Bernard Herrera-Soukup PhD Dissertation Defense
2022-11-09 12:00 - 13:00 (America/New_York) | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
“Ferroelectric Micro-machined Ultrasonic Transducers for Biomedical and Processing In-Sensor Applications”
Abstract:
Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) are Micro Electro-Mechanical Systems (MEMS) devices that have become an established technology in applications such as range-finding, fingerprint sensing and imaging due to their capability of ultrasonic transduction in a miniaturized footprint, easily amenable to create large arrays. However, their application space still remains quite open. PMUTs are well fitted to applications in liquid media, such as implantable and underwater devices, due to their inherent acoustic matching and wide bandwidth. Thus, in the first part of the dissertationl, we explore novel applications such as PMUT-based intra-body and underwater networking, power transfer, source localization, wide-band matching and duplexing.
Aluminum Nitride (AlN) has been the material of choice for our PMUTs due to its biocompatibility and possibility of single-chip integration with supporting CMOS circuitry. Scandium doping of AlN thin films has recently been demonstrated to increase piezoelectric coupling coefficients while introducing ferroelectric properties in the material. However, a simultaneous use of both capabilities has not been demonstrated in the state-of-the-art. The ability of having distinct ferroelectric states, that alter the mechanical performance of the devices, allows for Processing-In-Sensor features and provides the building blocks for neuromorphic signal processing capabilities. The second part of the dissertation explores the AlScN material integration into novel Ferroelectric Micromachined Ultrasonic Transducers (FMUTs) and their emerging application space.

Committee:
Prof. Matteo Rinaldi (Advisor)
Prof. Tommaso Melodia
Prof. Cristian Cassella

MS Electrical and Computer Engineering Programs at the Roux Institute
2022-11-10 08:00 - 09:00
Join Roux Institute ECE faculty as they present a webinar on ECE offerings in Portland, Maine. This webinar will take place on November 10 from 8:00 to 9:00 am. Registration is required.

Using NVivo for Literature Reviews Webinar
2022-11-10 12:00 - 13:00
CEE GSC & QSR Internation Presents:Scholarly Writing Webinar:Using NViVo for Literature Reviews
When: November 10, 2022 12:00 PM Eastern Time (US and Canada) QSR International, the developers of NVivo are presenting a complimentary webinar on Scholarly Writing focused on how NVivo and reference management software, like Citavi can assist you throughout the writing process from literature review, outline, and first draft to publishing. They (QSR International) promise you will never have writer’s block again!The webinar will cover how you can use the power of NVivo & Citavi together to assist with your writing in the following ways:

Review of Literature: Easily search databases and websites for references to include in your project
Pre-Writing: Efficiently organize and annotate literature, and highlight critical quotes, comments, and ideas across many articles while developing a detailed outline
Writing: Export your outline with the content you highlighted into a Word document in seconds, taking you from the first draft to final publication
Revise & Edit: With Word integration, organize content and manage citations, plus references seamlessly
Publish: Speed up the writing process to help you publish faster and more often
Collaborate: Enable research groups of any size to work together – worldwide in the cloud.

NViVo is available for download by following these instructions.
REGISTER HERE FOR ZOOM WEBINAR

Guanying Sun's PhD Proposal Review
2022-11-11 10:30 - 11:30
“Optimizing Reconstruction for Mm-Wave Body Scanner Imaging”

Abstract:
In the past decades, due to evolving threats, passenger screening has become an important secure measure at airport and other secure locations. Numerous passenger screening techniques have been developed by researchers in both academia and industry to detect threats from explosives and weapons. Among these developments, the multistatic mm-wave radar Advanced Imaging Technology (AIT) system was developed at Northeastern University. A problem with this system is the sidelobes from its physical limitations, such as the finite aperture extent and the violation of the Nyquist sampling criterion by the sparse array. Therefore, it is important to suppress the sidelobes so that to improve the quality of the reconstruction image. In this proposal, we investigate two categories of methods, one is based on post-processing, and the other is based on system configuration optimization. In the former category four methods are developed, while in the latter two methods are proposed.
In the first category, the first method is the phase coherence method which is designed to weight the coherent sum based on the phase diversity of the reconstructed solutions for different transmitters. In this method, two ways are considered to construct the Phase Coherence Factor (PCF). The first way is to use the information of wrapped phase, and the second way is to use the information of unwrapped phase, which is more intuitive than the first way. The second method is the coherence factor related method. Three coherence-factor based methods are analyzed and then incorporated into the imaging procedure of our nearfield millimeter-wave radar security scanning system. The third method is SNR-dependent coherence factor method, which takes SNR into consideration when forming the coherence factor. This method can generate better results than the pure coherence-factor based methods by choosing a proper set of parameters. The fourth method is the block-weighting algorithm where the neighbor weight amplifies bright areas and attenuates dark areas, while the block keeps the influence to local. The effectiveness of these methods has been verified with both simulation and measurement data.
In the second category, the first method is optimizing receiver positions via PSF-based multi-objective optimization. Two metrics for measuring image quality of the PSF are proposed and defined as the objective functions. The solution-selection metric is introduced to select the desired solution from the numerous Pareto-optimal solutions. Simulation shows that the optimized receiver design generates images with lower sidelobe level than the uniform receiver design. The second method is the dual-frequency radar design, where a dual frequency, wideband antenna array is designed by combining a high frequency subarray with a low frequency subarray. The image of the dual frequency array is obtained by multiplying the images of the two subarrays. The PSF analysis and the system imaging simulation show that the grating lobes are significantly reduced for the dual frequency array with fewer radar modules/elements than the conventional array. This design will make the new generation system superior to the conventional scanning system.

