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DTSTART;TZID=America/New_York:20240326T120000
DTEND;TZID=America/New_York:20240326T130000
DTSTAMP:20260405T065112
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:20260405T065112
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240327T120000
DTEND;TZID=America/New_York:20240327T150000
DTSTAMP:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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:20260405T065112
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240403T153000
DTEND;TZID=America/New_York:20240403T170000
DTSTAMP:20260405T065112
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:20260405T065112
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:20260405T065112
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:20240404T140000
DTEND;TZID=America/New_York:20240404T150000
DTSTAMP:20260405T065112
CREATED:20240118T204753Z
LAST-MODIFIED:20240321T134630Z
UID:41487-1712239200-1712242800@coe.northeastern.edu
SUMMARY:Mock Interview: A CommLab Workshop Series
DESCRIPTION:Join the CommLab every Thursday from 2-3pm ET\, we’ll delve into the intricacies of interviews\, unveiling effective tricks and preparation strategies for any interview scenario. Engage in an interactive setting as we dissect the overall interview experience\, discuss common interview scenarios\, and share insights on what to do during critical moments. Join this hybrid workshop series either in person in room 206 Egan or through Zoom.
URL:https://coe.northeastern.edu/event/mock-interview-a-commlab-workshop-series/2024-04-04/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=206 Egan 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=360 Huntington Ave:geo:-71.0888734,42.3376753
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240404T153000
DTEND;TZID=America/New_York:20240404T170000
DTSTAMP:20260405T065112
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/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240408T110000
DTEND;TZID=America/New_York:20240408T130000
DTSTAMP:20260405T065112
CREATED:20240129T143802Z
LAST-MODIFIED:20240321T135109Z
UID:41741-1712574000-1712581200@coe.northeastern.edu
SUMMARY:CommLab Writing Hours
DESCRIPTION:Graduate students\, are you looking for a place for focused research writing time?  Join the CommLab for writing hours on Mondays from 11 am-1 pm ET.  Drop in any Monday and stay for a short time or the whole two hours.  CommLab Fellows will be available to provide feedback on your writing.  We will be meeting in 335 Curry Student Center.
URL:https://coe.northeastern.edu/event/commlab-writing-hours-2/2024-04-08/
LOCATION:335 CSC\, 360 Huntington Ave\, CSC\, Boston\, MA\, 02115\, United States
GEO:42.339110916473;-71.087682620746
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=335 CSC 360 Huntington Ave CSC Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=360 Huntington Ave\, CSC:geo:-71.087682620746,42.339110916473
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240408T141500
DTEND;TZID=America/New_York:20240408T143000
DTSTAMP:20260405T065112
CREATED:20240405T203435Z
LAST-MODIFIED:20240405T212740Z
UID:43245-1712585700-1712586600@coe.northeastern.edu
SUMMARY:Soft Matter Days
DESCRIPTION:Soft Matter Days: April 8-17\, will feature invited guest speakers discussing a variety of interdisciplinary topics in soft matter and complex fluids.  These topics sit at the interface of chemical & mechanical engineering\, materials science\, physics\, chemistry\, and biology.  Guest speakers will discuss real-world phenomena found in food\, blood flow\, and granular materials.  Two talks are guest lectures in CHME5179: RSVP required for those not in the class. \nMonday\, April 8\, 2:15pm\, Curry 340\nCapillary Rise and Thin Films Near Edges: New Insights from Self-similarity\nHoward Stone\, Princeton University\nHost: Xiaoyu Tang x.tang@northeastern.edu \nTuesday\, April 9\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\n“Complex Fluids & Soft Matter in Food”\nDave Weitz\, Harvard University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nThursday\, April 11\, 1:30pm\, HS 210\nDynamics of blood flow at the cellular level in health and disease\nMichael Graham\, University of Wisconsin\nHost: Sara Hashmi s.hashmi@northeastern.edu \nFriday\, April 12\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\nNonlinear Rheology of Complex Fluids: Exploring Microstructure\nKate Honda\, Northeastern University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nWednesday\,  April 17\, 1:30pm\, HS 210\nUniversality and scaling in shear thickening suspensions\nBulbul Chakraborty\, Brandeis University\nHost: Sara Hashmi s.hashmi@northeastern.edu
URL:https://coe.northeastern.edu/event/soft-matter-days/2024-04-08/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240408T153000
DTEND;TZID=America/New_York:20240408T170000
