Northeastern University College of Engineering

USC Fall 2022 Graduate Schools Fair - Los Angeles, CA
2022-10-20 10:00 - 14:00 (America/Montserrat)
Join the Graduate Admissions team for an IN-PERSON recruiting event in Los Angeles, California! The event will take place at USC Trousdale Pkwy Los Angeles , California on October 20th between 10:00 AM to 2:00 PM PST. Registration and event details may be found at the website below. We look forward to seeing you there!

Neset Unver Akmandor's PhD Proposal Review
2022-10-20 12:00 - 13:00 (America/New_York)
“Improving Computational Efficiency of Motion Planning Algorithms for Mobile and Time-Dependent Robotic Tasks in Dynamic Environments”
Abstract:
Robots will become a part of our lives at home as personal assistants. Although their current functionality is highly restricted to specific tasks and environments, their practicality encourages robotics engineers for further advancement. Especially, mobile robots with manipulation capabilities have a huge potential to support humans in physically demanding workplaces, such as warehouses and hospitals. Considering the complexity of the human level tasks and the dynamic settings, the state-of-the-art robot motion planning methods need to be improved in terms of their computational efficiency. To contribute on closing the gap, this proposal presents three novelties whose applications focus on mobile robots in dynamic environments. First, we introduce a reactive navigation framework in 3D workspaces. The proposed approach does not rely on the global map information and achieves fast navigation by employing motion primitives and their heuristic evaluations on the-fly. Second, we present a Deep Reinforcement Learning based navigation approach in which we define the occupancy observations as heuristic evaluations of motion primitives, rather than using raw sensor data. It utilizes occupancy observations in different data structures to analyze their effects on both training process and navigation performance. We train and test our methodology on two different robots within challenging physics-based simulation environments including static and dynamic obstacles. Finally, we propose a computationally efficient framework for trajectory planning for robots with high degrees-of freedom while adapting its system model, constraints and time-dependent target state using the latest information from the dynamic environment.

Committee:
Dr. Taskin Padir (Advisor)Dr. Pau ClosasDr. Michael EverettDr. Erdal Kayacan

University of California, Santa Barbara Graduate & Professional School Day
2022-10-20 13:00 - 17:00 (America/Los_Angeles)
Learn about Northeastern University’s graduate engineering programs at UC Santa Barbara. One of our admissions representatives will be happy to answer your questions!

PlusOne Information Session
2022-10-20 18:00 - 19:00 (America/New_York)
Learn about the PlusOne Accelerated Master’s Degree Program
A master’s degree can provide you with an additional level of expertise in an area aligned with your career goals. As a currently enrolled Bachelor of Science (BS) student in the College of Engineering at Northeastern, you have the opportunity to earn a Master of Science degree (MS) in an accelerated time period with the PlusOne program. Once accepted into the program in an approved PlusOne pathway, which is a BS and MS PlusOne combination, you can earn an MS degree with, in most cases, just one extra year of study beyond your undergraduate degree program.
In this virtual information session, College of Engineering undergraduate and graduate academic advisors will provide an overview of the PlusOne program to give you the knowledge and next steps to take advantage of the program if you choose.
WHAT YOU WILL LEARN:
• What is PlusOne
• Benefits of the program
• Eligibility
• Co-op considerations
• Financial considerations
• Selecting your pathway
• Academic advising resources
• Timeline to apply
• The application process
• Course registration
• Transitioning to graduate school
Learn more and apply: coe.northeastern.edu/plusone

GSE Wonder Week: Learn about MSIS, MSIS-Bridge, MSDAMG, & MSSES
2022-10-21 09:00 - 10:00 (America/New_York)
Join this webinar to learn about MS Information Systems, MS Information Systems Bridge, MS Data Architecture & Management, and MS Software Engineering Systems

GSE Wonder Week: Learn about Mechanical + Industrial Engineering Graduate Programs
2022-10-21 10:00 - 11:00 (America/New_York)
Join this webinar to learn about the Mechanical + Industrial Engineering Graduate Programs at Northeastern University

COE FacDev Friday: Getting Your News Out - Working with COE Marketing and Communications
2022-10-21 13:00 - 14:00 (America/New_York)

Yixuan He's PhD Proposal Review
2022-10-24 11:00 - 12:00 (America/New_York)
Committee:
Prof. Yong-Bin Kim. Advisor
Prof. Marvin Onabajo
Prof. Lombardi Fabrizio

