the National Academy of Inventors\, is a recipient of the National Science Foundation’s CAREER Award\, the UC Davis Outstanding Junior Faculty Award\, the 2016 NSF I/UCRC Association’s Schwarzkopf Award for Technological Innovation\, and the 2018 East Bay Innovation Award. He has authored or co-authored over 200 scientific papers and holds over 30 patents.
URL:https://coe.northeastern.edu/event/ieee-microsystems-boston-tech-talk-systems-based-on-ultrasonic-mems-commercialization-and-future-directions-with-professor-david-horsley/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240313T120000
DTEND;TZID=America/New_York:20240313T130000
DTSTAMP:20260519T233334
CREATED:20240229T165457Z
LAST-MODIFIED:20240229T165457Z
UID:42589-1710331200-1710334800@coe.northeastern.edu
SUMMARY:Chemical Engineering Spring Seminar Series: Dr. Michael Murrell
DESCRIPTION:Energetic Constraints on Biological Assembly and Motion \nOn small length-scales\, the mechanics of soft materials may be dominated by their interfacial properties as opposed to their bulk properties. These effects are described by equilibrium models of elasto-capillarity and wetting. In these models\, interfacial energies and bulk material properties are held constant. However\, in biological materials\, including living cells and tissues\, these properties are not constant\, but are ‘actively’ regulated and driven far from thermodynamic equilibrium. As a result\, the constraints on work produced during the various physical behaviors of the cell are unknown. Here\, by measurement of elasto-capillary effects during cell adhesion\, growth\, and motion\, we demonstrate that interfacial and bulk parameters violate equilibrium constraints and exhibit anomalous effects\, which depend upon a distance from equilibrium. However\, their anomalous properties are reciprocal\, and thus in combination reliably define energetic constraints on the production of work arbitrarily far from equilibrium. These results provide basic principles that govern biological assembly and behavior. \n\nMichael Murrell received his BS at Johns Hopkins University and his PhD at MIT. He then had a joint postdoctoral fellowship between the Institute for Biophysical Dynamics at the University of Chicago\, and the Institut Curie\, in Paris\, France. He now runs the Laboratory for Living Matter within the Systems Biology Institute at the Yale West Campus\, as part of the Biomedical Engineering and Physics Departments. His laboratory studies the non-equilibrium properties of biological systems\, as well as designs and engineers novel bio-inspired materials. His group comprises a diverse group of experimentalists\, computational scientists\, and theorists all driven to understand some of the most fundamental questions in biophysics.
URL:https://coe.northeastern.edu/event/chemical-engineering-spring-seminar-series-dr-michael-murrell/
LOCATION:103 Churchill\, 103 Churchill Hall\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3387735;-71.0889235
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240314T090000
DTEND;TZID=America/New_York:20240314T100000
DTSTAMP:20260519T233334
CREATED:20240108T145934Z
LAST-MODIFIED:20240110T205758Z
UID:41153-1710406800-1710410400@coe.northeastern.edu
SUMMARY:PI Day Graduate School of Engineering Overview
DESCRIPTION:To celebrate PI Day (3/14)\, the Graduate School of Engineering invites you to learn more about our graduate programs by attending a webinar hosted by the Director of Graduate Admissions\, Kelly Egorova on Thursday\, March\, 14 at 9:00am ET. Webinar details are below. \nWebinar Details:\nTopic: Graduate School of Engineering Overview\nDate: March 14\, 2024\nTime: 9:00 AM ET\nRegistration: https://us02web.zoom.us/webinar/register/WN_TpaPO_9QQfi3Ro5pjBQd_A
URL:https://coe.northeastern.edu/event/pi-day-graduate-school-of-engineering-overview/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240314T110000
DTEND;TZID=America/New_York:20240314T130000
DTSTAMP:20260519T233334
CREATED:20240305T150058Z
LAST-MODIFIED:20240305T150058Z
UID:42633-1710414000-1710421200@coe.northeastern.edu
SUMMARY:Breaking the Glass Lab
DESCRIPTION:In celebration of Women’s History Month\, join us for a lunch and panel discussion on Breaking the Glass Lab: Understanding the Realities Faced by Women in STEM Higher Education. \nHosted by Bioengineering and Mechanical & Industrial Engineering. \nRegister
URL:https://coe.northeastern.edu/event/breaking-the-glass-lab/
LOCATION:Fenway Center\, 77 St. Stephen Street\, Boston\, MA\, 02115\, United States
ORGANIZER;CN="Bioengineering":MAILTO:bioe@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240314T120000
DTEND;TZID=America/New_York:20240314T140000
DTSTAMP:20260519T233334
CREATED:20240307T191523Z
LAST-MODIFIED:20240307T191523Z
UID:42693-1710417600-1710424800@coe.northeastern.edu
SUMMARY:Email Etiquette
DESCRIPTION:Email communication is a crucial aspect of academic life\, serving as a primary way for students to connect with faculty\, inquire about opportunities\, seek support\, and more. That’s why we’re thrilled to present a 75-minute Zoom workshop led by two communication specialists from NU. \nIn this workshop\, you’ll gain valuable insights into communication concepts and strategies tailored to improve the effectiveness of your email messaging. Learn how to craft purposeful emails with appropriate tone and audience awareness\, ensuring your messages resonate with clarity and professionalism. \nDon’t miss out on this opportunity to sharpen your email communication skills and elevate your academic interactions! Register now to secure your spot. \nRegistration \nHosted by the Office of the Provost
URL:https://coe.northeastern.edu/event/email-etiquette/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240318T190000
DTEND;TZID=America/New_York:20240318T200000
DTSTAMP:20260519T233334
CREATED:20240311T135943Z
LAST-MODIFIED:20240311T135943Z
UID:42734-1710788400-1710792000@coe.northeastern.edu
SUMMARY:Tau Beta Pi x BOSE
DESCRIPTION:Join NU Tau Beta Pi in welcoming Dr. Chris Cherry\, vice president of global research at BOSE\, to speak about innovation and his career\, with plenty of time for Q&A after. The event is in SN 358.