Committee:
Prof. Carey Rappaport (Advisor)
Prof. Edwin Marengo
Prof. Jose Martinez-Lorenzo

Funding for Commercialization
2022-11-14 11:00 - 12:00
Commercialization of grant-funded research provides additional opportunities for Northeastern inventors to increase the impact of their work. Financial support is available to help you move your research out of the lab and into the hands of the people who will benefit. Join the College of Engineering and Center for Research Innovation (CRI) for a virtual panel discussion on procuring funding for commercialization. Our panel will include perspectives from faculty who have succeeded (and struggled) to secure commercialization-oriented funding. In addition, the panel will highlight financial support available at Northeastern to advance technologies towards commercialization including the CRI’s Spark Fund.
Moderator and panelists include:

Katie Hemphill – Director of Technology Ventures & Talent Network at the CRI
Sara Rouhanifard – Assistant Professor of Bioengineering, Co-Founder of ViralNPQ
Yi Zheng – Associate Professor of Mechanical and Industrial Engineering, Founder and President of Planck Energies
Randall Erb – Associate Professor of Mechanical and Industrial Engineering, Co-Founder of Boston Materials, Fortify, and Fourier

Register for the event

Crypto Event ZCash Researchers and Development Talk
2022-11-14 18:00 - 19:00
Location in Shillman Hall, Rm. 420 and Hybrid. Scan QR code in attached flyer to join via Zoom.
Ian Sagstetler is the communications and community manager at Electric Coin Company, the creator of Zcash. He is also founder of ZecHub, an education channel focused on the Zcash protocol. His focus is on amplifying those working to ensure humanity has access to censor-resistant money.
Creative Workshop Questions? Contact Parth Gargava, Parthgargava22@gmail.com

Raana Sabri Khiavi's PhD Proposal Review
2022-11-15 14:00 - 15:00
“Theory and design of spatiotemporally-modulated metasurfaces for comprehensive control of light”
Abstract:
Photonic metasurfaces are key platforms for manipulating almost all properties of light such as amplitude, phase, polarization, wave vector, pulse shape, and orbital angular momentum in a sub-wavelength dimension. They are capable of providing unprecedented modulation of wavefront through imparting spatial or temporal variation on the incoming wave. Recently, considerable efforts have been devoted to design active metasurfaces that enable real-time tuning and post-fabrication control of the optical response. Toward achieving this goal, electro-optically tunable materials such as doped semiconductors, multiple-quantum-wells (MQWs), and atomically thin sheets are incorporated into the building blocks of the geometrically-fixed metasurfaces. Despite the significant progress in this field, there has been several limitations imparted to the optical response of such so-called quasi-static metasurfaces. Remarkably, the strong resonant dispersion in such metasurfaces leads to narrow spectral and angular bandwidths. In addition, the co-varying amplitude and phase response as well as the limited phase modulation give rise to undesired artefacts manifested on their output profiles. The slow response time to the external stimuli is another drawback that restricts the performance of the metasurfaces. Introducing time into the external stimulus of the metasurfaces, as an additional degree of freedom, offers a way out to surmount the obstacles facing the quasi-static metasurfaces. Modulation in time enables myriad of exotic space-time scattering phenomena, where possibility to break the reciprocity and generation/manipulation of the sideband scattered signals offer the most appealing functionalities. The objective of this work is to investigate the less explored mechanisms for yielding reconfigurable plasmonic metasurfaces in both space and time. Several realizations of quasi-static and time-modulated devices integrated with the electro-optical materials such as indium-tin-oxide (ITO) with the potential wide phase modulation is presented. It has been shown that time-modulated metasurfaces are superior to their quasi-static counterparts in terms of providing access to the dispersionless modulation-induced phase shift spanning over 2π as well as the constant amplitude at the sidebands. Novel and unique applications of space-time photonic metasurfaces by spatiotemporal manipulation of light for all-angle, broadband beam steering, suppressing the undesired sidelobes, high speed continuous beam scanning, and dispersionless dynamic wavefront engineering are studied.
Committee:
Prof. Hossein Mosallaei (Advisor)
Prof. Charles DiMarzio
Prof. Siddhartha Ghosh

BioE Seminar Series Presents: Ryan Flynn
2022-11-16 12:00 - 13:00
Department of Bioengineering Seminar Series presents
Ryan Flynn, Ph.D
Assistant Professor, Boston Children’s Hospital’s Stem Cell Program and Harvard University’s Stem Cell and Regenerative Biology Department, Boston MA
“GlycoRNAs: bridging the gap between glycobiology and RNA biology”
Wednesday, November 16th, 2022
12:00 pm – 1:00 pm EST
105 Shillman Hall
ABSTRACT:
Glycans modify lipids and proteins to mediate inter- and intramolecular interactions across all domains of life. RNA is not thought to be a major target of glycosylation. Here, we challenge this view with evidence that mammals use RNA as a third scaffold for glycosylation. Using chemical and biochemical approaches, we found that conserved small noncoding RNAs bear sialylated glycans. These ‘‘glycoRNAs’’ were present in multiple cell types and mammalian species, in cultured cells, and in vivo. GlycoRNA assembly depends on canonical N-glycan biosynthetic machinery and results in structures enriched in sialic acid and fucose. Analysis of living cells revealed that the majority of glycoRNAs were present on the cell surface and can interact with anti-dsRNA antibodies and members of the Siglec receptor family. New insights into the molecular nature of glycoRNAs will be presented, which help to solidify the existence of a direct interface between RNA biology and glycobiology, and an expanded role for RNA in extracellular biology.
BIO:
Ryan is a New Jersey native who completed his undergraduate training at MIT, where he worked in the lab of Phillip Sharp on small noncoding RNA biology. Subsequently, he moved to Stanford where he completed his M.D. and Ph.D. with Howard Chang developing methods to study RNA-protein interactions. From this work, he won the Weintraub Graduate Student Award. As a post-doc, he changed fields to learn both chemistry and glycobiology with Carolyn Bertozzi at Stanford as a Damon Runyon Cancer Research Postdoctoral Fellow. At the beginning of 2021, the Flynn Lab opened at Boston Children’s Hospital in the Stem Cell Program and the Department of Stem Cell and Regenerative Biology at Harvard University. The Flynn Lab is currently focused on advancing methods and mechanisms surrounding the glycoRNA molecule, which operates at the interface of RNA biology and the secretory pathway.