Abstract:
In order to match the needs of powerful neural networks and meet the hard constraints from hardware, binary neural networks are treated as hardware-friendly deep learning algorithms due to the fact that it can achieve similar inference accuracy with fewer computing resources comparing to traditional convolutional neural networks. As for its VLSI implementations, the computing-in-memory (CIM) technology has been proved to solve the memory-wall bottleneck problem shown in traditional von Neumann machine and can be a perfect choice to implement neural networks with binary data. Therefore, this work proposes a novel time-domain computing-in-memory core that implements XNOR-and-accumulate of binary neural networks with all-digital elements. This new technique uses 8T-SRAM cells to perform XNOR operations inside memory array and accumulates the related XNOR output values in time-domain with specialized racing structures and delay lines. The circuit is built and simulated in Cadence using Samsung 65nm CMOS technology with 1V power supply. The results show correct functionality, 2730 GOPS throughput and 431 TOPS/W power efficiency. With further exploration, the time-domain computation can be a new candidate in the field of in-memory-computing for deep learning applications since it has its own superiorities in terms of throughput, power efficiency in comparison to other mixed-signal or traditional digital methods.

Webinar: Learn about Northeastern's Co-op Program!
2022-10-25 08:00 - 09:00 (America/New_York)
Come learn more about Northeastern’s Co-op Program for graduate engineering students! A member of our admissions team, and the Assistant Dean & Senior Co-op Coordinator, Lorraine Mountain will present and answer questions.

BioE Seminar Series Presents Erica Pratt
2022-10-26 12:00 - 13:00 (America/New_York)
Department of Bioengineering Seminar Series presents:
Erica Pratt, Ph.D
Assistant Professor, Department of Biomedical Engineering, Boston University, Boston MA
“Liquid biopsy approaches in pancreatic cancer”
Wednesday, October 26th, 2022
12:00 pm – 1:00 pm EST
105 Shillman Hall
ABSTRACT:
Only 25% of pancreatic ductal adenocarcinoma (PDA) patients with localized disease survive five years after a ‘curative’ resection. It is hypothesized that PDA undergoes dissemination at the earliest stages of tumorigenesis, driving the formation of micrometastases that go undetected using conventional screening methods. The development of high-specificity, high-sensitivity biomarkers is critical to improving patient outcomes. Growing evidence suggests circulating tumor DNA (ctDNA) is an ideal candidate to fill this gap. ctDNA has been successfully used as a noninvasive prognostic biomarker in multiple solid tumor types. However, pancreatic cancer remains intractable due to its intrinsically low molecular signal and fast timeline to progression. To address this need, we have developed a digital PCR (dPCR)-based platform for rapid, flexible, and multiplexed ctDNA detection. Our approach for sensitive detection of low abundance ctDNA is a promising tool for modular and scalable mutation profiling.
BIO:
Erica D. Pratt is an assistant professor of Biomedical Engineering at Boston University. Her lab works at the interface of engineering, chemical biology and oncology to develop assays for cancer diagnosis and monitoring. She earned her B.S. in Mechanical Engineering and Biomedical Engineering from Carnegie Mellon University. Erica went on to earn her Ph.D. in Biomedical Engineering at Cornell University working with Brian J. Kirby. There she co-designed the Geometrically Enhanced Differential Immunocapture (GEDI) platform for high-efficiency and high-purity microfluidic isolation of circulating tumor cells from whole blood samples. Erica then completed multi-disciplinary postdocs with Andrew D. Rhim and Laurie L. Parker developing assays for non-invasive omic characterization of solid cancers.