URL:https://coe.northeastern.edu/event/tau-beta-pi-x-bose/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240319T120000
DTEND;TZID=America/New_York:20240319T130000
DTSTAMP:20260519T233334
CREATED:20240307T191846Z
LAST-MODIFIED:20240307T191846Z
UID:42698-1710849600-1710853200@coe.northeastern.edu
SUMMARY:Managing the Stress of Presentations workshop
DESCRIPTION:Join Global Learner Support and Wellness for an empowering one-hour workshop designed to equip you with invaluable tips on navigating the stress of presentations and exams. \nFrom study tools to mindfulness exercises\, we’ll explore effective strategies to help you thrive during finals season. Together\, we’ll cultivate healthy approaches to preparation and self-care that will set you up for success. \nDon’t miss this opportunity to enhance your well-being and excel academically! Register now to reserve your spot. \nRegister \nHosted by the Office of the Provost
URL:https://coe.northeastern.edu/event/managing-the-stress-of-presentations-workshop/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240320
DTEND;VALUE=DATE:20240325
DTSTAMP:20260519T233334
CREATED:20240108T145815Z
LAST-MODIFIED:20240108T145815Z
UID:41152-1710892800-1711324799@coe.northeastern.edu
SUMMARY:NSBE Annual Convention
DESCRIPTION:Join COE Graduate Admissions at the National Society of Black Engineers’ 50th Annual Convention in Atlanta\, GA! Ask your questions about our graduate engineering programs across the U.S. and Canada during the Career Fair on March 21-22. We look forward to meeting you there!
URL:https://coe.northeastern.edu/event/nsbe-annual-convention/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240320T120000
DTEND;TZID=America/New_York:20240320T150000
DTSTAMP:20260519T233334
CREATED:20240308T195353Z
LAST-MODIFIED:20240312T181251Z
UID:42710-1710936000-1710946800@coe.northeastern.edu
SUMMARY:MathWorks Day: Seeking Humanity via Technology: How AI Can Be Used to Reduce Maternal Mortality
DESCRIPTION:Seeking Humanity via Technology: How AI Can Be Used to Reduce Maternal Mortality by Louvere Walker-Hannon \nMaternal mortality continues to be a global issue however\, studies over the past 5 years identify a growing alarming trend in the United States with respect to maternal mortality. According to several studies from the Centers for Disease Control\, “Black women are three times more likely to die from a pregnancy-related cause than White women”. Many of these same studies have also acknowledged that most pregnancy-related deaths are preventable and that this alarming trend continues to grow. This session will entail providing an overview of historical approaches to this issue. The emphasis of this presentation will identify how Artificial Intelligence (AI) could be used to reduce maternal mortality and how AI could be used to reduce maternal mortality. \nBio: Louvere Walker-Hannon is a MathWorks application engineering senior team lead who provides technical guidance and strategic direction on AI/data science workflows for various applications. She also leads a team of application engineers. She has a bachelor’s degree in biomedical engineering and a master’s degree in geographic information technology/remote sensing. She has presented at several STEM-related conferences on various topics and serves as an avid STEM advocate. Louvere volunteers with Black Girls CODE\, the Society of WomenEngineers (SWE)\, and the National Society of Black Engineers (NSBE). She is also a recipient of the SWE WE Local 2022 Engaged Advocate Award and is a second-year SWE Senator. In 2023\, Louvere was highlighted as one of Boston University’s College of Engineering Distinguished Alumni and identified as one of the 10 Most Inspiring Women DrivingTechnological Progress\, in volume 11 of The Silicon Leaders magazine. \nLunch 12:00–1:00 pm\nTalk 1:00-1:30 pm\nPoster Session and Demonstrations 1:30–3:00 pm \nRegister \nMathWorks Demos: \n\n\n\nTitle\nSpeaker\n\n\nHeat Transfer for Chemical and Mechanical Engineers\nAycan Hacioglu\, Mehdi Vahab\n\n\nAI in Chemical and Mechanical Engineering\nAycan Hacioglu\, Mae Markowski\n\n\nUsing MATLAB Online with GitHub\nYann Debray\, Tharikaa Kumar\n\n\n5G Classification Neural Network\nIman Abdalla\n\n\nCryptocurrency Price Prediction using MATLAB and Python\nMatt Hannum
URL:https://coe.northeastern.edu/event/mathworks-day-seeking-humanity-via-technology-how-ai-can-be-used-to-reduce-maternal-mortality/
LOCATION:Raytheon Amphitheater (240 Egan)\, 360 Huntington Ave\, 240 Egan\, Boston\, MA\, 02115\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240321T120000
DTEND;TZID=America/New_York:20240321T130000
DTSTAMP:20260519T233334
CREATED:20240307T192131Z
LAST-MODIFIED:20240307T192131Z
UID:42700-1711022400-1711026000@coe.northeastern.edu
SUMMARY:Negotiating Job Offers
DESCRIPTION:Are you ready to take your career to the next level? Don’t miss this opportunity to gain valuable insights into effectively negotiating job offers. \nIn this engaging session\, Anne Grieves will guide you through the process of communicating your worth to employers and provide expert tips for negotiating your salary and benefits package. Whether you’re entering the workforce for the first time or looking for tips for the future\, mastering the art of negotiation is key to securing the best possible opportunities. \nRegister now to reserve your spot. \nHosted by the Office of the Provost
URL:https://coe.northeastern.edu/event/negotiating-job-offers/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240321T120000
DTEND;TZID=America/New_York:20240321T133000
DTSTAMP:20260519T233334
CREATED:20240319T141109Z
LAST-MODIFIED:20240319T141109Z
UID:42910-1711022400-1711027800@coe.northeastern.edu
