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DTSTART:20210314T070000
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221102T120000
DTEND;TZID=America/New_York:20221102T130000
DTSTAMP:20260617T182927
CREATED:20221103T213443Z
LAST-MODIFIED:20221103T213443Z
UID:5946-1667390400-1667394000@ece.northeastern.edu
SUMMARY:Yuexi Zhang's PhD Proposal Review
DESCRIPTION:“Human Body and Activity Analysis” \nAbstract: \nHuman-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. \n  \nCommittee: \nDr. Octavia Camps(Advisor) \nDr. Mario Sznaier \nDr. Sarah Ostadabbas
URL:https://ece.northeastern.edu/event/yuexi-zhangs-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221102T140000
DTEND;TZID=America/New_York:20221102T150000
DTSTAMP:20260617T182927
CREATED:20221103T213638Z
LAST-MODIFIED:20221103T213638Z
UID:5950-1667397600-1667401200@ece.northeastern.edu
SUMMARY:Kai Huang's PhD Dissertation Defense
DESCRIPTION:“Partitioning Data Across Multiple\, Network Connected FPGAs with High Bandwidth Memory to Accelerate Non-streaming Applications” \nAbstract:\nField 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.\nIn 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. \nCommittee: \nProf. Miriam Leeser(advisor) \nProf. Stratis Ioannidis(co-advisor) \nProf. Mieczyslaw Kokar
URL:https://ece.northeastern.edu/event/kai-huangs-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221103T133000
DTEND;TZID=America/New_York:20221103T143000
DTSTAMP:20260617T182927
CREATED:20221103T184634Z
LAST-MODIFIED:20221103T184634Z
UID:5922-1667482200-1667485800@ece.northeastern.edu
SUMMARY:Lin Deng's PhD Proposal Review
DESCRIPTION:“On-chip and multiplexed metasurfaces for light manipulation” \nAbstract: \nMetasurfaces\, 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. \nIn 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). \nCommittee:\nProf. Yongmin Liu (Advisor)
URL:https://ece.northeastern.edu/event/lin-dengs-phd-proposal-review/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221104T130000
DTEND;TZID=America/New_York:20221104T160000
DTSTAMP:20260617T182927
CREATED:20221021T181420Z
LAST-MODIFIED:20221021T181420Z
UID:5850-1667566800-1667577600@ece.northeastern.edu
SUMMARY:NanoSI Workshop
DESCRIPTION: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. \nThe 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. \nRegister Now
URL:https://ece.northeastern.edu/event/nanosi-workshop/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221107T123000
DTEND;TZID=America/New_York:20221107T140000
DTSTAMP:20260617T182927
CREATED:20221103T191749Z
LAST-MODIFIED:20221103T191749Z
UID:5938-1667824200-1667829600@ece.northeastern.edu
SUMMARY:Tianyu Dai's PhD Dissertation Defense
DESCRIPTION:“Robust Data-Driven Control” \nAbstract: \nDuring 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. \nRobust 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. \nThis 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. \nCommittee: \nProf. Mario Sznaier (Advisor) \nProf. Octavia Camps\nProf. Bahram Shafai \nProf. Eduardo Sontag
URL:https://ece.northeastern.edu/event/tianyu-dais-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221108T153000
DTEND;TZID=America/New_York:20221108T163000
DTSTAMP:20260617T182927
CREATED:20221103T213536Z
LAST-MODIFIED:20221103T213536Z
UID:5948-1667921400-1667925000@ece.northeastern.edu
SUMMARY:Giuseppe Michetti's PhD Dissertation Defense
DESCRIPTION:“RF Front-End Components based on Linear-Time-Variant Modulation of Piezoelectric MEMS Resonators” \nAbstract: \nThroughout 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. \nUsing 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. \nAlong with the experimental validation of the proposed components\, analytical and numerical tools are also discussed for future development and research. \nCommittee: \nProf. Matteo Rinaldi (Advisor) \nProf. Cristian Cassella \nProf. Andrea Alù
URL:https://ece.northeastern.edu/event/giuseppe-michettis-phd-dissertation-defense/
LOCATION:432 ISEC\, 360 Huntington Ave\, Boston\, MA\, 02115\, United States
GEO:42.3396156;-71.0886534
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221115T140000
DTEND;TZID=America/New_York:20221115T150000
DTSTAMP:20260617T182927
CREATED:20221103T184043Z
LAST-MODIFIED:20221115T204305Z
UID:5920-1668520800-1668524400@ece.northeastern.edu
SUMMARY:Raana Sabri Khiavi's PhD Proposal Review
DESCRIPTION:“Theory and design of spatiotemporally-modulated metasurfaces for comprehensive control of light” \nAbstract: \nPhotonic 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. \nCommittee: \nProf. Hossein Mosallaei (Advisor) \nProf. Charles DiMarzio \nProf. Siddhartha Ghosh
URL:https://ece.northeastern.edu/event/raana-sabri-khiavis-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221118T110000
DTEND;TZID=America/New_York:20221118T120000
DTSTAMP:20260617T182927
CREATED:20221115T232757Z
LAST-MODIFIED:20221115T232757Z