Modular and Composite Approaches to Engineering Challenging Tissues with Polysaccharide Materials
2022-10-26 12:00 - 13:00 (America/New_York) | 236 Richards, 360 Huntington Ave, Boston, MA, 02115, United States
ChE Seminar Series Presents:
Howard W.T. Matthew, PhD
Professor, Chemical Engineering, Wayne State University
Abstract:
Polysaccharides have long been recognized as polymeric materials with an array of properties that have made them indispensable for applications ranging from adhesives to property-enhancing nanomaterials. As a result, they have found wide acceptance as food and drug additives. Over the past thirty years, a growing body of work has served to raise their profile as effectors and modulators of receptor-based phenomena including immune recognition as well as cell-matrix, cell-pathogen, and cell-growth factor interactions. However, these materials remained underutilized as components of implantable systems. Within the last decade, the explosion of research in tissue engineering and regenerative medicine has increased demand for biologically active materials, and polysaccharides are receiving greater attention for their ability to facilitate tissue assembly and organization in vitro and in vivo. While many polysaccharides possess potentially useful biological activities, their mode of application has mainly been in bulk hydrogel form. The Matthew group has been working with polyelectrolyte ionic complexes formed between oppositely charged polysaccharides. These ionic complex membranes can be rendered as hollow microcapsules of controllable size. This presentation will describe our ongoing studies focused on deploying these capsules as a versatile tool for generating tissue organoids and as a platform for assembling vascularized tissues with a range of physical and biological properties.
Bio:
Howard Matthew is a Professor of Chemical Engineering and Materials Science at Wayne State University (WSU) in Detroit, Michigan. He received a B.Sc. degree in Chemical Engineering (1984) from the University of the West Indies, Trinidad. After two years in the food processing industry, he joined Wayne State University for graduate studies, receiving an M.S. degree in 1988 and a Ph.D. in 1992. He conducted two years of postdoctoral research at Harvard Medical School and the Massachusetts General Hospital. He then joined the WSU faculty as an Assistant Professor in 1994. He is a recipient of the National Science Foundation’s Early Faculty CAREER Award (1996), and was elected as a Fellow of the American Institute of Medical and Biological Engineering (AIMBE, 2012). His research spans the fields of biomaterials and tissue engineering, focusing on the use of polysaccharide materials in tissue design and assembly. His work has two broad themes: modulating the mechanics and biological activity of polysaccharide materials; and developing methods to apply these materials in cell and tissue-based therapies. Target applications include: heart valves for pediatric applications, designing transplantable liver tissue, and regeneration of musculoskeletal structures after surgical or traumatic loss. To date, Prof. Matthew has been research supervisor for over 40 graduate students 55 undergraduates and 43 high school students.

SWE Networking Night
2022-10-26 19:30 - 21:00 (America/New_York) | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Join the Society for Women Engineers (SWE) for our annual Networking Night!
When: Wednesday, October 26th at 7:30pm
Where: Curry Ballroom (second floor)
Who: Undergraduate womxn engineers and companies representing all engineering majors
Why: Become more comfortable networking and build relationships with industry professionals!
This is a unique opportunity for undergraduate womxn engineers to chat about professional development with engineers and recruiters from 20+ companies. Learn more about job opportunities, interview tips, resume help, career trajectory, etc. in a low-pressure environment!
Check out our event on Engage!

SACNAS National Diversity in STEM Conference - San Juan, PR
2022-10-27 00:00 - 2022-10-29 00:00 (America/New_York)
Join the Graduate Admissions team for an IN-PERSON recruiting event in San Juan, Puerto Rico! The event will take place at Governor Pedro Rosello San Juan Convention Center, on October 27th to October 29th. Registration and event details may be found at the website below. We look forward to seeing you there!

California State University, Fullerton Graduate School Expo
2022-10-27 14:00 - 16:00 (America/New_York)
Emily DeRosa, Recruiting Specialist from the Graduate School of Engineering will be present at this on-ground event at California State University Fullerton. Visit our table to learn more about our Graduate Engineering programs!

Dean's Distinguished Lecture Series: Finding Academic, Professional, and Personal Success
2022-10-27 15:00 - 16:30 (America/New_York) | 108 SN
DEAN’S DISTINGUISHED LECTURE SERIES
Finding Academic, Professional, and Personal Success
Ravi Bellamkonda
Provost and Executive Vice President for Academic Affairs, Emory University
Dr. Bellamkonda has had a rapid ascent in academia. But as most of us would agree, professional success means little without being connected to personal meaning. In this talk, Dr. Bellamkonda will talk about his personal journey and what lessons he would share with engineers at every career stage, from first-year undergrads to seasoned academics.
Reception to follow.
Thursday, October 27
3:00 – 4:30 P.M.
108 Snell Engineering

The Dean’s Distinguished Lecture Series brings inspirational guest speakers to Northeastern.