SUMMARY:Julian Gutierrez PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nJulian Gutierrez \nTitle:\nTowards Real-Time Safe Flight Paths for Urban Air Mobility \nDate:\n3/21/2024 \nTime:\n12:00:00 PM \nLocation: Zoom \nCommittee Members:\nProf. David Kaeli (Advisor)\nProf. Pau Closas\nDr. Evan Dill (NASA)\nDr. Natasha Neogi (NASA) \nAbstract:\nThe emergence and development of advanced technologies and vehicle types have created a growing demand for introducing new forms of flight operations. These new and increasingly complex operational paradigms\, such as Advanced and Urban Air Mobility (AAM/UAM)\, present regulatory authorities and the aviation community with the challenge of finding methods to integrate these emerging operations without significant additional risk to pedestrians and infrastructure. Predictive and autonomous risk mitigation capabilities become critical to meet this challenge. However\, urban environments experience effects that are computationally expensive to model\, limiting conventional aviation concepts\, policy\, and risk prediction tools from being effectively translated into this space. With the emergence of High-Performance Computing (HPC) ecosystems in the last two decades\, we can use these software and hardware capabilities to help bridge the gap between real-time predictive responses and modeling accuracy. \nIn this dissertation we first present a simulation framework to estimate the quality of Global Navigation Satellite System (GNSS) performance for autonomous aircraft in urban environments. We propose a new algorithm designed for HPC to accelerate modeling the characteristic effects of dense urban canyons on GNSS\, allowing the extension of established GNSS integrity techniques into urban navigation. Additionally\, we provide a thorough validation of the simulator\, which proves high-accuracy modeling when compared to sensors in the real world. Second\, we use this simulation framework to provide situational awareness when processing the raw output of a GNSS sensor. This effort focuses on multipath mitigation\, which reduces the error in the estimated position solution. Third\, we use this simulation framework as the input into a new 4D path-planning algorithm based on an adaptation of the Bellman-Ford algorithm. HPC techniques are employed to accelerate the algorithm to produce flight paths that minimize exposure to GNSS risks. We evaluate the computational cost of satellite availability fluctuations by prioritizing events when satellite availability changes as triggers for these updates.
URL:https://coe.northeastern.edu/event/julian-gutierrez-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240326T120000
DTEND;TZID=America/New_York:20240326T130000
DTSTAMP:20260519T233334
CREATED:20240322T143807Z
LAST-MODIFIED:20240322T143807Z
UID:42998-1711454400-1711458000@coe.northeastern.edu
SUMMARY:Negotiation Fundamentals: 5 Steps to Negotiation Success
DESCRIPTION:Get ready for our next Graduate Greatness webinar focusing on the art of negotiation! \n📅 Date: March 26\, 2024 \n🕒 Time: 12:00 pm – 1:00 pm \n📍 Location: Zoom Webinar \nNegotiation is an essential skill that impacts every aspect of our lives. Whether it’s securing a job offer\, navigating contracts\, or even managing everyday situations\, mastering negotiation can elevate your success. \nJoin us for an enlightening presentation by negotiation expert Roy Weissman\, where you’ll gain invaluable insights into negotiation best practices and fundamental skills. Discover how to transition from basic bargaining to strategic negotiation tactics that yield optimal outcomes. \nNo matter your profession or level of experience\, this webinar will empower you with practical strategies and hands-on experience to enhance your negotiation prowess. \nRegister for the event: http://tinyurl.com/2xythc38
URL:https://coe.northeastern.edu/event/negotiation-fundamentals-5-steps-to-negotiation-success/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240327T120000
DTEND;TZID=America/New_York:20240327T130000
DTSTAMP:20260519T233334
CREATED:20240307T180833Z
LAST-MODIFIED:20240307T180901Z
UID:42685-1711540800-1711544400@coe.northeastern.edu
SUMMARY:Chemical Engineering Spring Seminar Series: Dr. Christina Chan
DESCRIPTION:Role of microenvironment on mediating diseases\, DNA repair\, and lipid alterations \nOur group incorporates metabolic engineering and systems biology approaches in combination with biochemical and molecular biology measurements to identify targets and disease biomarkers. To modulate these targets and pathway we are concomitantly developing polymeric-based drug delivery systems. \nWe apply a multifaceted approach in investigating the role of soluble cues (e.g.\, elevated fatty acid levels\, PFAS) in the microenvironment on modulating the signaling and regulatory pathways that contribute to diseases. These extracellular signals are mainly in the form of soluble factors that activate intracellular signaling cascades that drive changes in the cell. Our group has identified that saturated fatty acids (i.e.\, palmitate)\, which are well studied for their roles in metabolism\, can also activate signaling pathways that affect proteostasis. Through biochemical and biophysical studies\, we found that palmitate binds directly to proteins involved in proteostasis to modulate their activity and downstream signaling to alter DNA repair\, which has implications on chemotolerance\, lipid profile\, and heart disease. \n\nChristina Chan is a University Distinguished Professor and Interim Chairperson of Chemical Engineering at Michigan State University (MSU). She also has appointments in the Departments of Biochemistry and Molecular Biology\, Biomedical Engineering\, and Computer Science and Engineering. Prior to joining MSU in 2002\, she was a post-doctoral fellow at the Center for Engineering in Medicine at the Harvard Medical School. Chan earned her B.S. in Chemical Engineering from Columbia University and her M.S. and Ph.D. in Chemical and Biochemical Engineering from the University of Pennsylvania. She spent 8 years in DuPont prior to returning to academia. Her laboratory applies a multifaceted approach in investigating the role of soluble cues in the microenvironment on modulating the signaling and regulatory pathways that contribute to diseases. To modulate these targets and pathways\, her laboratory is developing polymeric-based drug delivery systems as well as tissue engineering platforms that capitalize on how scaffolds\, cells\, and biologically active molecules interact to form functional tissues. Her group has published more than 165 journal articles\, reviews\, book chapters and reviewed conference papers. She was elected Fellow of the American Institute of Medical and Biological Engineering (AIMBE)\, AIChE\, and AAAS.