Distinguished Seminar - David Horsley
2022-11-17 13:30 - 14:40 | 136 ISEC, 360 Huntington Ave, 136 ISEC, Boston, MA, 02115, United States
“Systems Based on Ultrasonic MEMS: Commercialization and Future Directions “
David Horsley
Professor, University of California, Davis Adjunct Professor, University of California, Berkeley

Abstract
The increasing maturity of thin-film piezoelectric materials and the MEMS manufacturing ecosystem has enabled the rapid development of sensor systems based on piezoelectric micromachined ultrasonic transducers (PMUTs). In this talk, I will describe work by my research group over the last decade to develop and commercialize PMUT-based systems for consumer electronics applications, starting with air-coupled PMUTs used for time-of-flight (ToF) range-finding and human presence sensing. These ToF sensors were commercialized by my startup, Chirp Microsystems (now part of TDK), and are used today in various products such as smart-locks, robot vacuum cleaners, and laptops. We subsequently developed an ultrasonic fingerprint sensor based on the monolithic integration of PMUTs with CMOS that is used for biometric authentication in consumer products today. A common feature of the ToF sensor and the fingerprint sensor is that they are systems that combine MEMS, integrated circuits, and algorithms. The ability to realize a complete ultrasonic system on chip (SoC) opens new research opportunities in areas such as portable medical imaging systems for point-of care ultrasound (POCUS) as well as wearable ultrasonic devices.
Biography
David A. Horsley received his PhD in Mechanical Engineering from the University of California, Berkeley, in 1998. He is a Professor of Mechanical and Aerospace Engineering at the University of California, Davis, and an Adjunct Professor of Mechanical Engineering at the University of California, Berkeley, where he is co-director of the Berkeley Sensor and Actuator Center (BSAC). He is also co-founder and CTO of Chirp Microsystems Inc. (a TDK Group Company), a manufacturer of ultrasonic sensors using MEMS technology. Dr. Horsley was Co-Chair of the 2016 IEEE Sensors Conference, Co-Chair of the 2017 Transducers Research Foundation Napa Microsystems Workshop, and Co-Chair of the 2020 IEEE MEMS Conference. Dr. Horsley is an IEEE Fellow, a Fellow of the National Academy of Inventors, is a recipient of the National Science Foundation’s CAREER Award, the UC Davis Outstanding Junior Faculty Award, the 2016 NSF I/UCRC Association’s Schwarzkopf Award for Technological Innovation, and the 2018 East Bay Innovation Award. He has authored or co-authored over 200 scientific papers and holds over 30 patents.

PhD Dissertation Defense Shivang Aggarwal
2022-11-18 11:00 - 12:00
Location: ISEC 332
“Towards Reliable, High Capacity mmWave Wireless LANs for Mobile Devices”
Abstract:
The IEEE 802.11ad standard, with its 14 GHz of unlicensed spectrum around 60 GHz, is touted as one of the key technologies for building the next generation of WLANs that will enable high throughput demanding mobile applications. However, there have been serious concerns regarding the susceptibility of mmWave links to mobility and blockage as well as smartphone energy consumption at Gigabit scale data rates.
In this dissertation, first, through extensive measurement campaigns with commercial off-the-shelf (COTS) devices as well as a highly configurable software-defined radio (SDR) based testbed, we characterize the performance and energy efficiency of mobile devices operating in 60 GHz WLANs and identify problems that prevent wide adoption of the mmWave technology in such devices. Then, using the insights from these measurement campaigns, we design solutions to tackle these problems and prototype them for real-world evaluation.
This dissertation makes the following contributions:
(i) We extensively study the performance and power consumption of 802.11ad on commercial smartphones. We focus on the specific aspects affected by unique smartphone features, e.g., antenna placement or user mobility patterns, and compare the performance against that achieved by 802.11ad laptops in previous studies. We also compare 802.11ad against its main competitors 802.11ac and 802.11ax. Overall, our results show that 802.11ad is better able to address the needs of emerging bandwidth-intensive applications in smartphones than its 5 GHz counterparts. At the same time, we identify several key research directions towards realizing its full potential.
(ii) We extensively study the two main link adaptation mechanisms in 802.11ad, rate adaptation (RA) and beamforming. We undertake a large measurement campaign using an SDR-based testbed giving us complete access to the PHY and MAC layers. We look at the two link adaptation mechanisms separately and study the effectiveness of a few RA and beamforming heuristics. Further, look at the interaction between the two link adaptation mechanisms, specifically, which mechanism should be triggered when and in what order. We design a practical, standard-compliant link adaptation framework that leverages ML and PHY layer information to determine when to trigger link adaptation and which adaptation mechanism to use.
(iii) To address the issues with mmWave link reliability, we explore the use of multiple frequency bands to couple the performance of 802.11ad with the reliability of legacy WiFi. To accomplish this, we develop a Multipath TCP (MPTCP) scheduler to efficiently use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switch to a single interface when the other one fails. Further, we port MPTCP to a dual-band (5 GHz/60 GHz) smartphone, evaluate its power consumption, and provide recommendations towards the design of an energy-aware MPTCP scheduler.
(iv) To enable high user QoE, and maintain that in the face of ever-changing network conditions, applications such as virtual reality (VR) and video streaming perform quality adaptation. A key component of quality adaptation is throughput prediction. Thus, we extensively study the predictability of the network throughput of an 802.11ad WLAN in downloading data to an 802.11ad- enabled mobile device under varying mobility patterns and orientations of the mobile device.
(v) With a dramatic increase in throughput requirements of applications and AP-user density in the near future, multi-user multi-stream communication in the 60 GHz band is required. To this end, the IEEE 802.11ay standard, successor to the current 802.11ad standard, includes support for simultaneous transmission over multiple data streams. Using an SDR-based testbed, we extensively study the performance of SU- and MU-MIMO in 60 GHz WLANs in multiple environments, analyze the performance in each environment, identify the factors that affect it, and compare it against the performance of SISO. Finally, we propose two heuristics that perform both beam and user selection with low overhead while outperforming previously proposed approaches
Committee:
Prof. Dimitrios Koutsonikolas (Advisor)
Prof. Kaushik Chowdhury
Prof. Tommaso Melodia

