ECE PhD Proposal Review: Keng Chen
2021-08-30 09:30 - 10:30 (America/New_York)
PhD Proposal Review: Design of Accurate and Responsive Power Management Integrated Circuits for Microprocessor Systems
Keng Chen
Location: Zoom Link
Abstract: As technology improves, the processors used in data centers are becoming increasingly powerful. Since the number of complementary metal-oxide semiconductor (CMOS) transistors integrated into these processors continues to rise, it becomes more challenging to design the power management integrated circuits to accurately regulate the supply voltages and ensure fast operational speeds for the processors. Furthermore, with multi-core technology being extensively used in processor design, there is more than just one voltage rail per chip that needs to be precisely regulated. In this research, circuit design methods will be developed to improve the regulation accuracy, both of the output voltage and converter switching frequency, which are proposed for an integrated buck regulator designed for point of load (POL) applications. In order to ensure both accuracy and fast speed of operation, a constant-on-time (COT) architecture was selected for this integrated buck regulator design approach. To provide accurate output voltage regulation, the on-chip feedback sensing network and the bandgap reference circuit need to exhibit high accuracy. For this reason, a highly accurate bandgap reference generation circuit with 5.8 ppm/°C – 13.5 ppm/°C over a wide operational region (-40 °C to 150 °C) has been designed. This bandgap reference circuit has a current-mode architecture and provides a 1.16V reference voltage with a 3.3V supply. A multi-section curvature compensation method is proposed to alleviate the nonlinear temperature-dependent error from the bipolar junction transistor’s base-emitter voltage. The two operational amplifiers utilized in this bandgap reference design to generate proportional-to-absolute-temperature (PTAT) and complementary-to-absolute-temperature (CTAT) current sources share one auxiliary auto-zero amplifier to ensure low input-referred offset voltage. Within many voltage regulators, the feedback sensing network consists of multiple operational amplifiers, and a major error source is the impact of the input-referred offset voltages of these amplifiers.
This research introduces the utilization of two different input-referred offset voltage correction methods for multiple amplifiers. The multi-amplifier system under investigation is used for feedback sensing during voltage regulation. It contains an instrumentation amplifier consisting of three folded cascode stages, and an additional amplifier configured as a unity-gain buffer for a reference voltage. The first method in this work alleviates voltage offsets in a 4-amplifier system based on a shared auxiliary amplifier correction circuit that switches between different target amplifiers. The second method applies a chopping-based auto-zero procedure to cancel the input-referred offset voltage of the same system. Since chopping causes voltage ripples, a correction circuit with a successive approximation register (SAR) analog-to-digital converter is used to reduce the output ripples. Both proposed methods can achieve less than 1mV feedback sensing error in voltage regulator applications.
For the constant-on-time buck regulator itself, a new frequency locking loop to regulate the on-time pulse is also proposed in this work. The system shows less than 1% frequency shift over a wide programmable operational frequency range (400 KHz to 2 MHz). This frequency accuracy will further benefit the constant-on-time circuit to meet electromagnetic interference requirements without harming the fast-transient performance.

Northeastern University Graduate Expo
2021-08-31
This day-long virtual experience will allow you to connect with staff, students, and admissions representatives to learn more about the university and how we can help your academic journey and career.

Click here to view the agenda for the day.

Join live panels and information sessions during the event and enjoy access to on-demand video content whenever you’d like.

Register Today

Inside the PhD Fellowship Experience: Grad Student Panelists Share Advice and Insights
2021-09-02 14:00 - 15:00 (America/New_York)
In a panel co-presented by the College of Engineering CommLab, Khoury College Graduate Program, and the Network Science Institute, this panel reveals the experiences and insights of doctoral students who have been awarded fellowships. The six panelists, responding to questions from the moderator and audience, will discuss such topics as the application or nomination process, tips for effective application statements and supporting materials, and the place of a fellowship award in one’s doctoral career.
Though the discussion may focus on opportunities for STEM doctoral students, we will also touch on general principles and suggestions that may be helpful to grad students in any discipline, so anyone from the NU grad community is welcome to attend.
Register to join us by Zoom