URL:https://coe.northeastern.edu/event/chemical-engineering-spring-seminar-series-dr-christina-chan/
LOCATION:103 Churchill\, 103 Churchill Hall\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3387735;-71.0889235
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=103 Churchill 103 Churchill Hall 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=103 Churchill Hall\, 360 Huntington Ave:geo:-71.0889235,42.3387735
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240327T120000
DTEND;TZID=America/New_York:20240327T150000
DTSTAMP:20260519T233334
CREATED:20240321T142641Z
LAST-MODIFIED:20240321T142641Z
UID:42977-1711540800-1711551600@coe.northeastern.edu
SUMMARY:UMass Dartmouth Jobs\, Internship & Graduate School Expo
DESCRIPTION:Calling all Corsairs! Meet a COE Graduate Admissions team member at the UMass Dartmouth Jobs\, Internship & Graduate School Expo! Ask your questions about Northeastern University and the Graduate School of Engineering on March 27th.
URL:https://coe.northeastern.edu/event/umass-dartmouth-jobs-internship-graduate-school-expo/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240328T110000
DTEND;TZID=America/New_York:20240328T120000
DTSTAMP:20260519T233334
CREATED:20240306T150314Z
LAST-MODIFIED:20240321T190531Z
UID:42671-1711623600-1711627200@coe.northeastern.edu
SUMMARY:Huan Wang PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nHuan Wang \nTitle:\nTowards Efficient Deep Learning in Computer Vision via Network Sparsity and Distillation \nDate:\n3/28/2024 \nTime:\n11:00:00 AM \nZoom \nCommittee Members:\nProf. Yun Fu (Advisor)\nProf. Octavia Camps\nProf. Zhiqiang Tao \nAbstract:\nAI\, empowered by deep learning\, has been profoundly transforming the world. However\, the excessive size of these models remains a central obstacle that limits their broader utility. Modern neural networks commonly consist of millions of parameters\, with foundation models extending to billions. The rapid expansion in model size introduces many challenges including training cost\, sluggish inference speed\, excessive energy consumption\, and negative environmental implications such as increased CO2 emissions. \nAddressing these challenges necessitates the adoption of efficient deep learning. The dissertation focuses on two overarching approaches\, network pruning and knowledge distillation\, to enhance the efficiency of deep learning models in the context of computer vision. Network pruning focuses on eliminating redundant parameters in a model while preserving the performance. Knowledge distillation aims to enhance the performance of the target model\, referred to as the “student\,” by leveraging guidance from a stronger model\, known as the “teacher”. This approach leads to performance improvements in the target model without reducing its size. \nIn this defense presentation\, I will start with the background and major challenges of leveraging these techniques to improve the efficiency of deep neural networks. Then\, I shall present the proposed solutions for various vision tasks\, including image classification\, single-image super-resolution\, novel view synthesis / neural rendering / NeRF / NeLF\, text-to-image generation / diffusion models\, and photorealistic head avatars. Extensive results and analyses will justify the efficacy of the proposed approaches\, demonstrating that pruning and distillation make a generic and complete framework for efficient deep learning in various domains. Finally\, a comprehensive summary (with takeaways) and outlook of the future work will conclude the presentation.