COE FacDev Friday: Managing Your Finances and How COE can Help
2022-11-18 13:00 - 14:00

Interdisciplinary Women's Collaborative Hackathon
2022-11-19 08:00 - 22:00 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
The IWC will be hosting our first annual Hackathon! This event will take place on November 19th from 8am-10pm in the Curry Student Center. It is open to women and non-binary undergraduate and graduate students and we welcome all experience levels. There will be corporate sponsors, free swag, and food is provided. All members from a team must sign up, even if the team is tentative. Please sign up if this is of interest, and we will be in touch with teams in early November.
Sign up here

Research Initiation: Analyzing inequities in undergraduate workforce opportunities between biomedical and other engineering disciplines
2022-11-21 12:00 - 13:00
Monday, November 21st at 12pm (VIRTUAL)

Please Register:
https://bit.ly/3MxqA0u
All attendees receive a FREE BOOK!
Abstract: Biomedical Engineering majors have been shown to exhibit higher rates of transfer to different engineering majors, lower rates of internship and career employment offers, and lower average starting salary compared to other engineering majors. These inequities in undergraduate workforce opportunities are having adverse effects on the professional formation of Biomedical Engineers. This NSF study seeks to initiate a characterization of the challenges in the university-to-industry pipeline through investigating workforce opportunity between biomedical engineers and three other engineering majors at a large Midwestern University.
Speaker 1: Tanya Nocera
Clinical Associate Professor, Biomedical Engineering, The Ohio State University
Speaker 2: David Delaine
Assistant Professor, Engineering Education, The Ohio State University

Info Session: Dialogue in Turkey
2022-11-21 14:00 - 14:30
If you are interested in joining the Dialogue of Civilization program in Turkey (summer 1 2023), you can attend the Info Session which takes place on Mon 21st, from 2:00 pm – 2:30 pm. This event is hybrid and you can RSVP using this link.
Also, please visit the program brochure page for more information.

Mahshid Asri's Proposal Review
2022-11-22 11:00 - 12:00
“Development of Anomaly Detection and Characterization Algorithms Using Wideband Radar Image Processing for Security Applications”
Abstract:
Detection and characterization of suspicious body-worn objects is necessary for safe and effective personnel screening. In airports, developing a precise system that can distinguish threats and explosives from objects like money belt can reduce the pat-down significantly while maintaining effective security.
This work proposes two main algorithms which are developed for different millimeter-wave radar systems. The first project is a material characterization algorithm designed for a 30 GHz wideband multi bi-static radar system used for passenger screening in airports. The proposed algorithm can automatically distinguish lossless materials from lossy ones and calculate their thickness and permittivities. Starting from the radar reconstructed image showing a cross-section of the body, we extract the nominal body contour using Fourier series, separate body and object responses, categorize the object as lossy or lossless based on the depression and protrusion of the body contour, and finally predict possible values for the object’s permittivity and thickness. Our resulting classification is good, implying fewer nuisance alarms at check points. The second project is a metal detection algorithm designed to monitor pedestrians walking along a sidewalk for large, concealed metallic objects. Finite Difference Frequency Domain and SAR algorithms are used to simulate the images produced by this 6 GHz wideband radar system.
Committee:
Prof. Carey Rappaport (Advisor)
Prof. Charles DiMarzio
Prof. Edwin Marengo