DTSTAMP:20260405T065112
CREATED:20240403T182632Z
LAST-MODIFIED:20240403T182632Z
UID:43172-1712590200-1712595600@coe.northeastern.edu
SUMMARY:Jinkun Zhang PhD Dissertation Defense
DESCRIPTION:Announcing:\nPhD Dissertation Defense \nName:\nJinkun Zhang \nTitle:\nLow-latency Forwarding\, Caching and Computation Placement in Data-centric Networks \nDate:\n4/8/2024 \nTime:\n3:30:00 PM \nLocation:\nEXP-459\, \nCommittee Members:\nProf. Edmund Yeh (Advisor)\nProf. Stratis Ioannidis\nProf. Kaushik Chowdhury \nAbstract:\nWith the exponential growth of data- and computation-intensive network applications\, such as real-time augmented reality/virtual reality rendering and large-scale language model training\, traditional cloud computing frameworks exhibit inherent limitations. To address these challenges\, dispersed computing has emerged as a promising next-generation networking paradigm. By enabling geographically distributed nodes with heterogeneous computation capabilities to collaborate\, dispersed computing overcomes the bottlenecks of traditional cloud computing and facilitates in-network computation tasks\, including the training of large models. In data-centric networks\, communication and computation are resolved around data names instead of host addresses. The deployment of network caches\, by enabling data reuse\, offers substantial benefits for data-centric networks. For instance\, consider a scenario where multiple machine learning applications seek to train different models simultaneously. This application could (partially) share data samples and/or computational results. Optimal caching of data and/or results can significantly reduce the overall training cost\, compared to each application independently gathering and transmitting data. \nThis dissertation aims to minimize average user delay in a general cache-enabled computing network. We introduce a low-latency framework that jointly optimizes packet forwarding\, storage deployment\, and computation placement. The proposed framework effectively supports data-intensive and latency-sensitive computation applications in data-centric computing networks with heterogeneous communication\, storage\, and computation capabilities. To minimize user latency in congestible networks\, we model delays caused by link transmissions and CPU computations using traffic-dependent nonlinear functions. We consider a series of related network resource allocation problems in a unified network model. \nWe first investigate the joint forwarding and computation placement problem\, then the joint forwarding and elastic caching problem. Despite the non-convexity of the former subproblem\, we provide a set of sufficient optimality conditions that lead to a distributed algorithm with polynomial-time convergence to the global optimum. For the latter subproblem\, we demonstrate its NP-hardness and non-submodularity\, even after continuous relaxation. We propose a set of conditions that provide a finite bound from the optimum. To the best of our knowledge\, our method represents the first analytical progress in addressing the joint caching and forwarding problem with arbitrary topology and non-linear costs. Upon solving the above two subproblems\, we formally propose the low-latency joint forwarding\, caching\, and computation placement framework. We formulate the mixed-integer NP-hard total cost minimization problem jointly over forwarding\, caching\, and computation offloading variables. Developing on the established result for both subproblems\, we propose two methods\, each with an analytical guarantee. The first method achieves a 1/2 approximation guarantee by exploiting the “submodular + concave” structure of the problem\, leading to an offline distributed algorithm. In real scenarios\, however\, request patterns and network status are not known prior and can be time-varying. To this end\, our second method leads to an online adaptive algorithm exploiting its “convex + geodesic-convex” nature\, with a proven bounded gap from the optimum. \nThe proposed solutions are followed by a few extension problems. Specifically\, we generalize the computation from “single-step” to “service chain” applications. We also generalize the solution to incorporate congestion control by considering an “extended graph”. Furthermore\, several network resource allocation optimization problems related to data-centric networking are introduced\, expanding the scope of this dissertation. For example\, we investigate joint caching and transmission power allocation in wireless heterogeneous networks\, where the total transmission energy is minimized subject to constraints for SINR lower bounds\, cache capacities\, and total power budget at each node. We also study the optimal multi-commodity pricing with finite menu length\, where novel asymptotic bounds on quantization errors are devised.