UID:5962-1668769200-1668772800@ece.northeastern.edu
SUMMARY:PhD Dissertation Defense Shivang Aggarwal
DESCRIPTION:Location: ISEC 332 \n“Towards Reliable\, High Capacity mmWave Wireless LANs for Mobile Devices” \nAbstract: \nThe 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. \nIn 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.\nThis dissertation makes the following contributions:\n(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.\n(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.\n(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.\n(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.\n(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 \nCommittee:\nProf. Dimitrios Koutsonikolas (Advisor)\nProf. Kaushik Chowdhury\nProf. Tommaso Melodia
URL:https://ece.northeastern.edu/event/phd-dissertation-defense-shivang-aggarwal/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221122T110000
DTEND;TZID=America/New_York:20221122T120000
DTSTAMP:20260617T182927
CREATED:20221103T213322Z
LAST-MODIFIED:20221103T213322Z
UID:5942-1669114800-1669118400@ece.northeastern.edu
SUMMARY:Mahshid Asri's Proposal Review
DESCRIPTION:“Development of Anomaly Detection and Characterization Algorithms Using Wideband Radar Image Processing for Security Applications” \nAbstract:\nDetection 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.\nThis 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. \nCommittee: \nProf. Carey Rappaport (Advisor) \nProf. Charles DiMarzio \nProf. Edwin Marengo
URL:https://ece.northeastern.edu/event/mahshid-asris-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221128T120000
DTEND;TZID=America/New_York:20221128T140000
DTSTAMP:20260617T182927
CREATED:20221121T212045Z
LAST-MODIFIED:20221121T212045Z
UID:5973-1669636800-1669644000@ece.northeastern.edu
SUMMARY:Xuanyi Zhao's PhD Proposal Review
DESCRIPTION:“AlN/AlScN based Micro Acoustic Metamaterials for Radio Frequency Applications of the Next Generations” \nAbstract: \nIn 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. \nCommittee: \nProf. Cristian Cassella (advisor) \nProf. Matteo Rinaldi \nDr. Jeronimo Segovia-Fernandez
URL:https://ece.northeastern.edu/event/xuanyi-zhaos-phd-proposal-review/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221129T100000
DTEND;TZID=America/New_York:20221129T130000
DTSTAMP:20260617T182927
CREATED:20221104T010151Z
LAST-MODIFIED:20221104T010151Z
UID:5952-1669716000-1669726800@ece.northeastern.edu
SUMMARY:Research Presentations On Bendable Electronics and Sustainable Technologies (BEST)
DESCRIPTION: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. \n  \nThe presenters are: \nDr. Dhayalan Shakthivel\, Research Associate\, Inorganic Nanowires for Flexible and Large Area Electronics \nDr. Gaurav Khandelwal\, Post-doc\, Functional Materials based Triboelectric Nanogenerators for Selfpowered Sensors and Systems \nDr. Fengyuan Liu\, Post-doc\, “Hebbian-like” learning in electronic skin \nDr. Abhishek S. Dahiya\, Research Associate\, Towards energy autonomous electronic skin using sustainable technologies \nAyoub Zumeit\, PhD candidate\, Inorganic nanostructures-based high-performance flexible electronics \nAdamos Christou\, PhD candidate\, Novel Technologies for High-Performance Printed Electronics \nRadu Chirila\, PhD candidate\, Electronic Skin and Holographic Systems for Socially Intelligent Robots \nJoão Neto\, PhD candidate\, Hardware building for neuromorphic electronic skin \nLuca De Pamphilis\, PhD candidate\, Nanowire-based electronic layers for flexible neuromorphic devices \nMake sure to RSVP & specify inperson or virtual attendance. See you soon!
URL:https://ece.northeastern.edu/event/research-presentations-on-bendable-electronics-and-sustainable-technologies-best/
LOCATION:442 Dana\, 360 Huntington Ave\, 442 DA\, Boston\, MA\, 02115\, United States
GEO:42.3387508;-71.0923044
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=442 Dana 360 Huntington Ave 442 DA Boston MA 02115 United States;X-APPLE-RADIUS=500;X-TITLE=360 Huntington Ave\, 442 DA:geo:-71.0923044,42.3387508
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221129T140000
DTEND;TZID=America/New_York:20221129T153000
DTSTAMP:20260617T182927
CREATED:20221122T012209Z
LAST-MODIFIED:20221122T012209Z
UID:5975-1669730400-1669735800@ece.northeastern.edu
SUMMARY:Prof. Hui Guan -  "Towards accurate and efficient edge computing via multi-task learning "
DESCRIPTION:“Towards accurate and efficient edge computing via multi-task learning ” \n\nAbstract: \n\n\nAI-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. \n\n\nBio:\n \n\n\n\nHui 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.
URL:https://ece.northeastern.edu/event/prof-hui-guan-towards-accurate-and-efficient-edge-computing-via-multi-task-learning/
LOCATION:442 Dana\, 360 Huntington Ave\, 442 DA\, Boston\, MA\, 02115\, United States
GEO:42.3387508;-71.0923044
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