Ravi V. Bellamkonda serves as Emory’s provost and executive vice president for academic affairs. Prior to becoming provost at Emory, Bellamkonda served as dean of the Pratt School of Engineering at Duke University. Previously, he was Wallace H. Coulter professor and chair of the Department of Biomedical Engineering at Georgia Institute of Technology and Emory University. From 2014 to 2016, Bellamkonda served as president of the American Institute for Biological and Medical Engineering.
A trained bioengineer and neuroscientist, Bellamkonda holds an undergraduate degree in biomedical engineering. His graduate training at Brown University was in biomaterials and medical science, and his postdoctoral training at MIT focused on the molecular mechanisms of axon guidance and neural development.
Bellamkonda is committed to fostering transformative research and pedagogical innovation as well as programs that create an entrepreneurial mindset among faculty and students. His current research explores the interplay of biomaterials and the nervous system for neural interfaces, nerve repair, and brain tumor therapy.

Dean's Speaker: What Society Must Require from AI
2022-10-28 11:30 - 12:30 (America/New_York) | Fenway Center, 77 St. Stephen Street, Boston, MA, 02115, United States
WHAT SOCIETY MUST REQUIRE FROM AI
A lecture with Dr. Ronald M. Baecker, Emeritus Professor of Computer Science and Bell Chair in Human-Computer Interaction at the University of Toronto
Dr. Baecker will discuss the dangers of premature use of AI, and what society must require of algorithms affecting human welfare, health, life, and death. The talk will be of interest to researchers in prioritizing problems for AI guided by human-computer interaction, as well as policy makers and citizens considering when and how AI technology should be deployed.
Please RSVP to attend
Lunch will be served following the lecture.
Ronald M. Baecker received bachelor’s, master’s, and doctoral degrees from MIT. He researched interactive computing at MIT’s Lincoln Laboratory, the National Institutes of Health, Xerox PARC, Apple Computer, and the MIT Media Lab. At the University of Toronto, he founded its Knowledge Media Design Institute and its Technologies for Aging Gracefully Lab, and co-founded its Dynamic Graphics Project. He has started five software companies, leading three as founding CEO, and has taught principles of software entrepreneurship for over three decades.
Fenway Center or via Zoom
View Flyer

Systems Thinking, Community Engagement, and Collaborative Change Within and Beyond Engineering Education
2022-10-28 12:00 - 13:00 (America/New_York)
Friday, October 28th at 12pm (VIRTUAL)

Please Register:
https://bit.ly/3BPSSOu
All attendees receive a FREE BOOK!
Abstract: This seminar explores intersections between systems thinking, community engagement, and collaborative change within and beyond engineering education by discussing three big questions:
What skills do we (and our students) need to address some of the complex, intractable, systemic challenges that we care about? How would we know what learning looks like?
What are some of the central values, imperatives, or habits of mind that comprise community engagement? Where do we fit in to address issues we care about?
What factors influence our capacity to collaboratively enact change?
The seminar will be grounded in brief findings from research projects engaged with these core questions and will invite discussion about how we can prioritize these activities within engineering education and the opportunities for broader impacts.
Bio: Dr. Jake Grohs is an Associate Professor in the Department of Engineering Education and an affiliate faculty member to both Learning Science and Technologies and Biomedical Engineering and Mechanics. Grohs currently serves as PI of two and co-PI of two NSF-funded education focused grants which involve partnering with different stakeholder groups on continuous improvement or collaborative change (e.g., K12 teachers and administrators, university engineering faculty). His primary research interests focus on systems thinking, including how individuals reason through complex ill-structured problems, how educational environments develop systems thinking skills, and how collaborative groups might apply systems thinking to enact positive change.

Guillem Reus Muns' PhD Proposal Review
2022-10-28 13:00 - 14:00 (America/New_York)
Location: ISEC 332
“AI for communications and sensing in RF environments”
Abstract:
The recent growth of Internet of Things (IoT), as well as other new revolutionary applications utilizing wireless spectrum are leading the way towards realization of next generation wireless systems that jointly utilize communications and sensing. However, such systems offer many degrees of freedom, and optimizing them for a specific task is difficult to accomplish with deterministic and classical approaches. For this reason, data-driven and AI-based methods have been pursued actively by the research community, as they are able to find solutions that often come close to or exceed the performance of the deterministic counterparts with a fractional execution complexity. This thesis presents, through real systems and with experimental validation, our progressive efforts in three broad areas, where AI enables the operation of aerial and terrestrial systems that combine sensing and communications. This dissertation explores the following key use cases with distinct contributions made in each:
i) Sensing-aided communications for air and ground systems. First, we present a UAV communication method that defines constellation points in space that map to transmitter frequency bands and are detected at the Base Station using millimeter wave sensors. Second, we explore alternative vehicle-to-infrastructure mmWave beamforming methods, leveraging a) vehicle position and velocity estimation using in-band standard compliant 802.11ad radar and b) camera images and GPS location information.
ii) Signal classification using communication signals, where we propose a) a UAV classification method using uniquely UAV-transmitted signals and b) an RF fingerprinting technique that improves class separation by combining triplet loss with regular classification techniques.
iii) ‘AirFC’, an over-the-air computation method that implements fully connected neural networks inference leveraging multi-antenna systems.
Finally, the proposed work will address challenges in the CBRS band, where a tiered structure is implemented to access the spectrum. Hence, continuous sensing is needed to make sure that radar (tier 1) is not interfered by cellular systems (tier 2). Here, we propose reusing the already existing cellular infrastructure to act as a radar detector, which enhances their functionality to go beyond that of regular wireless communications.
Committee:
Prof. Kaushik Chowdhury (Advisor)
Prof. Hanumant Singh
Prof. Stratis Ioannidis