Can Qin's PhD Proposal Review
2022-11-28 10:00 - 11:00
“Transfer Learning across Domains, Tasks and Models”
Abstract:
The big data stands as a cornerstone of deep learning, which has significantly improved a wide range of machine learning and computer vision tasks. Despite such a great success, data collection is time-consuming and costly, considering manual efforts and privacy restrictions. Transfer learning is a promising direction toward data-efficient AI by leveraging acquired data and pre-trained models as guidance. This dissertation focus on the feature and model transfer across different domains and tasks, which can be roughly summarized into three sections. (1) Section One focuses on Unsupervised Domain Adaptation (UDA) without any labels in the target domain. The technical challenge of UDA is the distribution mismatch across domains. I have presented a hierarchical alignment model as the solution. (2) Section Two extends UDA into semi-supervised domain adaptation (SSDA) with minimal target-domain labels, which is useful and effortless to acquire. To avoid overfitting toward labeled data, I have proposed structural regularization verified on different classification benchmarks. (3) Section Three mainly explores the model transfer, including teacher-student knowledge distillation and heterogeneous models infusion with a high potential for model compression and enhancement.
Committee:
Prof. Raymond Fu (Advisor)
Prof. Octavia Camps
Prof. Huaizu Jiang

Xuanyi Zhao's PhD Proposal Review
2022-11-28 12:00 - 14:00
“AlN/AlScN based Micro Acoustic Metamaterials for Radio Frequency Applications of the Next Generations”
Abstract:
In the last two decades‚ micro-acoustic resonators (μARs) have played a key role in integrated 1G-to-4G radios‚ providing the technological means to achieve compact radio frequency (RF) filters with low loss and moderate fractional bandwidths (BW<4%). More specifically‚ Aluminum Nitride (AlN) based filters have populated the front-end of most commercial mobile transceivers due to the good dielectric‚ piezoelectric and thermal properties exhibited by AlN thin-films and because their fabrication process is compatible with the one used for any Complementary Metal Oxide Semiconductor (CMOS) integrated circuits (ICs). Nevertheless‚ the rapid growth of 5G and the abrupt technological leap expected with the development of sixth-generation (6G) communication systems are expected to severely complicate the design of future radio front-ends by demanding Super-High-Frequency (SHF) filtering components with much larger fractional bandwidths than achievable today. In the meantime, as more acoustic filters replying on bulk waves which requests the devices to be physically-suspended to operate, thermal related nonlinearity has been a challenge which requests new designs to enhance the thermal linearity thus power handling for these acoustic components. Even more‚ the recent invention of on-chip nonreciprocal components‚ like the circulators and isolators recently built in slightly different CMOS technologies‚ has provided concrete means to double the spectral efficiency of current radios by enabling the adoption of full-duplex communication schemes. Nevertheless‚ for such schemes to be really usable in wireless systems‚ self-interference cancellation networks including wideband‚ low-loss and large group delay lines are needed. Yet‚ the current on-chip delay lines that are also manufacturable through CMOS processes‚ which rely on the piezoelectric excitation of Surface Acoustic Waves (SAWs) or Lamb Waves in piezoelectric thin films‚ have their bandwidth and insertion-loss severely limited by the relatively low electromechanical coupling coefficient exhibited by their input and output transducers. As a results‚ these components are hardly usable to form any desired self-interference cancelation networks. In order to overcome these challenges‚ only recently‚ new classes of microacoustic resonators and delay lines exploiting the high piezoelectric coefficient of Aluminum Scandium Nitride (AlScN) thin films and the exotic dispersive features of acoustic metamaterials (AMs) have been emerging. These devices rely on forests of locally resonant piezoelectric rods to generate unique modal distributions‚ as well as unconventional wave propagation features that cannot be found in conventional SAW and Lamb wave counterparts. In this presentation‚ the design‚ fabrication and performance of the first microacoustic metamaterials (μAMs) based resonators and delay lines will be showcased. Moreover, AMs based reflectors are invented and demonstrated providing new improving the linearity and power handling of the AlScN μARs. In addition to reviewing the current status of our work, we will propose several further explorations of using our AlN/AlScN based AMs in RF applications of the next generations.
Committee:
Prof. Cristian Cassella (advisor)
Prof. Matteo Rinaldi
Dr. Jeronimo Segovia-Fernandez

Research Presentations On Bendable Electronics and Sustainable Technologies (BEST)
2022-11-29 10:00 - 13:00 | 442 Dana, 360 Huntington Ave, 442 DA, Boston, MA, 02115, United States
Professor Ravinder Dahiya will be joining Northeastern’s ECE Department on January 2023. Please join us for an interactive mini-symposium featuring projects from the BEST Lab directed by Professor Dahiya.

The presenters are:
Dr. Dhayalan Shakthivel, Research Associate, Inorganic Nanowires for Flexible and Large Area Electronics
Dr. Gaurav Khandelwal, Post-doc, Functional Materials based Triboelectric Nanogenerators for Selfpowered Sensors and Systems
Dr. Fengyuan Liu, Post-doc, “Hebbian-like” learning in electronic skin
Dr. Abhishek S. Dahiya, Research Associate, Towards energy autonomous electronic skin using sustainable technologies
Ayoub Zumeit, PhD candidate, Inorganic nanostructures-based high-performance flexible electronics
Adamos Christou, PhD candidate, Novel Technologies for High-Performance Printed Electronics
Radu Chirila, PhD candidate, Electronic Skin and Holographic Systems for Socially Intelligent Robots
João Neto, PhD candidate, Hardware building for neuromorphic electronic skin
Luca De Pamphilis, PhD candidate, Nanowire-based electronic layers for flexible neuromorphic devices
Make sure to RSVP & specify inperson or virtual attendance. See you soon!