URL:https://coe.northeastern.edu/event/jinkun-zhang-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240409T090000
DTEND;TZID=America/New_York:20240409T100000
DTSTAMP:20260405T065112
CREATED:20240223T212744Z
LAST-MODIFIED:20240223T212744Z
UID:42522-1712653200-1712656800@coe.northeastern.edu
SUMMARY:Learn about engineering program opportunities in Miami\, FL
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 Miami\, FL 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-miami-fl/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240409T095000
DTEND;TZID=America/New_York:20240409T113000
DTSTAMP:20260405T065112
CREATED:20240405T203435Z
LAST-MODIFIED:20240405T212740Z
UID:43259-1712656200-1712662200@coe.northeastern.edu
SUMMARY:Soft Matter Days
DESCRIPTION:Soft Matter Days: April 8-17\, will feature invited guest speakers discussing a variety of interdisciplinary topics in soft matter and complex fluids.  These topics sit at the interface of chemical & mechanical engineering\, materials science\, physics\, chemistry\, and biology.  Guest speakers will discuss real-world phenomena found in food\, blood flow\, and granular materials.  Two talks are guest lectures in CHME5179: RSVP required for those not in the class. \nMonday\, April 8\, 2:15pm\, Curry 340\nCapillary Rise and Thin Films Near Edges: New Insights from Self-similarity\nHoward Stone\, Princeton University\nHost: Xiaoyu Tang x.tang@northeastern.edu \nTuesday\, April 9\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\n“Complex Fluids & Soft Matter in Food”\nDave Weitz\, Harvard University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nThursday\, April 11\, 1:30pm\, HS 210\nDynamics of blood flow at the cellular level in health and disease\nMichael Graham\, University of Wisconsin\nHost: Sara Hashmi s.hashmi@northeastern.edu \nFriday\, April 12\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\nNonlinear Rheology of Complex Fluids: Exploring Microstructure\nKate Honda\, Northeastern University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nWednesday\,  April 17\, 1:30pm\, HS 210\nUniversality and scaling in shear thickening suspensions\nBulbul Chakraborty\, Brandeis University\nHost: Sara Hashmi s.hashmi@northeastern.edu
URL:https://coe.northeastern.edu/event/soft-matter-days/2024-04-09/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240410T120000
DTEND;TZID=America/New_York:20240410T130000
DTSTAMP:20260405T065112
CREATED:20240328T155531Z
LAST-MODIFIED:20240328T155531Z
UID:43110-1712750400-1712754000@coe.northeastern.edu
SUMMARY:Chemical Engineering Spring Seminar Series: Dr. Jodie Lutkenhaus
DESCRIPTION:Organic Batteries for a More Sustainable Future \nCobalt\, nickel\, and lithium are essential ingredients in today’s lithium-ion batteries (LIBs)\, but their continued use presents economic\, ethical\, and environmental challenges. Society must now begin to consider the implications of a LIB’s full life cycle\, including the carbon footprint\, the economic and environmental costs\, and material access. These challenges motivate the case for degradable or recyclable batteries sourced from earth-abundant materials whose life cycle bears minimal impact on the environment. This presentation considers organic polymer-based batteries\, which have the potential to address many of these issues. Redox-active polymers form the positive and negative electrodes\, storing charge through a reversible redox mechanism. We demonstrate polypeptide radical batteries that degrade on command into amino acids and by-products as a first step toward circular organic batteries. Further\, we show the recycling of redox-active polymer electrodes using a solvent-based approach. Polymer-air batteries are examined as high-capacity alternatives to metal-air batteries. The molecular mechanism for each case is investigated\, revealing pathways forward for improving each polymer’s performance. Taken together\, organic batteries offer the promise of a circular platform free of critical elements. \n\nJodie L. Lutkenhaus is a Professor\, Associated Department Head\, and holder of the Axalta Chair in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. Lutkenhaus received her B.S. in 2002 from The University of Texas at Austin and her Ph.D in 2007 from the Massachusetts Institute of Technology. Current research areas include polyelectrolytes\, redox-active polymers\, energy storage\, and composites. She has received recognitions including World Economic Forum Young Scientist\, Kavli Fellow\, NSF CAREER\, AFOSR Young Investigator\, and the 3M Non-tenured Faculty Award. She is the past-Chair of the AICHE Materials Engineering & Sciences Division. Lutkenhaus is the Deputy Editor of ACS Applied Polymer Materials and a member of the U.S. National Academies Board of Chemical Sciences & Technology.