Introducing the MS in Computational Medicine
2022-10-31 10:00 - 11:00 (America/New_York)
Learn about the College of Engineering’s newest program offering at Northeastern’s Roux Institute, the MS in Computational Medicine on Monday, October 31 at 10:00am. Registration is required.

KRI Research Networking
2022-10-31 15:00 - 17:00 (America/New_York) | 440 Egan, 360 Huntington Ave, Boston, MA, 02115, United States
Please join us for all or part of a poster session/reception at which the NU Kostas Research Institute for Homeland Security research teams will present KRI research capabilities (facilities and staff expertise) in:

Geospatial data analysis
RF materials & devices
Unmanned autonomous systems
Additive manufacturing
Formulation chemistry
And beyond (e.g. meeting space/support, venture-stage facilities/equipment)

Open to the entire university.

SHPE 2022 NATIONAL CONVENTION
2022-11-02 - 2022-11-06
Join Northeastern University in Charlotte, NC for the annual SHPE (Society of Hispanic Professional Engineers) National Convention!
Northeastern University and the Graduate School of Engineering will be in attendance at the Career Fair & Graduate School Expo from 10am-4pm on Friday and Saturday. We will also be hosting a Diversity and Inclusion Hospitality Suite on Thursday night from 7:30-9:30pm.

Engineered cellular models to explore human disease heterogeneity
2022-11-02 12:00 - 13:00 (America/New_York) | 236 Richards, 360 Huntington Ave, Boston, MA, 02115, United States
ChE Seminar Series Presents:
Alison McGuigan, PhD
Professor, Chemical Engineering & Applied Chemistry, University of Toronto
Abstract:
Ex vivo culture models provide powerful tools to interrogate the role of tumour heterogeneity in human cancers. Patient-derived organoids (PDOs) are emerging as powerful models to capture the genetic heterogeneity of human tumors. However, extrinsic factors present in the tumor microenvironment (TME) of a tumour, such as the presence of stromal cells and gradients of small molecules such as oxygen, also affect cancer phenotype and response to therapy. This talk will describe tissue-engineered platforms we have developed 1) to enable controlled assembly and disassembly of organoid structures to study the impact of both genetic and microenvironmental heterogeneity on tumor cell behavior and 2) to explore tumour microenvironment remodelling, heterogeneity in response to therapy, and potential to re-grow after therapy.
Bio:
Dr. Alison McGuigan is a Professor in Chemical Engineering and Applied Chemistry and the Institute for Biomedical Engineering at University of Toronto. She obtained her undergraduate degree from University of Oxford, her PhD from University of Toronto working, and completed Post Doctoral Fellowships at Harvard University and Stanford School of Medicine. Dr. McGuigan research group is focused on the engineering of tissue models to explore mechanisms of disease and regeneration. Dr. McGuigan has established strategies to generate multi-component tissue systems with specified organization. Furthermore, she has pioneered the design of tissue platforms for smart data acquisition, with a focus on stratifying heterogeneous bulk data by cell population, by spatial location, or by time. In recognition of Dr. McGuigan’s work she has received numerous awards including the 2013 TERMIS-AM Young Investigator Award, and the Canadian Society for Chemical Engineering Hatch Innovation Award. In 2018 was elected to the Royal Society of Canada-College of New Scholars, Artists and Scientists and in 2022 she was elected a Fellow of TERM by the Tissue Engineering and Regenerative Medicine International Society. She serves on the executive leadership team of CFREF Medicine by Design program and on the Centre for Commercialization of Regenerative Medicine (CCRM) incubation and outreach committee.