Prof. Hui Guan - "Towards accurate and efficient edge computing via multi-task learning "
2022-11-29 14:00 - 15:30 | 442 Dana, 360 Huntington Ave, 442 DA, Boston, MA, 02115, United States
“Towards accurate and efficient edge computing via multi-task learning ”

Abstract:

AI-powered applications increasingly adopt Deep Neural Networks (DNNs) for solving many prediction tasks, leading to more than one DNNs running on resource-constrained devices. Supporting many models simultaneously on a device is challenging due to the linearly increased computation, energy, and storage costs. An effective approach to address the problem is multi-task learning (MTL) where a set of tasks are learned jointly to allow some parameter sharing among tasks. MTL creates multi-task models based on common DNN architectures and has shown significantly reduced inference costs and improved generalization performance in many machine learning applications. In this talk, we will introduce our recent efforts on leveraging MTL to improve accuracy and efficiency for edge computing. The talk will introduce multi-task architecture design systems that can automatically identify resource-efficient multi-task models with low inference costs and high task accuracy.

Bio:

Hui Guan is an Assistant Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst, the flagship campus of the UMass system. She received her Ph.D. in Electrical Engineering from North Carolina State University in 2020. Her research lies in the intersection between machine learning and systems, with an emphasis on improving the speed, scalability, and reliability of machine learning through innovations in algorithms and programming systems. Her current research focuses on both algorithm and system optimizations of deep multi-task learning and graph machine learning.

Summer 1, 2023 Panama DOC: International Applications of Fluid Mechanics – Info Session
2022-11-29 18:00 - 19:00
If you are interested in learning fluid mechanics through relevant examples in an international setting in a Dialogue Of Civilization (DOC) program this summer in Panama, please join the Zoom Info Session on Tuesday, November 29th at 6:00 pm. By participating in this program, you will gain an international perspective on the real-life applications of fluid mechanics, while learning about the culture and history of this burgeoning and diverse Latin America country. This program will take place in Summer 1, 2023 and will include travel to 3 relevant engineering projects (including the Panama Canal) in different locations in Panama. Two courses are offered under this program:

ME 3480 – International Applications of Fluid Mechanics (4SH; equivalent to ME 3475, ME degree core course requirement)
Studies fundamental principles in fluid mechanics in an international setting. Students have an opportunity to travel to a foreign locale to develop theoretical understanding while experiencing the issues that affect applications of fluids engineering in a culture and environment different from their own. Topics include hydrostatics (pressure distribution, forces on submerged surfaces, and buoyancy); Newton’s law of viscosity; dimensional analysis; integral forms of basic laws (conservation of mass, momentum, and energy); pipe flow analysis; differential formulation of basic laws including Navier-Stokes equations; and the concept of boundary layer and drag coefficient.

ME 4699 – Special Topics in Mechanical Engineering: Fluid Mechanics Engineering Analysis within the Socio-Cultural, Political and Economic History of Panama (4SH)
This course is designed for college undergraduate students who are interested in addressing and analyzing fluid mechanics related engineering problems and solutions in the context of the traditions, cultures, and socioeconomic and political history of Panama, seeking to obtain a solid grasp on the historical developments of the country and their effects on contemporary fluid mechanics engineering projects and issues.

The courses and program will be taught and run by Prof. Carlos Hidrovo Chavez.
Please visit the program website for more information.

Engineering Elastin-like Peptides to Control Solid Surface Properties: A Biomaterials Research Platform and Education Tool
2022-11-30 12:00 - 13:00 | 236 Richards, 360 Huntington Ave, Boston, MA, 02115, United States
ChE Seminar Series Presents: Dr. Julie N. Renner
Associate Professor, Department of Chemical Engineering, Case Western Reserve University
Abstract: Key biomaterials applications (e.g., bioelectronics, drug delivery, and tissue engineering) rely on control of solid surface properties for success. Surface-bound peptide monolayers are a promising way to control surface properties because peptides are biocompatible, easily tunable, can be stimuli-responsive, and possess specific secondary structures and binding capabilities. Our work focuses on enabling surface-bound peptide monolayers as a means of precisely engineering surfaces for biomaterials applications by understanding their assembly and sequence-driven properties. Specifically, we are establishing new engineering models to control and understand the behavior of surface-bound elastin-like peptides. We use a quartz crystal microbalance with dissipation to provide detailed information about the binding behavior of the peptides under various conditions, including in an electric field. We also use techniques such as Fourier-transform infrared spectroscopy, atomic force microscopy, and cyclic voltammetry to further probe our materials. These techniques combined with traditional peptide analysis tools show that 1) the coverage of surface-bound elastin-like peptides can be predicted with a simple linear model based on mass loading and hydrophobicity and 2) control of peptide orientation can be achieved using a combination of electric field and peptide chemistry which results in the ability to dictate surface morphology, loading and properties. In addition, we demonstrate that biomolecular engineering is an excellent platform for service learning which engages East Cleveland high school students, as well as CWRU undergraduate and graduate students in way that significantly increases their self-efficacy in science and engineering. Generally, our results demonstrate that engineered surface-bound peptides are promising tools for biomaterials design and excellent education tools for helping to achieve a more diverse STEM workforce.
Bio: Dr. Julie N. Renner is a Climo Associate Professor at Case Western Reserve University. Her group has multiple projects developing biomolecular platforms to control solid-liquid interfaces including projects in nutrient recycling technology, resource recovery, antifouling, and biomaterials. Her work has been recognized by the National Science Foundation (NSF) CAREER award, an Electrochemical Society Toyota Young Investigator Fellowship, and the Case School of Engineering Research Award. In addition, her efforts in the classroom have received the Case School of Engineering Undergraduate and Graduate Teaching Awards. Prior to becoming a professor, Dr. Renner worked in a broad range of research areas. She spent four years conducting industrial research at Proton OnSite (now Nel Hydrogen), a world-leader in hydrogen generation via proton exchange membrane electrolysis. She completed her thesis as an NSF Graduate Research Fellow at the Purdue School of Chemical Engineering, where she specialized in designing, creating, and characterizing novel polypeptide materials for tissue engineering applications. She earned her bachelor’s degree in chemical engineering from the University of North Dakota where she worked on environmental remediation projects.