URL:https://coe.northeastern.edu/event/chemical-engineering-spring-seminar-series-dr-jodie-lutkenhaus/
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:20240410T140000
DTEND;TZID=America/New_York:20240410T150000
DTSTAMP:20260405T065112
CREATED:20240118T180754Z
LAST-MODIFIED:20240118T180754Z
UID:41441-1712757600-1712761200@coe.northeastern.edu
SUMMARY:LinkedIn\, CV\, Resume: A CommLab Workshop Series
DESCRIPTION:Join our empowering LinkedIn\, CV\, and Resume Workshop series any Wednesday from 2 pm to 3 pm ET. This collaborative space offers valuable tips and peer feedback to enhance your online profile and professional presence. This is a community learning initiative\, and together\, we strive to make our profiles better. Join this hybrid workshop series either in person in room 206 Egan or through Zoom.
URL:https://coe.northeastern.edu/event/linkedin-cv-resume-a-commlab-workshop-series-3/2024-04-10/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=206 Egan 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=360 Huntington Ave:geo:-71.0888734,42.3376753
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240410T170000
DTEND;TZID=America/New_York:20240410T180000
DTSTAMP:20260405T065112
CREATED:20240311T133948Z
LAST-MODIFIED:20240311T133948Z
UID:42790-1712768400-1712772000@coe.northeastern.edu
SUMMARY:Poster Design and Presentation: A CommLab Workshop Series
DESCRIPTION:The CommLab will host a workshop series for poster design and presentation to focus on crafting the best visual communication of your research and telling your research story! With the upcoming RISE Expo\, we will discuss techniques and implement communication strategies to successfully showcase your work. No matter where you are in the process\, whether it is just in the idea phase or you are trying to polish your final poster\, we are happy to help you.  Join us any Wednesday\, between February 28th to April 10 from 5:00-6:00 PM on Zoom. See you there!
URL:https://coe.northeastern.edu/event/poster-design-and-presentation-a-commlab-workshop-series/2024-04-10/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T090000
DTEND;TZID=America/New_York:20240411T100000
DTSTAMP:20260405T065112
CREATED:20240408T134711Z
LAST-MODIFIED:20240410T141025Z
UID:43283-1712826000-1712829600@coe.northeastern.edu
SUMMARY:Giving Day Donuts with the Dean
DESCRIPTION:All faculty\, staff\, and students are invited to have donuts with Dean Gregory Abowd and kick off an exciting day of activities and college challenges. We need your support — a gift to the College of Engineering is an investment in our students\, faculty\, and programs! Make your gift today. \nLocation: outside of Snell Engineering\, by the entryway facing Egan. If raining\, inside SN Lobby
URL:https://coe.northeastern.edu/event/giving-day-donuts-with-the-dean/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T120000
DTEND;TZID=America/New_York:20240411T133000
DTSTAMP:20260405T065112
CREATED:20240410T210113Z
LAST-MODIFIED:20240410T210113Z
UID:43325-1712836800-1712842200@coe.northeastern.edu
SUMMARY:Gerald LaMountain PhD Proposal Review
DESCRIPTION:Name:\nGerald LaMountain \nTitle:\nOn the Performance of Classical Estimation Under Adverse\nConditions \nDate:\n4/11/2024 \nTime:\n12:00:00 PM \nLocation:\nEXP 459 \nCommittee Members:\nProf. Pau Closas (Advisor)\nProf. Deniz Erdogmus\nProf. Aanjhan Ranganathan \nAbstract:\nSystem designers across all disciplines of technology face the need to develop machines capable of independently processing and analyzing data and\, in many cases\, subsequently predicting future data. Over the past century\, numerous approaches have been developed to perform this task\, including those that fall under the umbrella of “classical statistics;” that is\, those that employ probabilistic analyses to isolate relationships between variables and\, in particular\, “statistical estimation” wherein those variables are used to make inferences about real-world quantities. To fully leverage the bevy of established estimation algorithms\, it is necessary to be able to evaluate the performance of a given estimator and\, where possible\, make changes to the methodology to improve its performance according to pertinent metrics. In the presence of ground-truth information\, the accuracy of estimations can be evaluated a posteriori for a specific set of data. But what of future data which may not be associated with the same set of ground-truth information? In these cases\, we require statistical generalizations about estimator behavior based on models of observed reality. In reality\, these models are rarely fully representative of the reality of the observed and latent variables of interest. In such cases\, there exists a “model misspecification\,” and estimators which are designed based on such an imprecise model will produce results which differ from both properly specified estimators and the truth. \nThe overall objective