ECE PhD Proposal Review: Nikita Mirchandani
2021-09-03 11:00 - 12:00 (America/New_York)
PhD Proposal Review: Ultra-Low Power and Robust Analog Computing Circuits and System Design Framework for Machine Learning Applications
Nikita Mirchandani
Location: Zoom Link
Abstract: As the scaling of CMOS transistors has almost halted, performance gains of digital systems have also started to stagnate. There is a renewed interest in alternate computing techniques such as in-memory computing, hybrid computing, approximate computing, and analog computing. In particular, analog computing has reemerged as a promising alternative to save power and improve performance specifically for machine-learning (ML) applications. Analog computing has better area and power efficiency when compared to their digital counterpart. Power and chip area efficiency make analog computing highly appealing for implementing deep learning algorithms on-chip, computing circuits for the internet-of-things (IoT) devices, and implantable and wearable biomedical devices. However, compared to digital computing, analog computing methods have not nearly been utilized to their fullest potential due to longstanding challenges related to reliability, programmability, power consumption, and high susceptibility to variations.
The subject of this dissertation research is to develop robust ultra-low power analog hardware suitable for machine learning applications. First, a robust analog design methodology is presented to address issues of variability in analog circuits. A constant transconductance design technique using switched capacitor circuits is presented. The design approach is then applied to build circuits for ML applications. An analog vector matrix multiplier (VMM) is designed to be used in the convolutional layer in an ML analog computing vision hardware platform. Computing circuits are tested as part of an image classification DNN algorithm on the MNIST dataset and can achieve a classification accuracy of 96.1%.
The design approach is also used to design an analog computing system architecture for detection of seizures using EEG signals. A conventional EEG monitoring system includes an analog front-end (AFE), ADC, digital filtering stage, EEG feature extraction engine, and SVM classification. Such systems suffer from high power and chip area requirements. The corresponding analog architecture is composed of AFE amplifiers to provide gain for the incoming signal. The AFE is followed by an analog filtering stage, where spectral power from each of the bands is used as a feature for seizure classification. The output of each filter is applied to a corresponding feature extraction circuit to continuously monitor the onset of a seizure in an ultra-lower power mode with sub-threshold analog processing. The system level architecture is first modeled to obtain classification accuracy of seizures. Simulation times for the design of such complex analog systems can be prohibitively long, particularly when the impacts of nonidealities such as noise, nonlinearity, and device mismatches have to be considered at the system level. The simulation time is reduced by building accurate models of the analog blocks for faster simulations. The analog models help to define the required specifications for each block in order to achieve a specified system-level classification accuracy.
Infrastructure circuits like oscillators and voltage regulators for the proposed SoC are presented. A 254 nW 21 kHz on-chip RC oscillator with 21.5 ppm/oC temperature stability is presented to provide stable clock source for the proposed SoC.

Explore Global Engineering Co-ops
2021-09-09 12:00 - 13:00 (America/New_York)
The College of Engineering is offering advice on how to discover and pursue co-ops around the world, including search techniques, information on logistics, and tips for self-developing positions. For anyone planning to do an engineering co-op in Spring/Summer 2022, attendance is required at one of these sessions.
Learn More

ECE PhD Dissertation Defense: Wenqian Liu
2021-09-10 14:00 - 15:00 (America/New_York)
PhD Dissertation Defense: Explainable Efficient Models for Computer Vision Applications
Wenqian Liu
Location: Zoom Link
Abstract: State of the art deep learning based models, such as Convolutional Neural Networks (CNNs) and generative models, achieve impressive results, but with their great performance comes great complexity and opacity, huge parametric spaces and little explainability. The criticality of model explainability and output interpretability, manifests clearly in real-time critical decision making processes and human-centred applications, such as in healthcare, security and insurance. Explainability and interpretability are tackled in this thesis, as intrinsic qualities in the model architecture as well as post-hoc improvement on existing models. In the area of frame prediction in video sequences, we introduce DYAN, a novel network with very few parameters, that is easy to train and produces accurate high quality predictions. Another key aspect of DYAN is interpretability, as its encoder-decoder architecture is designed following concepts from systems identification theory and exploits the dynamics-based invariants of the data. We also introduce KW-DYAN, an extension of DYAN that tackles the issue of time lagging in video predictions, by implementing a novel way of quantifying prediction timeliness and proposing a new recurrent network for adaptive temporal sequence prediction. The experimental results show the reduced lagging across datasets, while also performing well in other metrics. In this thesis we also propose the first technique to visually explain VAEs by means of gradient-based attentions, with methods to generate visual attentions from the learned latent space, and also demonstrate such attention explanations serve more than just explaining VAEs. We show how these attention maps can be used to localize anomalies in images, conducting state-of-the-art performance on multiple datasets. We also apply our technique for skin image anomaly detection and diagnosis and achieve competitive quantitative and qualitative results.

GEM Annual Conference and Graduate Resource Fair
2021-09-11 08:00 - 14:00 (America/New_York)
The GEM Annual Conference will take place from September 9-11 in Houston Texas. During this event, GEM University and Employer Representatives will exhibit to promote their graduate and undergraduate (REU) research programs.