URL:https://coe.northeastern.edu/event/human-wang-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240328T120000
DTEND;TZID=America/New_York:20240328T130000
DTSTAMP:20260519T233334
CREATED:20240322T144012Z
LAST-MODIFIED:20240322T144419Z
UID:43002-1711627200-1711630800@coe.northeastern.edu
SUMMARY:Interdisciplinary Thinking as a Professional Skill
DESCRIPTION:Our next Graduate Greatness webinar is here to broaden your horizons with Interdisciplinary Thinking as a Professional Skill. \n📅 Date: Thursday\, March 28th \n🕒 Time: 12:00 – 1:00 p.m. EDT \n📍 Location: Zoom Webinar \nIn today’s complex world\, the ability to think across disciplines is more valuable than ever. Join us for an engaging session where we’ll explore the power of interdisciplinary thinking as a professional skill. \nLed by David Dawson\, this webinar will explore strategies for integrating diverse perspectives\, fostering creativity\, and solving complex problems. Interdisciplinary thinking can boost your career and drive innovation. \nRegister for the event: http://tinyurl.com/2tfsskat
URL:https://coe.northeastern.edu/event/interdisciplinary-thinking-as-a-professional-skill/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240328T160000
DTEND;TZID=America/New_York:20240328T173000
DTSTAMP:20260519T233334
CREATED:20240318T183812Z
LAST-MODIFIED:20240318T183812Z
UID:42900-1711641600-1711647000@coe.northeastern.edu
SUMMARY:3MT (Three Minute) Thesis
DESCRIPTION:This event is being presented by Graduate Women in Science and Engineering (GWISE) and Northeastern University Library. It’s a competition where PhD/ graduate students can share their thesis research under 3 minutes and compete for Cash prizes. It is a great opportunity for students to practice their communication skills and to share their research with a broader audience.
URL:https://coe.northeastern.edu/event/3mt-three-minute-thesis/
ORGANIZER;CN="GWiSE%3A Graduate Women in Science and Engineering":MAILTO:gwise.neu@gmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240329T100000
DTEND;TZID=America/New_York:20240329T120000
DTSTAMP:20260519T233334
CREATED:20240319T141258Z
LAST-MODIFIED:20240319T141258Z
UID:42908-1711706400-1711713600@coe.northeastern.edu
SUMMARY:Matthew Wallace MS Thesis Defense
DESCRIPTION:Announcing:\nMS Thesis Defense \nName:\nMatthew Wallace \nTitle:\nModel Predictive Planning \nDate:\n3/29/2024 \nTime:\n10:00:00 AM \nLocation:\nRoom: HS 204.  Link: Teams \nCommittee Members:\nProf. Laurent Lessard (Advisor)\nProf. Michael Everett\nProf. Derya Aksaray \nAbstract:\nThis thesis presents Model Predictive Planning (MPP)\, a trajectory planner for low-agility vehicles such as a fixed-wing aircraft to navigate obstacle-laden environments.  MPP consists of (1) a multi-path planning procedure that identifies candidate paths\, (2) a raytracing procedure that generates linear constraints around these paths that enforce obstacle avoidance\, and (3) a convex quadratic program that finds a feasible trajectory within these constraint if one exists. Low-agility aircraft cannot track arbitrary paths\, so refining a given path into a trajectory that respects the vehicle’s limited maneuverability and avoids obstacles often leads to an infeasible optimization problem. The critical feature of MPP is that it efficiently considers multiple candidate paths during the refinement process\, thereby greatly increasing the chance of finding a feasible and trackable trajectory. I begin by presenting a background on path planning\, trajectory optimization\, and Model Predictive Control.  This is followed by a presentation of the MPP algorithm.  Finally\, I demonstrate the effectiveness of MPP on both a longitudinal and 3D aircraft model.
URL:https://coe.northeastern.edu/event/matthew-wallace-ms-thesis-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240401T103000
DTEND;TZID=America/New_York:20240401T113000
DTSTAMP:20260519T233334
CREATED:20240319T140923Z
LAST-MODIFIED:20240319T140923Z
UID:42912-1711967400-1711971000@coe.northeastern.edu
SUMMARY:Reza Vafaee PhD Proposal Review
DESCRIPTION:Announcing:\nPhD Proposal Review \nName:\nReza Vafaee \nTitle:\nEfficient Algorithms for Sparse Sensor Scheduling in Large-Scale Dynamical Systems with Performance Guarantees \nDate:\n4/1/2024 \nTime:\n10:30:00 AM \nLocation: Zoom \nCommittee Members:\nProf. Milad Siami (Advisor)\nProf. Eduardo Sontag\nProf. Laurent Lessard\nProf. Alex Olshevsky (Boston University) \nAbstract:\nThis research proposal introduces innovative frameworks for sparse sensor scheduling in large-scale dynamical networks. The first framework addresses sensor scheduling in discrete-time linear time-invariant dynamical networks\, presenting a novel learning-based rounding method to convert weighted sensor schedules into sparse\, unweighted schedules while maintaining comparable observability performance. The second framework extends the approach to dynamically select sensors for linear time-varying systems\, utilizing an online sparse sensor scheduling framework with randomized algorithms to approximate fully-sensed systems with a constant average number of active sensors at each time step. Finally\, a myopic approach within a Kalman filtering framework is adopted in the third framework\, addressing non-submodular sensor scheduling in large-scale linear time-varying dynamics. A simple greedy algorithm is employed\, providing approximation bounds based on submodularity and curvature concepts. Simulation results validate the theoretical foundations and demonstrate the proposed approach’s superiority over existing methods.
URL:https://coe.northeastern.edu/event/reza-vafaee-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240402T090000
DTEND;TZID=America/New_York:20240402T100000
DTSTAMP:20260519T233334
CREATED:20240223T211942Z
LAST-MODIFIED:20240223T211942Z
UID:42518-1712048400-1712052000@coe.northeastern.edu
SUMMARY:Learn about engineering program opportunities in Seattle\, WA
DESCRIPTION:The Graduate School of Engineering is proud to offer programs on many of Northeastern University’s multiple global campuses. In this webinar\, we focus on spotlighting the Seattle\, WA campus. You’ll have an opportunity to learn more about the programs and opportunities available on this campus from admissions and campus representatives.