DOC info session: Sustainable Waste Management in Cagliari, ITALY
2022-11-30 17:00 - 18:00
Learn about the Summer 1 Dialogue of Civilizations on Sustainable Waste Management in Cagliari, ITALY
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Meeting ID: 960 2359 0759
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Postgrad Virtual Fair - Africa & Middle East
2022-12-01 10:00 - 14:00
Join the Graduate Admissions team at The Student World’s Virtual Postgrad Fair! Talk with an admissions representative and learn more about our graduate engineering programs.
Registration and event information may be found at the website below. We look forward to seeing you there!

Public Policy for Healthcare Cyber Security: Fireside Chat with Senator Mark Warner
2022-12-01 15:00 - 16:00
Zoom Registration Required: https://tinyurl.com/archimedes-warner
From hospital floors to medical device manufacturing factory floors, health care cybersecurity faces daunting challenges including unpatchable legacy medical devices, ransomware disrupting patient care, privacy breaches of patient records, cybersecurity workforce development, and basic cyber hygiene. U.S. Senator Mark Warner recently published a paper, “Cybersecurity is patient safety: policy options in the health care sector.” Join a conversation with Senator Mark Warner and moderator Prof. Kevin Fu, PhD, of the Archimedes Center for Health Care and Medical Device Security presently at the University of Michigan.
Senator Mark Warner was elected to the U.S. Senate in November 2008 and reelected to a third term in November 2020. He serves on the Senate Finance, Banking, Budget, and Rules Committees as well as the Select Committee on Intelligence, where he is the Chairman. He has a history of crafting legislation that addresses the cybersecurity challenges facing our nation. From 2002 to 2006, he served as Governor of Virginia. The first in his family to graduate from college, Mark Warner spent 20 years as a successful technology and business leader in Virginia before entering public office. An early investor in the cellular telephone business, he co-founded the company that became Nextel and invested in hundreds of start-up technology companies that created tens of thousands of jobs. Senator Warner and his wife Lisa Collis live in Alexandria, Virginia. They have three daughters.
Prof. Kevin Fu, PhD, founded the field of medical device security, served as the nation’s first Acting Director of Medical Device Cybersecurity at the U.S. Food and Drug Administration, and directs the Archimedes Center for Health Care and Medical Device Security at Michigan. Archimedes carries out higher education and academic research to protect Operational Technology (OT) cybersecurity of medical devices, health care delivery, and pharmaceutical factory floors. In 2023, Prof. Kevin Fu and Archimedes join Northeastern University in Electrical & Computer Engineering in the College of Engineering and the Khoury College of Computer Sciences.

First Year Engineering Expo
2022-12-02 08:00 - 17:00 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Please come to the Curry Student Center indoor quad and pit on Friday, December 2nd to see Northeastern’s First-Year Engineering Students’ inventive projects, games, and exhibits.
Students will showcase original board games, interactive projects geared to teach children sustainability concepts, and prolific prototypes to help solve a wide range of problems.
Each project applies the engineering concepts introduced this past semester, which includes the Engineering Design Process, Solidworks, AutoCAD, Programming with C++ and Matlab, and controlling microelectronics with Arduino.

Ramtin Khalili's PhD Dissertation Defense
2022-12-05 10:00 - 11:00
Abstract:
State estimation is a critical application in energy management systems. Due to the increased penetration of inverter-based resources, installed advanced infrastructure at all voltage levels, and unconventional loads like electric vehicle charging stations, a three-phase state estimator formulation is essential. The first issue is the convoluted formulation and modeling techniques that are required in three-phase systems studies. Moreover, the size of network matrices expanded, which makes the analysis computationally costly. This dissertation addresses this by proposing a new decoupled state estimation method. The idea is to exploit the linearity of measurement equations, decompose the three-phase coupled equations into three independent modal measurement equations, perform the state estimation independently for each mode, and finally reconstruct the three-phase quantities. This method is applicable to both radial and meshed three-phase networks. Furthermore, multi-phase structures can be handled by the new estimator, which makes the approach practical when monitoring mixed-phase feeder sections is of interest.
While utilities are investing in expanding the grid and installing more PMUs, there might not be enough PMUs to make the network observable in all networks, especially at lower voltage levels. So, PMU-based linear state estimators are not always feasible. On the other hand, SCADA measurements are available with adequate redundancy in most networks. However, SCADA-based state estimation is nonlinear, which brings various problems like divergence issues and significant CPU times. The computational complexity will be even worse if the three-phase state estimation is formulated based on SCADA measurements due to their nonlinear nature, which makes modal decoupling impossible. So, a new linear formulation has been proposed for both the positive-sequence and three-phase networks based on conventional measurements. This approach converts the nonlinear recursive problem into an iterative linear state estimation problem.
The inherent assumption in most of the state estimators is a perfect network model. However, network parameter errors are susceptible to errors that can bias the state estimation solution. This can deceive the existing bad data tools as parameter errors appear as if multiple interacting measurement errors occur locally. So, a two-stage method is proposed for parameter error identification and correction for large three-phase networks. A systematic PMU placement strategy is also proposed to ensure the detectability of parameter errors. The benefits of multi-area state estimation are demonstrated for the deregulated power grids for monitoring the local and boundary areas. It has also shown promising results in increasing the efficiency of state estimation using a distributed framework. Parameter and measurement errors can remain undetected as a result of weakened measurement redundancy on the boundaries. However, boundary errors in the area boundaries will be detected due to measurement consolidation at the coordination level.
Committee:
Prof. Ali Abur (Advisor)
Prof. Bahram Shafai
Prof. Mahshid Amirabadi