ECE PhD Dissertation Defense: Vageeswar Rajaram
2021-09-14 14:00 - 15:00 (America/New_York) | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
PhD Dissertation Defense: Near-Zero Power Microelectromechanical Sensors for Large-Scale IoT Sensor Networks
Vageeswar Rajaram
Location: ISEC 432
Abstract: The Internet-of-things revolution has ushered the development of sensing technologies aimed towards establishing large-scale remote sensor networks to monitor the environment continuously and with high spatial resolution. However, with existing sensor technologies this goal has so far been limited in terms of scalability (i.e., the number of sensors in a network, areal coverage and spatial granularity). A major impeding factor is sensor power consumption: state-of-the-art remote sensor technologies need to be actively powered (i.e., by a battery) to continuously monitor the environment for an object of interest, even at standby (when it is not present). This is because all signals collected by the sensor from the environment need to be processed by active signal conditioning circuits to distinguish a signal of interest from other signals. Therefore, in applications where an event or signal of interest occurs only occasionally, most of the battery is drained by processing irrelevant signals. The result is that as the sensor network scales up, so do the costs and labor associated with the sensors’ battery replacements. This makes it unfeasible to deploy and maintain large numbers of sensors for any application and greatly limits the scale of sensor networks. Extremely low power consumption therefore is critical in enabling large sensor networks by reducing or even eliminating costs associated with frequent battery replacements.
This work describes the development of a revolutionary new sensing platform aimed at creating sensors with battery lifetimes limited only by the self-discharge of the battery itself (>10 years). The ultimate goal for the technology is to enable maintenance-free sensor nodes for truly large-scale “deploy-and-forget” sensor networks. In particular, this work details the development of novel infrared sensors based on micro-electro-mechanical photoswitches that are capable of detecting and distinguishing specific infrared signatures associated with objects of interest (hot gases, fire, human body, etc.) while remaining dormant with near-zero power consumption at standby. This unique sensor technology aims to break the paradigm of requiring a power supply to perform sensing by instead relying on the energy contained in the infrared signals emitted by the object of interest itself to perform its detection. This dissertation presents a comprehensive summary of the sensor’s design, its capabilities, and the various technical developments that have led this technology to evolve from a concept to a prototype near-zero power wireless infrared sensor with orders of magnitude lesser power consumption compared to the state-of-the-art.

From Food to Resilience and Everything In Between
2021-09-14 17:00 - 18:30 (America/New_York)
This unique, interactive 7-part open seminar (attend one or all!) will feature guest speakers that explore the challenges and opportunities for implementing sustainable and resilient programs at Northeastern University. The class topics will include energy, recycling, ecology, resilience, sustainable food, and climate justice, as taught by Northeastern faculty and administrative staff. Civil and Environmental Engineering Assistant Professor Michael Kane is the guest speaker on 9/21/21.
When: Tuesdays, September 14 through October 26
Where: 305 Shillman | Via Zoom
Time: 5:00 p.m. to 6:30 p.m. EST
Registration and Details: https://facilities.northeastern.edu/sustainability/open-classroom-2021/

ECE PhD Proposal Review: Nirjhar Bhattacharjee
2021-09-16 16:00 - 17:00 (America/New_York)
PhD Proposal Review: Sputtered Topological Insulator/Ferromagnet Heterostructures for Energy Efficient Spintronic Device Applications
Nirjhar Bhattacharjee
Location: Zoom Link
Abstract: Topological insulators (TI) are Van der Waals (VdW) layered materials which possess enormous spin-orbit coupling (SOC) strength and spin-momentum locked robust surface states. TIs in presence of time-reversal symmetry breaking magnetic order can also exhibit chiral quantum anomalous (QAH) or Axion insulator edge channels. These and myriad of other material properties predicted, and achievable utilizing TIs, magnetic-TIs (MTI) and TI based heterostructures can open the path towards realization of a diverse class of energy efficient spintronic devices for information processing and storage. Crystalline oriented TIs which possess topologically nontrivial properties are grown using molecular beam epitaxy (MBE) which is incompatible with industrial CMOS processes. Magnetron sputtering, on the other hand is the CMOS industry stand thin film growth technique because of the advantages of high throughput, large area, and high quality thin film growth capability. In this work, first the growth of high quality TI: Bi2Te3 thin films using CMOS compatible magnetron sputtering process is introduced. Next, room temperature characterization of magnetic and SOT properties of TI/ferromagnet (FM) heterostructures will be presented. Finally, fascinating magnetic properties of material systems with FM species intercalated in TIs will be reported which can possibly house exotic quantum material phases.
By varying process temperature between 20-250ºC, growth of Bi2Te3 with stoichiometric composition and varying crystalline order from disordered to highly c-axis oriented VdW layered films were obtained. Using X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) imaging, the crystalline property of the TI film was confirmed. Further, coupling the sputtered TI films with ferromagnetic (FM) thin films surprisingly showed a giant enhancement in Gilbert damping with c-axis oriented TI which is crucial for energy efficient SOT-MRAM devices. This suggested enhancement in spin-orbit coupling strength for c-axis oriented TI thin films compared to disordered ones. Formation of interface layers because of elemental diffusion has been reported in literature. But, literature reports on SOT characteristics have largely assumed atomically sharp interfaces between TI and FM layers. We observed crystalline order dependent interface thickness and composition in Bi2Te3/Ni80Fe20 heterostructures because of diffusion of Ni across the interface. An enhancement in damping-line SOT in crystalline ordered Bi2Te3 was observed. The spin-charge conversion efficiency was however found to be larger for granular and lowest for polycrystalline disordered Bi2Te3 samples considering the interface layers. Further, with the intercalation of Ni in Bi2Te3, emergence of an antiferromagnetic VdW phase was observed in Ni-intercalated Bi2Te3 interface. This AFM VdW interface resulted in a large spontaneous exchange bias in Bi2Te3/Ni80Fe20 and Bi2Te3/NiZn-Ferrite heterostructures at temperatures below ~63 K which is higher than the transition temperatures of MTIs reported in literature. Structural and chemical characterization of the Ni-intercalated Bi2Te3 showed evidence of formation of Ni-Te bonds and indicated towards formation of MTI compounds. These results open new avenues for experimental exploration of fascinating high-temperature QAH and other topologically nontrivial material phases in interfaces of industrial CMOS process compatible sputter-grown TI/FM heterostructures. Understanding the properties of these TI based material systems can lead to realization of robust energy efficient spintronic devices.