URL:https://coe.northeastern.edu/event/learn-about-engineering-program-opportunities-in-seattle-wa/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240402T100000
DTEND;TZID=America/New_York:20240402T110000
DTSTAMP:20260519T233334
CREATED:20240223T212709Z
LAST-MODIFIED:20240223T212709Z
UID:42520-1712052000-1712055600@coe.northeastern.edu
SUMMARY:Learn about engineering program opportunities in Oakland\, CA
DESCRIPTION:The Graduate school of Engineering is proud to offer programs on many of Northeastern University’s multiple global campuses. In this webinar\, we focus on spotlighting the Oakland\, CA campus. You’ll have an opportunity to learn more about the programs and opportunities available on this campus from admissions and campus representatives.
URL:https://coe.northeastern.edu/event/learn-about-engineering-program-opportunities-in-oakland-ca/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240403T110000
DTEND;TZID=America/New_York:20240403T123000
DTSTAMP:20260519T233334
CREATED:20240403T182458Z
LAST-MODIFIED:20240403T182458Z
UID:43174-1712142000-1712147400@coe.northeastern.edu
SUMMARY:Batool Salehihikouei PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nBatool Salehihikouei \nTitle:\nLeveraging Deep Learning on Multimodal Sensor Data for Wireless Communication: From mmWave Beamforming to Digital Twins \nDate:\n4/3/2024 \nTime:\n11:00:00 AM \nLocation: EXP-601A \nCommittee Members:\nProf. Kaushik Chowdhury (Advisor)\nProf. Hanumant Singh\nProf. Josep Jornet\nDr. Mark Eisen \nAbstract:\nWith the widespread Internet of Things (IoT) devices\, a wide variety of sensors are now present in different environments. For example\, self-driving vehicles and automated warehouses depend on sensor information for navigation and management of the robots\, respectively. In this dissertation\, we present methods\, where these sensors are re-purposed to assist network management in wireless communication\, especially when classic approaches fall short to provide the required quality of service (QoS). This thesis presents data-driven and AI-based methods\, where the multimodal sensor information is used for two applications: (i) beamforming at the mmWave band and (ii) joint optimization of the navigation and network management in warehouse environments. In the first part\, we study multimodal beamforming methods for mmWave vehicular networks. First\, we present deep learning fusion algorithms\, where the inputs from a multitude of sensor modalities such as GPS (Global Positioning System)\, camera\, and LiDAR (Light Detection and Ranging) are combined towards predicting the optimum beam at the mmWave band. We prove that fusing the multimodal sensor data improves the prediction accuracy\, compared to using single modalities. Second\, we study the trade-off between the accuracy and cost of different learning strategies and demonstrate that federated learning is the most successful learning strategy\, with respect to the communication overhead. Third\, we propose algorithms to further optimize the communication overhead by incorporating a pruning strategy tailored to the disturbed nature of the federated learning systems. Fourth\, we propose a modality-agnostic deep learning paradigm that operates on any possible combination of sensor modalities. In part two\, we propose using digital twins to overcome the challenges of scarcity of data and close-world assumption in deep learning algorithms. A digital twin is a replica of a real world entity\, which is typically used for studying the impact of any configuration settings in a safe\, digital environment. In this dissertation\, we propose a framework that operates by harmonic usage of the DL models and running emulations in the twin. Moreover\, we use digital twins to generate training labels and fine-tune the models for unseen scenarios. Finally\, we study a robotic industrial setting\, where the path planning policy is continuously updated by monitoring the dynamics of the real world\, constructing the digital twin\, and updating the policy. The constructed twin captures the features of both physical and RF environments in the digital world and includes a reinforcement learning algorithm that jointly optimizes navigation and network resource management.
URL:https://coe.northeastern.edu/event/batool-salehihikouei-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240403T120000
DTEND;TZID=America/New_York:20240403T130000
DTSTAMP:20260519T233334
CREATED:20240223T212831Z
LAST-MODIFIED:20240223T212831Z
UID:42524-1712145600-1712149200@coe.northeastern.edu
SUMMARY:Learn about engineering program opportunities in Silicon Valley \, CA
DESCRIPTION:The Graduate school of Engineering is proud to offer programs on many of Northeastern University’s multiple global campuses. In this webinar\, we focus on spotlighting the Silicon Valley\, CA campus. You’ll have an opportunity to learn more about the programs and opportunities available on this campus from admissions and campus representatives.