Yuexi Zhang's PhD Proposal Review
2022-11-02 12:00 - 13:00 (America/New_York)
“Human Body and Activity Analysis”
Abstract:
Human-related applications such as person detection, human pose estimations and human activity recognition, that always draw a lot of attentions in computer vision community. In this proposal, we discuss several related topics that we are interested in, and demonstrate how we improve the existing methods. The first problem we consider is video-based human pose estimation. For most general approaches, researchers focus on collecting human poses from each frame independently and then associate them based on matching or tracking methods. However, such the pipeline usually relies on complex computations and also consumes running time. To overcome such shortages, we propose a light weighted network with the unsupervised training strategy, that aims to reduce running time but remaining the performance. The next problem we explore is about cross-view action recognition (CVAR). The goal of CVAR is to recognize a human action when observed from a previously unseen viewpoint. This is important for some applications such as surveillance systems where is not practical or feasible to collect large amounts of training data when adding a new camera. In this case, it requires methods that are able to generate reliable view-invariant information trained with given viewpoints and recognize the action from an unseen viewpoint. In general, most approaches rely on 3D data, but using 2D data is still under-discovered. Besides, the performance of those approaches using only 2D data is far worse than 3D approaches. Therefore, we propose a simple yet efficient CVAR framework that takes 2D data as input and close the performance gap between 3D and 2D input. The last problem we investigate is online action detection and we are interested in detecting action start at current stage. Online action start detection problem is to detect an action startpoint as soon as it occurs with its action category in untrimmed, streaming videos, and it has potential applications such as early alert generation in surveillance systems. The typical approaches usually heavily rely on frame-level annotations and also they are limited to pre-defined action categories. Therefore, we propose a novel yet simple design, 3D MLP-mxier based architecture that aims to detect the taxonomy-free action start without using frame-level annotations.

Committee:
Dr. Octavia Camps(Advisor)
Dr. Mario Sznaier
Dr. Sarah Ostadabbas

Kai Huang's PhD Dissertation Defense
2022-11-02 14:00 - 15:00 (America/New_York)
“Partitioning Data Across Multiple, Network Connected FPGAs with High Bandwidth Memory to Accelerate Non-streaming Applications”
Abstract:
Field Programmable Gate Arrays (FPGAs) are increasingly used in cloud computing to increase the run time of various applications. Flexibility, efficiency and lower power enable FPGAs to be important components in modern data centers. Applications such as Secure Function Evaluation (SFE), graph processing, and machine learning are increasingly mapped to FPGA-based adaptable cloud computing platforms. However, due to resource limitations, it is difficult to map applications to only one FPGA. Applications with a streaming data processing pattern can be mapped to a multiple-FPGA platform where the FPGAs are connected in a 1-D or ring topology, thus communications overhead can be pipelined with computations. The communication, merely passing data from boards to boards, will not significantly affect the system performance if the bandwidth is sufficient. In a more general processing pattern involving non-streaming applications, each FPGA is responsible for only a portion of the computation and the FPGAs must keep exchanging data during the run time of the application. The communication cost can be the bottleneck of such a system. The challenge is how to map and parallelize these applications to a multi-FPGA cloud computing platform in such a way that communication is minimized and speedup is maximized.
In this research, we build a framework to map garbled circuit applications, an implementation of SFE, to a cloud computing platform that has FPGA cards attached to computing nodes. The FPGAs on the node are able to communicate directly through the network. The framework consists of two parts: hardware design and software preprocessing. The hardware design integrates with the Xilinx UDP network stack enabling the capability to exchange data through the network and thus bypassing the processor and its software stack. The framework also takes advantage of High Bandwidth Memory (HBM) for high off-chip memory throughput. The levels of memory hierarchy available on the FPGA are used for caching both local data and incoming and outgoing network data. Preprocessing will generate the reordered batches of each layer needed for processing, efficient memory allocation and final memory layout. We also applied an effective partitioning algorithm to schedule executions to different FPGAs to minimize the communication between FPGAs. By generating different size of problems from the EMP-toolkit, we can demonstrate that this hardware-software co-design framework achieves nearly optimal two times speedup on a two-FPGA setup compared to a one-FPGA implementation. We explore extremely large examples that cannot be mapped to one-FPGA, proving that it is achievable to map large examples of billions of operations to this distributed heterogeneous system.
Committee:
Prof. Miriam Leeser(advisor)
Prof. Stratis Ioannidis(co-advisor)
Prof. Mieczyslaw Kokar