Distinguished Lecture: Dr. Elliot Eichen
2021-09-20 13:00 - 14:00 (America/New_York)
The Institute for the Wireless Internet of Things is pleased to host a distinguished lecture on Real-time Geo-spatial Spectrum Sharing by Dr. Elliot Eichen.
When: Monday, September 20th, 1pm.
Location: Zoom Link
Abstract: New technology and new applications for wireless communications have created competition for frequency bands traditionally allocated to remote sensing and defense applications. Competition for spectrum is particularly intense in mm (and sub-mm) wave bands where the requirements for 5G/6G transmissions overlap with measurements made by passive radiometers (Earth Exploration Satellite Services – EESS) that are used for weather forecasting and as baseline data for climate models. Real-time Geospatial Spectrum Sharing (RGSS) enables EESS radiometers and 5G/6G networks to gracefully share spectrum by modifying network traffic during the time window (~ 10s of msec) that a base station (gNB) and its connected endpoints (UEs) are within the effective field of view (eFOV) of a radiometer. RGSS is based on existing network infrastructure rather than Monte-Carlo network simulations (the ITU model); it can provide better isolation between 5G/6G transmissions and EESS radiometers than the ITU’s hardware-based Out-of-Band (OOB) emission limits (e.g., -32 dBW/200MHz-gNB and -29 dBW/200MHz-UE) in dense urban environments, while simultaneously enabling carriers to create larger cell sizes and use network repeaters in suburban and rural settings. In addition, RGSS can adapt to changes in network or remote sensing technology by modifying the underlying network or EESS ecosystem descriptions (schemas).
In this talk, we show that RGSS:

Can prevent 5G/6G transmissions from corrupting EESS measurement data
Has sufficient geolocation accuracy to provide a realistic solution, based on experimental confirmation of predicted measurement pixels vs. actual measurement pixels
Applies to all mm-wave and submm-wave bands (e.g., a single system can be used for all bands, such as 24, 51, and 90 GHz, although the modification time windows for each band may be different)
Enables carriers to optimize network performance by geography and time of day, rather than designing for the worst-case scenario across the entire network (i.e., avoids the ” one size fits all” OOB emissions model)
Includes the effect of massive Multiple-Input Multiple-Output (MIMO) beamforming antennas
Is commensurate with existing 5G architectures and deployment models, and
Provides a simple mechanism to test and police compliance compared with over the air TRP OOB measurements.

Bio: Elliot Eichen retired as Director of R&D at Verizon in 2017, after a 35-year career (except for 2½ years on staff at MIT) at GTE Labs, GTE/BBN, and Verizon Labs. From 2018-2019, he was an IEEE-USA/AAAS congressional fellow, which is where he became interested in spectrum management and the overlap between 5G/6G and EESS passive sensors. Dr. Eichen received a Ph.D. in Optics from The University of Arizona, and a B.S in Physics from SUNY Stony Brook. His contributions to the technical community include associate editor of IEEE Photonics Technology Letters, committee chair of Optical Fiber Communications (OFC), chair of the IEEE/OSA Optical Amplifier Conference, Visiting Industry Professor at Tufts University, and adjunct faculty at NEU. He has more than 40 peer-reviewed publications and about 60 US patents.