URL:https://coe.northeastern.edu/event/learn-about-engineering-program-opportunities-in-silicon-valley-ca/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240403T120000
DTEND;TZID=America/New_York:20240403T130000
DTSTAMP:20260519T233334
CREATED:20240326T142857Z
LAST-MODIFIED:20240326T142857Z
UID:43035-1712145600-1712149200@coe.northeastern.edu
SUMMARY:Chemical Engineering Spring Seminar Series: Dr. Sindia M. Rivera Jiménez
DESCRIPTION:Professional Organizations and Social Responsibility in Chemical Engineering Education \nProfessional organizations (POs) are established communities that significantly influence the competencies and values of engineers\, but the impact of their interaction with academia on undergraduate education is not fully understood. This study addresses this gap by exploring how engineering faculty in POs strategically incorporate social responsibility into their teaching. Relying on Paulo Freire’s critical consciousness and the Transformational Agency framework\, it examines faculty reflections on societal and power dynamics for curriculum change. \nConducted over eight months\, the study focuses on a Community of Practice (CoP) within the American Institute of Chemical Engineering’s Education Division\, engaging faculty from multiple institutions. We employed qualitative methods\, analyzing interview data through thematic analysis with In-Vivo and Axial coding. Preliminary results highlight how the CoP influences faculty’s reflective practices and understanding of societal structures\, suggesting it enhances educators’ critical awareness and ability to integrate social responsibility into their teaching. \nThe findings deepen our understanding of POs’ role in evolving engineering education. They showcase how educators’ involvement in POs can shape socially responsible engineers\, addressing the complex societal roles engineers face. This seminar aims to inspire educators with strategies for creating transformative learning environments. \n\nDr. Rivera-Jiménez is an Assistant Professor in the Department of Engineering Education at the University of Florida and is affiliated with the Department of Chemical Engineering and the Institute of Higher Education. Her research group focuses on community-driven methods to improve practices and policies that enhance the professional formation of engineers and impact the success of diverse engineering communities\, including faculty\, undergraduate and graduate students\, and transfer students. Current projects include faculty support via professional societies\, student motivation and emotions in blended learning\, and studying diverse transfer student success within organizational contexts. \nAdditionally\, she hosts “The Engineering Professor Speaks Education Podcast\,” a bilingual series exploring the nuances of being an effective engineering educator. Her most recent accolades include the AIChE IDEAL Star Award (2021)\, the AIChE Education Division Service Award (2022)\, and the ASEE Education Research Methods Apprentice Faculty Grantee Award (2023).
URL:https://coe.northeastern.edu/event/chemical-engineering-spring-seminar-series-dr-sindia-m-rivera-jimenez/
LOCATION:103 Churchill\, 103 Churchill Hall\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3387735;-71.0889235
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=103 Churchill 103 Churchill Hall 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=103 Churchill Hall\, 360 Huntington Ave:geo:-71.0889235,42.3387735
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240403T153000
DTEND;TZID=America/New_York:20240403T170000
DTSTAMP:20260519T233334
CREATED:20240319T141441Z
LAST-MODIFIED:20240319T141441Z
UID:42906-1712158200-1712163600@coe.northeastern.edu
SUMMARY:Kaustubh Shivdikar PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nKaustubh Shivdikar \nTitle:\nEnabling Accelerators for Graph Computing \nDate:\n4/3/2024 \nTime:\n3:30 PM \nLocation: Zoom \nCommittee Members:\nProf. David Kaeli (Advisor)\nProf. Devesh Tiwari\nProf. Ajay Joshi (Boston University)\nProf. John Kim (KAIST)\nProf. José Luis Abellán (University of Murcia) \nAbstract:\nThe advent of Graph Neural Networks (GNNs) has revolutionized the field of machine learning\, offering a novel paradigm for learning on graph-structured data. Unlike traditional neural networks\, GNNs are capable of capturing complex relationships and dependencies inherent in graph data\, making them particularly suited for a wide range of applications including social network analysis\, molecular chemistry\, and network security. The impact of GNNs in these domains is profound\, enabling more accurate models and predictions\, and thereby contributing significantly to advances in these fields. \nGNNs\, with their unique structure and operation\, present new computational challenges compared to conventional neural networks. This requires comprehensive benchmarking and a thorough characterization of GNNs to obtain insight into their computational requirements and to identify potential performance bottlenecks. In this thesis\, we aim to develop a better understanding of how GNNs interact with the underlying hardware and will leverage this knowledge as we design specialized accelerators and develop new optimizations\, leading to more efficient and faster GNN computations. \nA pivotal component within GNNs is the Sparse General Matrix-Matrix Multiplication (SpGEMM) kernel\, known for its computational intensity and irregular memory access patterns. In this thesis\, we address the challenges posed by SpGEMM by implementing a highly optimized hashing-based SpGEMM kernel tailored for a custom accelerator. This optimization is crucial to enhancing the performance of GNN workloads\, ensuring that the acceleration potential of custom hardware is fully realized. \nSynthesizing these insights and optimizations\, we design state-of-the-art hardware accel-erators capable of efficiently handling various GNN workloads. Our accelerator architectures are built on our characterization of GNN computational demands\, providing clear motivation for our approaches. Furthermore\, we extend our exploration to emerging GNN workloads in the domain of graph neural networks. This exploration into novel models underlines our comprehensive approach\, as we strive to enable accelerators that are not just performant\, but also versatile\, able to adapt to the evolving landscape of graph computing.