Lin Deng's PhD Proposal Review
2022-11-03 13:30 - 14:30 (America/New_York)
“On-chip and multiplexed metasurfaces for light manipulation”
Abstract:
Metasurfaces, which consist of two-dimensional subwavelength nanostructures that can locally manipulate the proprieties of light including amplitude, phase, and polarization, provide an unprecedented means to control optical waves in a prescribed manner. Different functionalities, such as structured light, holograms, and flat lenses, have been realized by metasurfaces. It is a pressing need to develop on-chip and multiplexed metasurfaces to further advance the practical applications of metasurfaces.
In this proposal review, I will discuss two metasurfaces designed with compact size and the ability to multiplex various information channels. The first one can realize mode conversion and wavefront shaping by integrating a C-shape metallic metasurface on top of a planar waveguide. By controlling the orientation of each C-shape nanoantenna, we can achieve mode conversion and focusing effect for the cross-polarized electric fields inside the waveguide. We demonstrated the design and simulation results of 16 scenarios of wideband transverse magnetic (TM) to transverse electric (TE) modes conversion with mode purity up to 98% as well as on-chip lenses at the wavelength of 1550 nm. The second device is to realize the precise control of the amplitude and phase at multiple channels in response to different incident angles and output polarization states by a single planar metasurface. With the help of the genetic algorithm, we designed and demonstrated all-dielectric metasurfaces composed of silicon nano-blocks that can produce multiple complex structured light beams when taking the angle of incidence and the polarization states into consideration. Our research is expected to substantially benefit the development of mode division multiplexing (MDM) as well as polarization-division multiplexing (PDM).
Committee:
Prof. Yongmin Liu (Advisor)

IISE Six Sigma Green Belt Certification
2022-11-04 - 2022-11-06
Six Sigma Green Belt Certification 6σ Six Sigma Green Belt Certification
Register to Learn methods and tools for increasing quality by reducing variability – applicable to all fields! All years and majors are welcome!
Make your resume stand out for co-ops and job searches.
Taught by Dr. Brian J Galli
Friday 11/4 from 4 – 8pm
Saturday and Sunday 11/6-7 from 9am – 5pm
(must attend all sessions)

Rising Tides Conference
2022-11-04 08:30 - 13:30 (America/New_York) | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
This conference explores issues of racial and social justice in the context of environmental action to address climate change.
The event will be held Friday, November 4th from 8:30am-1:30pm in the Curry Ballroom on the second floor of Curry Student center, but please feel free to come in and out of the event at your convenience.
This conference is linked to Northeastern’s Myra Kraft Open Classroom, and to an environmental justice map exhibition at the Leventhal Map & Education Center at the Boston Public Library. Engaging with civic community action toward emerging environmental policies brings forward issues of justice and social equality. This conference will address how citizens engage with environmental governance and how policymakers engage with equitable green development.
Our Noon keynote speaker is Senator Edward Markey, whose new Federal climate legislation includes $60 billion out of $370 billion to address issues of climate justice brought on by decades of racial, economic, and social discrimination. Morning presentations and discussions are linked to policy actions and community engagement by public officials, faculty, community activists, planners, and advocates addressing racial and social justice to address climate change.
RSVP

NanoSI Workshop
2022-11-04 13:00 - 16:00 (America/New_York)
The NSF sponsored Nano Systems Innovation (NanoSI) workshop will conduct a deep dive into infrastructure requirements to enable a unique national infrastructure for piezoelectric and hetero-integrated nano systems. The virtual workshop will bring together researchers, government, industry and foundry partners to identify the emerging needs for adaptable infrastructure that can address national research priorities in advanced hetero integration to post-CMOS and more than Moore devices. The workshop will concentrate on planning for infrastructure that can close the gap between the local research and prototyping capabilities of the universities with advanced semiconductor manufacturing activities with the ultimate goal of reducing the time for innovation and transition of the new foundational nano-system technologies that are going to be the at root of our nation’s economic strength, national security and technological standing in the years to come. The workshop will explore the community’s preferred pathways for accessing and engagement with the future infrastructure, management plans, and ideas to strengthen the community by extending access to underrepresented groups. Furthermore, the workshop will identify strategies to leverage the national facility to educate an experienced future workforce for semiconductor and advanced nanomanufacturing industries in the United States.
The NanoSI virtual workshop will include pre-recorded 8-minute presentations given by multiple stakeholders from academia, industry and government highlighting technological areas of interest and providing multiple perspectives on the value proposition of a national infrastructure for piezoelectric and hetero-integrated nano systems. These short presentations will be made available to the workshop attendees through the password-protected event web page by Friday October 28th, 2022. Taking inputs from this asynchronous session of the workshop, the organizers will prepare a report and present it to the attendees during a three-hours synchronous virtual session that will take place on Friday November 4th, 2022 at 1 – 4 pm EST. The report presentation will be followed by breakout discussion sessions focused on providing feedback and addressing outstanding questions.
Register Now