ChE Seminar Series: Materials Innovation in Nanotechnologies
2021-09-22 12:00 - 13:00 (America/New_York) | 108 SN
ChE Seminar Series Presents:
Dr. Paulette Clancy, Ph.D
Head of the Department of Chemical and Biomolecular Engineering at Johns Hopkins University
Materials Innovation in Nanotechnologies
Abstract
There are many problems at the forefront of materials chemistry whose solution is stymied by its inherent complexity. Such problems are characterized by a rich landscape of parameters and processing variables that is combinatorially too large for either an experimental or a computational approach to solve through an exhaustive search. In such cases, the usual approach is an Edisonian trial-and-error approach, which inevitably leaves areas of parameter space unexplored. The problems that we have explored are also characterized by a scarcity of data, since the data are expensive to acquire, both experimentally and computationally. This makes it an ideal candidate to solve using a Bayesian optimization (BayesOpt) approach.
We have used a Bayesian approach to study several problems in self-assembly processes involving materials chemistry. This talk will discuss two mature test cases in which we used BayesOpt extensively to study (1) how to optimize the choice of solvent and halides to produce high quality thin films of lead-based hybrid organic-inorganic perovskites and (2) identify stable and metastable polymorphs of an organic semiconducting material. I will end with some ideas of where the BayesOpt field can expand its use in the chemical sciences and share some “lessons learned” in implementing BayesOpt and machine learning, which may be helpful to others who decide to start adding machine learning to their research repertoire.
Biography
Paulette Clancy is a Professor and the inaugural Head of the Department of Chemical and Biomolecular Engineering at Johns Hopkins University. She is also the Samuel and Diane Bodman Professor Emerita of Chemical Engineering at Cornell. She is the Associate Director of the Hopkins Center for Integrated Structure-Materials Modeling and Simulation. She was the inaugural Director of the Cornell Institute for Computational Science and Engineering for almost 10 years and is reprising a similar role at Hopkins, chairing our petascale research computing resources, ARCH.
Her research group is recognized as one of the country’s leading computational groups in atomic- scale modeling of materials and algorithm development. Her current thrust is to develop machine learning algorithms to accelerate the search for optimal materials processing protocols. Her group has always been focused on electronic materials, but it also includes more esoteric projects include xenobiology (Life on Titan) and a screening of therapeutic oligomers to maximize antibacterial ability. She has won numerous awards for mentoring, service learning and civic engagement, and promoting those from under- represented groups.

From Concept to Company: Navigating a Non-Linear Path
2021-09-23 18:30 - 19:30 (America/New_York) | Raytheon Amphitheater (240 Egan), 360 Huntington Ave, 240 Egan, Boston, MA, 02115, United States
Please join the Edward G. Galante Engineering Business Program in welcoming guest speaker Christina Chase for her presentation From Concept to Company: Navigating a Non-Linear Path. This talk will explore the different aspects of entrepreneurship, what it means to be entrepreneurial, and the concepts, tools and frameworks the most successful entrepreneurs employ to go from concept to company.
Christina Chase is a Lecturer at the MIT School of Engineering and the Managing Director of the MIT Sports Lab, which she co-founded in 2015. The lab works with global leaders across the field of sports to advance research in the fields of artificial intelligence, computer vision, mechanics, human and institutional behavior, machine learning, and statistics in areas, such as athlete health and performance, talent identification and development, game strategy, and fan engagement. The Sports Lab also focuses on the design and discovery of new materials and products to advance high-performance personal and protective equipment.
Chase teaches a number of courses in the School of Engineering, including Sports Technology: Engineering & Innovation, which she established to work with pro-sports teams, leagues and brands to tackle the challenges at the intersection of sports, engineering and data. She is also one of the contributing authors of 21st Century Sports: How Technologies Will Change Sports in the Digital Age (Springer 2021).
Chase also teaches in the MIT Sloan Executive Education in the field of sports analytics, as well as for international programs, such as MIT-Skoltech and the MIT-Portugal, in the field of innovation. In 2015, she helped establish and co-chair MIT’s Start6, now StartMIT, a bootcamp for MIT entrepreneurs and innovators.
Prior to this she was the first Entrepreneur-in-Residence at MIT’s Martin Trust Center for MIT Entrepreneurship where she helped hundreds of teams go from concept to company. In 2013, she was named one of the 25 Most Influential Women in the Boston Tech Community and in 2014, Mashable named her one of the 15 People Shaping Boston’s Tech Scene.
Chase started her first company at the age of 18 and is a former cyclist where she was one of 12 women selected by the US Cycling Federation to train at the US Olympic Training Center.
Chase serves on the External Evaluation Board for EIT Health, the European Union’s Institute of Innovation and Technology, is a Techstars mentor, and advisor and board member for multiple startups.