URL:https://coe.northeastern.edu/event/kaustubh-shivdikar-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240404T120000
DTEND;TZID=America/New_York:20240404T130000
DTSTAMP:20260519T233334
CREATED:20240322T144254Z
LAST-MODIFIED:20240322T144254Z
UID:43007-1712232000-1712235600@coe.northeastern.edu
SUMMARY:Conflict Resolution and Effective Communication Skills
DESCRIPTION:Join us for our upcoming Graduate Greatness webinar on “Conflict Resolution and Effective Communication” presented by Kimberly Wong. \n📅 Date: Thursday\, April 4th \n🕒 Time: 12:00 – 1:00 p.m. EDT \n📍 Location: Zoom Webinar \nConflict is an inevitable part of any academic journey\, but with effective communication skills\, challenges can be transformed into opportunities for growth. In this virtual workshop\, we’ll dive into strategies for navigating conflict during graduate school. \nParticipants will have the opportunity to examine their own approaches to conflict\, identifying strengths and barriers along the way. Together\, we’ll explore methods to foster trust and understanding in professional relationships\, providing you with concrete strategies for improving dialogue with faculty\, staff\, and classmates. \nRegister for the event: http://tinyurl.com/mw79jbhz
URL:https://coe.northeastern.edu/event/conflict-resolution-and-effective-communication-skills/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240404T130000
DTEND;TZID=America/New_York:20240404T140000
DTSTAMP:20260519T233334
CREATED:20240403T182208Z
LAST-MODIFIED:20240403T182208Z
UID:43178-1712235600-1712239200@coe.northeastern.edu
SUMMARY:Anu Jagannath PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nAnu Jagannath \nTitle:\nDeep Learning at the Edge for Future G Networks: RF Signal Intelligence for Comprehensive Spectrum Awareness \nDate:\n4/4/2024 \nTime:\n1:00:00 PM \nCommittee Members:\nProf. Tommaso Melodia (Advisor)\nProf. Kaushik Chowdhury\nProf. Yanzhi Wang \nAbstract:\nFuture communication networks must address the scarce spectrum to accommodate extensive growth of heterogeneous wireless devices. Efforts are underway to address spectrum coexistence\, enhance spectrum awareness\, and bolster authentication schemes. Wireless signal recognition is becoming increasingly more significant for spectrum monitoring\, spectrum management\, secure communications\, among others. Consequently\, comprehensive spectrum awareness at the edge has the potential to serve as a key enabler for the emerging beyond 5G (fifth generation) networks. State-of-the-art studies in this domain have (i) only focused on a single task – modulation or signal (protocol) classification or radio frequency fingerprinting – which in many cases is insufficient information for a system to act on\, (ii) consider either radar or communication waveforms (homogeneous waveform category)\, and (iii) does not address edge deployment during neural network design phase. In this dissertation\, deep learning is applied to the various signal recognition problems from  a multi-task perspective with an emphasis on edge deployment. To address edge deployment\, various techniques are applied to solve the signal recognition problem under consideration (modulation\, wireless protocol\, emitter fingerprint recognition) to design scalable and computationally efficient framework. While designing the edge deployable architectures\, the generalization capability of the architectures are evaluated under various circumstances to quantify their performance under real-world settings such as emissions from actual emitters (commercial emissions wherever applicable)\, training with a different propagation scenario and testing under a never-before-seen setting. \nThe study was sectioned into different stages where multi-task learning is first applied to solving wireless standard and modulation recognition\, followed by applying deep compression for CBRS radar waveform classification\, next radio frequency fingerprinting for commercial WiFi and Bluetooth emissions were studied utilizing novel multi-task attentional architectures\, and finally the multi-task learning together with deep compression was employed to deploy the architectures in a real-time streaming radio testbed for real-time inferencing of wireless standard and modulation recognition. The feasibility of employing deep compression techniques are carefully evaluated in a real-world deployment setting to quantify the performance from a computational and inference capacity perspective.
URL:https://coe.northeastern.edu/event/anu-jagannath-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240404T153000
DTEND;TZID=America/New_York:20240404T170000
DTSTAMP:20260519T233334
CREATED:20240319T141622Z
LAST-MODIFIED:20240319T141622Z
UID:42904-1712244600-1712250000@coe.northeastern.edu
SUMMARY:Nicolas Bohm Agostini PhD Proposal Review
DESCRIPTION:Announcing:\nPhD Proposal Review \nName:\nNicolas Bohm Agostini \nTitle:\nHardware/Software Codesign and Compiler Techniques for Efficient Hardware Acceleration of Dense Linear Algebra Kernels and Machine Learning Applications \nDate:\n4/4/2024 \nTime:\n3:30:00 PM \nLocation: Zoom \nCommittee Members:\nProf. David Kaeli (Advisor)\nProf. Gunar Schirner\nProf. José Luis Abellán (University of Murcia)\nAntonino Tumeo (PNNL) \nAbstract:\nToday’s linear algebra and machine learning applications (ML) continue to grow in size and complexity\, placing rapidly increasing demands on the underlying hardware and software systems. To address these issues\, hardware designers have proposed using custom accelerators explicitly designed for accelerating these demanding workloads. What needs to be improved is the ability to perform efficient hardware/software (HW/SW) co-design in order to reap the full benefits from these platforms. This thesis presents an integrated solution to facilitate HW/SW accelerator design. We also address issues in accelerator deployment\, enabling rapid prototyping\, integrated benchmarking\, and comprehensive performance analysis of custom accelerators. \nIn this thesis\, we demonstrate the value of a lightweight system modeling library integrated into the build/execution environment\, leveraging TensorFlow~Lite for deployment. We also explore efficient design space exploration of different classes of accelerators while considering the impact of parameters. Secondly\, we employ the Multi-Level Intermediate Representation (MLIR) compiler framework to automatically partition host code from accelerator code\, pre-optimizing the latter for improved high-level synthesis designs and high-quality accelerated kernels. Lastly\, we propose compiler extensions to automate the generation and optimization of communication between the host CPU and AXI-based accelerators. \nWe present novel solutions that enable more efficient and effective design space exploration\, optimization\, and deployment of custom accelerators. The utility of these approaches is demonstrated through experiments with specific accelerator designs and key linear algebra and ML workloads. Most importantly\, these solutions empower high-level language users\, such as domain scientists\, to participate in the design of new accelerator features.
URL:https://coe.northeastern.edu/event/nicolas-bohm-agostini-phd-proposal-review/
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END:VCALENDAR