Dialogues of Civilization: Biomedical Imaging in Chile
2022-12-05 18:00 - 19:00
If you are interested in a Summer 1 Dialogue on Biomedical imaging and Chilean Culture in Santiago, there will be an info session on Monday 5 December, at 6pm in 302 Stearns, or on Zoom at
https://northeastern.zoom.us/j/99185015932
Meeting ID: 991 8501 5932

Enabling Engineering Fall Showcase
2022-12-06 13:30 - 15:30 | 002 Ell Hall, 360 Huntington Ave, Boston, MA, 02115, United States
Please come to the Enabling Engineering Fall Showcase on Tuesday, December 6th, 1:30 -3:30pm ET in 002 Ell Hall where students will present their design projects.
Enabling Engineering is a Northeastern University student group that designs and builds devices to empower individuals with physical and cognitive disabilities. Our students collaborate with clients on projects that provide greater independence, reduce medical burdens, and increase social connectedness. We help family members, clinicians, and teachers care for people with disabilities. By giving students the opportunity to participate in Enabling Engineering projects, we are training the next generation of engineers to be knowledgeable about, and aware of, the needs of individuals with disabilities.

Md Navid Akbar's PhD Dissertation Defense
2022-12-06 16:00 - 17:30
“Inference from Brain Imaging: Incorporating Domain Knowledge and Latent Space Modeling”
Abstract:

Brain imaging can probe the anatomy (structural) of our brain, or its function (functional). A particular imaging modality (unimodal) generally provides only a particular insight into human health. Transcranial magnetic stimulation (TMS), though still in its infancy as a brain imaging modality, is such a functional, unimodal technique. TMS helps model human motor-cortical mapping, using corresponding muscle activity captured by surface electromyography (EMG), but it necessitates a reliable data-driven model. Earlier works have modeled the causal direction only (from cortical representation to muscles), or the inverse direction (from muscles to cortical representation), with simple statistical regression. We modeled this motor-cortical mapping bi-directionally in this dissertation, using deep learning. We first modeled TMS-induced 3D electric field (E-field) in a brain to causal multi-muscle activation picked up by EMG, in a regression task using a convolutional neural network (CNN) autoencoder. By fusing neuroscience domain knowledge (e.g., an empirical neural response profile), we reduced 14% squared error, compared to the baseline model that did not contain this. We then designed our novel inverse imaging CNN model, to reconstruct physiologically meaningful E-field distributions (in the image domain) from a given set of muscle activations (in the sensor domain). By adopting variational inference in the CNN model, to learn the underlying latent space better, we were able to reduce 13% in squared error over our purely CNN baseline.
Diagnosis with brain imaging is often incomplete with a unimodal technique, and having multiple sources (multimodal) may be advantageous. Successful multimodal fusion can provide more holistic information, compared to its constituents. One relevant example is the classification of late post-traumatic seizure (LPTS). Previous works in this space have tackled LPTS classification with either unimodal functional imaging, or non-machine learning (ML) structural modeling. In this dissertation, we first undertook the ML classification of binary LPTS: with unimodal, structural brain imaging, namely diffusion magnetic resonance imaging (dMRI). By incorporating interpretable domain knowledge (post-traumatic lesion volume compensation), we improved 7% in the mean area under the curve (AUC) over the standard technique in literature. Finally, we classified LPTS for a larger sample of subjects, utilizing multimodal imaging, including functional MRI (fMRI) and electroencephalography (EEG). Following unsupervised imputation for any missing modality within the subjects, we introduced our novel multimodal fusion algorithm, which attempts to leverage the underlying structure of the multivariate information. We found that our proposed algorithm improved by 7% in AUC performance, over a naive Bayesian estimator that can handle missing data intrinsically.
Collectively, the work presented here demonstrated that incorporating domain knowledge in the modeling pipeline successfully improved inference. Similar improvements were also observed by learning and leveraging the possible underlying latent structure of the given information, and adapting the models accordingly.

Committee:

Prof. Deniz Erdogmus (Advisor)
Prof. Mathew Yarossi (Co-advisor)
Prof. Dominique Duncan
Prof. Sarah Ostadabbas

Offshore Wind Tech Week Network Reception
2022-12-06 17:00 - 19:00 | Alumni Center, 716 Columbus Ave, 6th Floor, Boston, MA, 02120, United States
This event will celebrate #OffshoreWindTechWeek – comprised of the National Offshore Wind R&D Symposium December 5 & 6 and the International Offshore Wind Technical Conference (IOWTC) December 7 & 8.
This networking reception will close out the 2022 Symposium and introduce the IOWTC, happening the following days on December 7 & 8 at Northeastern University. All offshore wind industry professionals are welcome to attend, regardless of whether they are attending Symposium or IOWTC.
*Note – All in-person NOWRDC Symposium registrants are automatically registered for this networking reception.
Location: Alumni Center at Northeastern University, 716 Columbus Ave, Boston, MA 02120
Register