ECE PhD Proposal Review: Tianyu Dai
2021-09-27 11:00 - 12:00 (America/New_York)
PhD Proposal Review: Data-Driven Control and Estimation
Tianyu Dai
Location: Zoom Link
Abstract: During the last two decades, data-driven control (DDC) has attracted growing attention in the control community. Unlike model-based control (MBC) that 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 important 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.
The aim of this proposal is to summarize our contributions to the DDC field. We mainly discuss the following problem: given a single trajectory of noisy data and a few priors of the model structure, how to design a state feedback controller to stabilize the system with unknown dynamics and in addition, to meet some performance criteria. 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.
This proposal is organized as follows: to start with, we propose a DDC framework for switched linear systems relying on the Farkas’ lemma to search for a common polyhedral control Lyapunov function using the theory of moments. Then to reduce the computational burden, we provide another method called data-driven quadratic stabilization control for linear systems that is based on quadratic Lyapunov function. To deal with nonlinear system, we first design data-driven controllers for polynomial systems using the dual Lyapunov theorem. Then to handle general nonlinearities, we propose a method based on state-dependent representations. Finally, a data-driven estimator is proposed that gives the worst-case optimal estimation of the trajectory of a switched linear system.

Introduction to Citation Managers
2021-09-27 12:00 - 12:45, 2021-09-30 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn the basics of how to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.

Dialogue of Civilizations Info Session
2021-09-29 12:00 - 13:00 (America/New_York) | 420 Shillman Hall, 360 Huntington Ave, Boston, MA, 02115, United States
This info session is designed to introduce you to Dialogues of Civilization. Listen to students share their experiences. Presenters for this event are Joy Erb, COE and Amanda Earley, Global Experience Office who will be on hand to provide the details you need for this exciting opportunity.
Location: 135 Shillman Hall
Time: 12:00 – 1:00pm

ChE Seminar Series: Learning about Biological Interactions, Recognition, and Targeted Delivery Through Surface Forces
2021-09-29 12:00 - 13:00 (America/New_York)
ChE Seminar Series Presents:
Dr. Tonya Kuhl
Professor and Chair, Department of Chemical Engineering, UC Davis
Learning about biological interactions, recognition, and targeted delivery through surface forces
Abstract:
The promoters of cell adhesion are ligands, which are often attached to semi-flexible tethers that bind to surface receptors on adjacent cells. Drug delivery systems, such as Stealth Liposomes, have also attempted to use biological specificity to target therapeutic payloads. Using a combination of Monte Carlo simulations, diffusion reaction theory, and direct experiments (surface force measurements), we have quantified how polymer tethers alter the interaction and binding/capture based on biospecificity (ligand-receptor binding). Experimental and theoretical results as a function of molecular weight and bi-modal distributions will be discussed to enable rational design.
Biography:
Tonya Kuhl, is Professor and Chair of Chemical Engineering, the co-Director of the UC Davis Coffee Center (and co-instructor and developer of ECH 1 “The Design of Coffee”), and a faculty member of the Biophysics and Biomedical Engineering Graduate Groups. Her Bachelors was from the University of Arizona and Ph.D. from UCSB, both in chemical engineering. Her research interests are in the general area of colloidal science, self-assembly, and complex fluids. In particular, the Kuhl group studies a wide range of systems from surfactants, lipids and proteins to polymer coatings, nanoparticles and confined fluids. The common theme is that “interfaces are where stuff happens”. Her group studies interfaces by directly measuring the normal interactions (attractive and repulsive) between surfaces and their lateral friction using specialized high resolution force spectroscopy. Complementary x-ray and neutron scattering measurements are used to measure the exact film structure on a molecular level, enabling a fundamental understanding of how surface film structure and experimental conditions yield the measured properties. Rather than more empirical, “guess and test”, approaches for improvement in properties or functionality – the Kuhl group uses direct measurements and theory to enable predictive modeling and rational design.

Getting Started with Mendeley
2021-10-04 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn how to use Mendeley to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.

Further Education Expo
2021-10-06 09:00 - 17:00 (America/New_York)
Join the Graduate School of Engineering admissions team at the Further Education Expo. The fair is open to Ontario Tech and Durham College students. An admissions representative will be available throughout the day to answer your graduate school questions.

ECE PhD Proposal Review: Bin Sun
2021-10-06 11:00 - 12:00 (America/New_York)
PhD Proposal Review: Lightweight Neural Networks via Factorization
Bin Sun
Location: Zoom Link
Abstract: Deep learning has become popular in recent years primarily due to powerful computing devices such as GPUs. However, many applications such as face alignment, image classification, and gesture recognition need to be deployed to multimedia devices, smartphones, or embedded systems with limited resources. Thus, there is an urgent need for high-performance but memory-efficient deep learning models. For this, we design several lightweight deep learning models for different tasks with factorization strategies.
Specifically, we constructed a lightweight face alignment model by proposing a factorization-based deep convolution module named Depthwise Separable Block (DSB) and a light but practical module based on the spatial configuration of the faces. Experiments on four popular datasets verify that Block Mobilenet has better overall performance with less than 1MB storage size. Besides the face analysis application, we also explored a general, lightweight deep learning module for image classification with low-rank pointwise residual (LRPR) convolution, called LRPRNet. Essentially, LRPR aims at using a low-rank approximation to factorize the pointwise convolution while keeping depthwise convolutions as the residual module to rectify the LRPR module. Moreover, our LRPR is quite general and can be directly applied to many existing network architectures.
Due to the success of the factorization strategy on image-based data, we extended factorization on time sequence data for Sign Language Recognition (SLR). We achieved the first rank in the challenge of SLR with the help of our proposed novel Separable Spatial-Temporal Convolution Network (SSTCN), which divides a 3D convolution on joint features into several stages , which help the SSTCN achieve higher accuracy with fewer parameters.