of this thesis is to evaluate and expand upon state-of-the-art approaches to estimation and estimator analysis under various types of misspecification\, including modeling errors that naturally occur as a result of the sensory environment\, for example\, unknown or variable observation noise. We contribute a method of Bayesian covariance estimation which\, when embedded within the Kalman filter architecture\, may be used to adapt to real-time changes in sensor performance while maintaining the recursive structure that allows the Kalman filter to be implemented in so many different applications. Furthermore\, we investigated the efficacy of signal subspace algorithms (e.g. MUSIC) for performing multi-antenna radio direction finding\, again in the presence of modelling errors. Although these algorithms are considered suboptimal (in the sense of the minimum mean squared error—MMSE) in finite time\, their computational efficiency motivates their use in many different applications. Our analysis shows that under certain classes of model misspecification\, the candidate algorithm for misspecified multiple signal classification (MMUSIC) performs asymptotically as well as the “gold standard” maximum likelihood estimator (MMLE) under the same misspecification. The final objective of this thesis is to combine the estimation bounds analysis we have applied to static estimation and extend it to dynamical systems. Although there exist established methods for evaluating and bounding the performance of estimators on misspecified models and dynamic models\, there has been limited progress in establishing a standard for performing misspecified estimator analysis under dynamic conditions. Although this work is still ongoing\, preliminary results are encouraging\, suggesting that there are likely multiple approaches to this bounded analysis based around different objectives. Further results will be included in the final version of our work.
URL:https://coe.northeastern.edu/event/gerald-lamountain-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T133000
DTEND;TZID=America/New_York:20240411T143000
DTSTAMP:20260405T065112
CREATED:20240405T203435Z
LAST-MODIFIED:20240405T212740Z
UID:43260-1712842200-1712845800@coe.northeastern.edu
SUMMARY:Soft Matter Days
DESCRIPTION:Soft Matter Days: April 8-17\, will feature invited guest speakers discussing a variety of interdisciplinary topics in soft matter and complex fluids.  These topics sit at the interface of chemical & mechanical engineering\, materials science\, physics\, chemistry\, and biology.  Guest speakers will discuss real-world phenomena found in food\, blood flow\, and granular materials.  Two talks are guest lectures in CHME5179: RSVP required for those not in the class. \nMonday\, April 8\, 2:15pm\, Curry 340\nCapillary Rise and Thin Films Near Edges: New Insights from Self-similarity\nHoward Stone\, Princeton University\nHost: Xiaoyu Tang x.tang@northeastern.edu \nTuesday\, April 9\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\n“Complex Fluids & Soft Matter in Food”\nDave Weitz\, Harvard University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nThursday\, April 11\, 1:30pm\, HS 210\nDynamics of blood flow at the cellular level in health and disease\nMichael Graham\, University of Wisconsin\nHost: Sara Hashmi s.hashmi@northeastern.edu \nFriday\, April 12\, 9:50am\, Zoom (Guest Lecture for CHME 5179)\nNonlinear Rheology of Complex Fluids: Exploring Microstructure\nKate Honda\, Northeastern University\nRSVP: Sara Hashmi s.hashmi@northeastern.edu \nWednesday\,  April 17\, 1:30pm\, HS 210\nUniversality and scaling in shear thickening suspensions\nBulbul Chakraborty\, Brandeis University\nHost: Sara Hashmi s.hashmi@northeastern.edu
URL:https://coe.northeastern.edu/event/soft-matter-days/2024-04-11/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T140000
DTEND;TZID=America/New_York:20240411T150000
DTSTAMP:20260405T065112
CREATED:20240118T204753Z
LAST-MODIFIED:20240321T134631Z
UID:41488-1712844000-1712847600@coe.northeastern.edu
SUMMARY:Mock Interview: A CommLab Workshop Series
DESCRIPTION:Join the CommLab every Thursday from 2-3pm ET\, we’ll delve into the intricacies of interviews\, unveiling effective tricks and preparation strategies for any interview scenario. Engage in an interactive setting as we dissect the overall interview experience\, discuss common interview scenarios\, and share insights on what to do during critical moments. Join this hybrid workshop series either in person in room 206 Egan or through Zoom.
URL:https://coe.northeastern.edu/event/mock-interview-a-commlab-workshop-series/2024-04-11/
LOCATION:206 Egan\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3376753;-71.0888734
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=206 Egan 360 Huntington Ave Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=360 Huntington Ave:geo:-71.0888734,42.3376753
END:VEVENT
END:VCALENDAR