Tianyu Dai's PhD Dissertation Defense
2022-11-07 12:30 - 14:00 (America/New_York)
“Robust Data-Driven Control”
Abstract:
During the last two decades, data-driven control (DDC) has attracted growing attention in the control community. Unlike model-based control (MBC), which first uses the collected data to identify the system, then designs the controller according to the certainty equivalence principle, DDC skips the system identification (SYSID) step and leads to a control law directly from data. One crucial feature of DDC is that some fundamental limitations of MBC, such as uncertainty versus robustness, inevitable modeling error, and possible expensive cost of SYSID, are avoided in the DDC framework. These benefits enable the researcher to design controllers with better performance and accuracy.
Robust data-driven control (RDDC) as a branch of DDC has developed rapidly in recent years, focusing on the data-driven controller design for the state space model. It aims to solve the following problem: given a single trajectory of noisy data and a few priors of the model structure, how to design a robust state feedback controller to stabilize the system with unknown dynamics, and in addition, to meet some performance criteria. By robust, we mean the learned controller can stabilize all possible systems residing in the set compatible with the noisy data.
This dissertation aims to summarize our contributions to the RDDC field. We focus on the L_infinity bounded noise, and the main idea hinges on duality theory to establish the connection between two sets, one compatible with the noisy data and the second satisfying some design properties such as stability or optimality. Our main results show that for all possible systems compatible with the data, the data-driven control law can be obtained by solving a convex optimization problem. In the dissertation, we propose RDDC algorithms for linear, switched, and nonlinear systems with process noise, extend results for error-in-variables (a more general case), and discuss a worst-case optimal estimation of the trajectory of a switched linear system.
Committee:
Prof. Mario Sznaier (Advisor)
Prof. Octavia Camps
Prof. Bahram Shafai
Prof. Eduardo Sontag

Giuseppe Michetti's PhD Dissertation Defense
2022-11-08 15:30 - 16:30 (America/New_York) | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
“RF Front-End Components based on Linear-Time-Variant Modulation of Piezoelectric MEMS Resonators”
Abstract:
Throughout the last decade, radio frequency (RF) components for over-the-air communication and sensing have been subject to sustained market pressure to adapt to the novel trends such as spectrum sharing, programmability, and low-power operation. When these features are required in chip-scale RF hardware, innovative solutions are necessary as conventional materials and techniques become bottlenecks for next-generation radios. In this work, we explore advanced wave manipulation circuital techniques such as Linear-Time-Variant (LTV) networks in conjunction with high-performance RF passives based on Micro-Electro-Mechanical Systems (MEMS) to address some of these challenges. Leveraging the unique spectral characteristic of RF MEMS resonators, we show some components based on LTV concepts, for novel RF systems with advanced spectral efficiency and real-time reconfigurability.
Using AlN and ScAlN thin film MEMS resonators as building blocks, we propose a design technique for MEMS-based LTV Circulators and Self Interference Cancelers, enabling chip-scaled RF full-duplex systems to enable efficient use of the RF spectrum with up to 47.5 dB cancellation in an 8 % bandwidth (BW) at 450 MHz. We introduce and validate experimentally MEMS-based LTV BW-tunable filters with high linearity (>30 dBm), and 5:1 BW tunability, designed for several bands from 100 MHz to 2.7 GHz for emerging paradigms such as software-defined-radios and cooperative networks. We also introduce MEMS-based near-zero energy RF front-end for the Internet-of-Things (IoT), implementing RF energy harvesting to power up a resonant Wake-Up Receiver circuit, with an experimental demonstration at (800 MHz) for deployment in remote sensor networks and emerging IoT wearable applications.
Along with the experimental validation of the proposed components, analytical and numerical tools are also discussed for future development and research.
Committee:
Prof. Matteo Rinaldi (Advisor)
Prof. Cristian Cassella
Prof. Andrea Alù