Getting Started with EndNote for Mac
2021-10-06 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn how to use EndNote for Mac to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.

BioE Seminar: The Case for Diversity and Inclusion, From An Engineer’s Perspective
2021-10-06 12:00 - 13:00 (America/New_York) | 010 Behrakis, 360 Huntington Ave, Boston, MA, 02115, United States
Department of Bioengineering
Seminar Series
Karl W. Reid, Ed.D., CDP
Senior Vice Provost and Chief Inclusion Officer, Northeastern University “The Case for Diversity and Inclusion, From An Engineer’s Perspective”
Behrakis 010
ABSTRACT:
This talk makes the case for why diversity and inclusion matter and offers steps to creating more equitable and inclusive campuses and workplaces.
BIOGRAPHY:
Dr. Karl W. Reid was appointed Senior Vice Provost and Chief Inclusion Officer at Northeastern University on April 1, 2021. He also holds the title of Professor of Practice in the Graduate School of Education in the College of Professional Studies. Prior to joining Northeastern, Dr. Reid served for seven years as the Executive Director of the National Society of Black Engineers (NSBE), marking his return to the organization that gave him his first major leadership experience 32 years earlier. A certified diversity professional, Dr. Reid has been a leading national advocate for diversity and inclusion, and increasing college access, opportunity, and success for low-income and minority youth.
Dr. Reid came to NSBE from the United Negro College Fund (UNCF), where he oversaw new program development, research, and capacity building for the organization’s 37 historically black colleges and universities and held the title of Senior Vice President for Research, Innovation, and Member College Engagement. Before his service at UNCF, he worked in positions of progressive responsibility to increase diversity at his alma mater, the Massachusetts Institute of Technology (MIT), which he left as Associate Dean of Undergraduate Education and Director of the Office of Minority Education. While working at MIT as Director of Engineering Outreach Programs, Dr. Reid earned his Doctor of Education degree at Harvard University. His dissertation explored the interrelationship of race, identity, and academic achievement for African American males in college. He is the author of “Working Smarter, Not Just Harder: Three Sensible Strategies for Succeeding in College…and Life.” Dr. Reid is also a founding member of the 50K Coalition, a national effort to produce 50,000 diverse engineering graduates annually by 2025.
Dr. Reid was born in the Bronx, New York, and grew up in Roosevelt, New York, a mostly working-class, African-American community on Long Island. The high value his parents placed on education, and his admission to a well-resourced, magnet high school near Roosevelt, put him on a track to follow his older brother to MIT, where he earned his undergraduate and master’s degrees in Materials Science and Engineering and was a Tau Beta Pi Scholar. He credits his membership in the NSBE chapter at MIT with giving a vital boost to his self-confidence and leadership skills. He joined the Society during his freshman year, was elected chapter Vice President during his junior year, and subsequently served as NSBE National Chair.
After graduating from MIT, Dr. Reid worked in the computer industry for 12 years in product management, marketing, sales, and consulting. In 1991, five years into a successful career in sales and marketing with IBM Corporation, Dr. Reid read Jonathan Kozol’s “Savage Inequalities,” a seminal book about educational disparities in the U.S., which sparked his passion for bringing about positive change through the education of African Americans and other underserved populations.
Dr. Reid sits on the National Council for Expanding American Innovation at the US Patent and Trademark Office; the Committee on Addressing the Underrepresentation of Women of Color in Technology at the National Academy of Engineering; the American Society for Civil Engineers Industrial Leaders Council; the Dean’s advisory cabinets for the Harvard University School of Engineering and Applied Sciences and the University of Michigan College of Engineering. He holds memberships in the American Society for Engineering Education and the Council of Engineering and Scientific Society Executives.
He is a frequent contributor to the national diversity engineering dialogue and author of several commentary pieces, and he has been quoted in numerous articles in publications such as Forbes, The Wall Street Journal, U.S. News & World Report, and The Hechinger Report.

Showcase of Opportunities for Undergraduate Research and Creative Endeavor (SOURCE)
2021-10-06 17:00 - 20:00 (America/New_York) | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Calling all Huskies! Learn more about what cutting-edge research and creative endeavor look like at Northeastern. This is your chance to talk one-on-one with faculty from across the colleges about their research – and how you can get involved in projects during your time at Northeastern. Not everyone will have open positions right now but you’ll get a chance to see the range of work that’s happening and begin to make connections that you can build for the rest of your time at Northeastern.
Before you attend, here’s some advice to consider.

Take a look and see who’ll be there. We have an online database of attendees. Go through it and learn more about the project areas and visit the researcher/creative practitioner web pages. This will help prepare you for a conversation and help you ask any questions you might have.
Get ready for a conversation from your end. Think about goals you have , as well as your current interests and skills and those that you want to develop. How does what you have read about the various projects align with what you know about yourself and your interests? Take a minute to practice a simple declarative sentence, “My name is ____________. I study ____________. I think that this part of your work ____________ is interesting because of this intellectual reason/moral imperative/grand impact ____________. I’d love to learn more about it because of this previous experience ____________ and these skills ____________ and my long-term interest in ____________. How I can get involved?” You might not know how to fill in all of the blanks right now (that’s why you’re in school) but see how close you can get. When you know who you are, what you value, and how you can contribute — and get some practice saying it out loud– being confident becomes easier.
Remember, not every faculty member will have open positions now — but a good impression lasts a long time. You can’t go wrong with being polite and courteous. Address faculty members as Professor until told otherwise (better to err on the side of formality).
Keep in mind your time! If you want to be involved in research or creative practice, a good thing to keep in mind is that faculty members will commit a lot of time to training and mentoring their undergraduates. They’re investing time, energy, and expertise in their mentees and want to know that you will make time for the projects, show up consistently, and ideally be with them for longer than a semester if possible. The learning curve of most projects is steep and it takes some time to get to the meatiest parts of the work. Be honest with yourself about the commitment you can make, be frank with your faculty mentors, and stick to your word. Communication and honesty in relationships, including the mentoring relationship, is key.

SOURCE is a collaboration between Bouvé College of Health Sciences; College of Arts, Media and Design; College of Engineering; College of Science; College of Social Sciences and Humanities; D’Amore-McKim School of Business; and Khoury College of Computer Science. It is coordinated by Undergraduate Research and Fellowships on behalf of the Office of the Chancellor.

Getting Started with RefWorks
2021-10-07 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn how to use RefWorks to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.

Getting Started with Zotero
2021-10-12 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn how to use Zotero to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.

Launch of ALLIED Project
2021-10-12 14:30 - 15:30 (America/New_York)
The ALLIED (Allies for Leading, Learning, Inclusion, and Education of Disabilities) Project at Northeastern University is working to open discussions and raise awareness about disabilities on campus. This ALLIED program is taking the first steps towards connecting disability services and planting the seed for future disability programming.
In-person launch happening in 655 ISEC (Interdisciplinary Science & Engineering Complex).
You can also join us on Zoom: https://northeastern.zoom.us/j/98915783606

The Evolution of Healthcare Emergency Preparedness and Response in the Context of COVID-19
2021-10-12 17:00 - 18:00 (America/New_York) | Raytheon Amphitheater (240 Egan), 360 Huntington Ave, 240 Egan, Boston, MA, 02115, United States
The Vinod Sahney Distinguished Lecture Series on Health Systems Innovation welcomes Paul Biddinger, Chief Preparedness and Continuity Officer at Mass General Brigham, to Northeastern University, as he presents his research on “The Evolution of Healthcare Emergency Preparedness and Response in the Context of COVID-19.” Dr. Biddinger is an active researcher in the field of emergency preparedness and has lectured nationally and internationally on topics of preparedness and disaster medicine. He has authored numerous articles and book chapters on multiple topics related to disaster medicine and emergency medical operations and has responded to numerous prior disaster events, including Hurricane Katrina, Superstorm Sandy, the Boston Marathon bombings, the Nepal earthquakes, and many others.

Experiential Learning at Northeastern Seattle
2021-10-12 18:00 - 19:00 (America/Los_Angeles)
On October 12, Northeastern in Seattle will be hosting a virtual session about the ways that our graduate students gain real-world experience throughout their academic programs, from short-term projects to internships and co-ops.
Patrick Chidsey, associate director, career development and experiential learning, will be in conversation with Stephanie Curtiss, assistant director of student recruitment and enrollment. An open Q&A will provide attendees the chance to ask questions of the Seattle staff.
Chidsey earned a master’s degree in education focusing on college student services administration from Oregon State University and a bachelor’s degree in history from Western Washington University. He has spent his entire career working in higher education and career services. Chidsey supports Northeastern students in all aspects of career development, while also engaging employers to hire students into co-ops, internships, and sponsored XN projects.

Getting Started with BibTeX
2021-10-13 12:00 - 12:45 (America/New_York)
Start your fall 2021 research off on the right foot with Northeastern University Library’s series of online workshops and webinars!
In this webinar, learn how to use BibTeX to manage citations for yourself or your research group.
Register here: bit.ly/citationmgmtworkshops
All times are in Eastern Time.
