Northeastern University College of Engineering

Md Navid Akbar's PhD Dissertation Defense
2022-12-06 16:00 - 17:30 (America/New_York)
“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

The "Finals Cookie" with Dean Abowd
2022-12-06 20:30 - 22:00
Please join us for a relaxing evening before finals begin. We’ll provide hot chocolate and LOTS of cookies.
Hosted by the College of Engineering
Tuesday December 6th from 8:30 to 10:00 pm
The Tents at Robinson Quad

How green hydrogen is made
2022-12-07 12:00 - 13:00 | 236 Richards, 360 Huntington Ave, Boston, MA, 02115, United States
ChE Seminar Series Presents:
Marc T.M. Koper
Leiden Institute of Chemistry
Leiden University, Leiden, The Netherlands
Abstract:
The electrocatalytic production of hydrogen through water splitting is a necessary approach for storing (excess) renewable electricity as chemical energy in fuels, and for making green hydrogen as a building block for the chemical industry. Here, I will discuss recent advances and challenges in the mechanistic understanding of electrochemical H2 formation. Specifically, I will show that H2O activation is influenced by an intricate interplay between surface structure (both on the nano- and on the mesoscale), electrolyte effects (pH, ion effects) and mass transport conditions. This complex interplay is currently still far from being completely understood.
Bio:
Marc Koper is Professor of Surface Chemistry and Catalysis at Leiden University, The Netherlands. He received his PhD degree (1994) from Utrecht University (The Netherlands) with a thesis on nonlinear dynamics and oscillations in electrochemistry. He was an EU Marie Curie postdoctoral fellow at the University of Ulm (Germany) and a Fellow of Royal Netherlands Academy of Arts and Sciences (KNAW) at Eindhoven University of Technology, before moving to Leiden University in 2005. His research in Leiden focuses on fundamental aspects of electrocatalysis, theoretical and computational electrochemistry, and electrochemical surface science, in relation to renewable energy and chemistry. He has received various national and international awards, among which the Spinoza Prize of the Netherlands Organization for Scientific Research (2021), Allen J. Bard Award for Electrochemical Science of The Electrochemical Society (2020), the Netherlands Catalysis and Chemistry Award (2019), and the Faraday Medal (2017) from the Royal Society of Chemistry. He is currently President of the International Society of Electrochemistry.

12/7 IER Seminar Series: Steve Dorton - "Trust Dynamics with AI in High-Consequence Work Systems"
2022-12-07 13:00 - 14:00 | 532 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
Trust Dynamics with AI in High-Consequence Work Systems
Wednesday, 12/7/2022 from 1 – 2 pm
ISEC 532 & Zoom
Zoom: https://northeastern.zoom.us/j/96750528112?pwd=[REDACTED]
Steve Dorton
Principal Scientist for Sensemaking, Decision Making, and AI
The MITRE Corporation
Abstract:
Artificial Intelligence (AI) is often viewed as the means by which intelligence analysts will cope with the ever-increasing deluge of data from various sources. The best AI is moot, however, if analysts cannot trust the outputs of the AI to inform high-consequence decision making. A naturalistic study was performed to understand how intelligence professionals gain and lose trust in AI “in the wild.” The study assessed various trust factors proposed in the literature and identified various themes from interviews with intelligence professionals. We will discuss how to apply these findings to engineer more trustworthy AI for high-consequence decision applications.
Bio:
Steve Dorton is a Principal Scientist for Sensemaking, Decision Making, and AI at the MITRE Corporation. His research generally falls at the intersection of the social and computational sciences, focusing on how intelligent systems can help and harm human cognition in national security contexts. He also holds an adjunct lecturer appointment in the University of Maryland School of Public Policy, where he teaches social, ethical, and policy considerations for AI and big data.

Forge Fall Showcase
2022-12-07 18:30 - 20:30 | 010 Hayden Hall, 010 Hayden Hall, 360 Huntington Ave, Boston, MA, 02115, United States
Come to Forge’s Fall Showcase to learn all about the amazing work that our Product Lab teams have completed this semester.
Forge a student-led initiative of the Sherman Center to help students learn about product development and entrepreneurship through hands-on project experience and tailored workshops.
As a part of Forge, students solve problems in our community by developing solutions that make a lasting impact and develop skills through an engaging workshop and speaker series.
This semester, our Product Lab teams have completed amazing projects all centered around the theme of musical exploration, while learning transferrable skills within the field of entrepreneurial engineering.
We look forward to seeing everyone there!

Danlin Jia's PhD Dissertation Defense
2022-12-08 11:00 - 12:00
“Towards Performance and Cost-efficiency for Data-intensive Applications in Distributed Data Processing Systems”
Abstract:
Data-intensive science (DIS) has experienced a significant boom in the past decade. The emerging technologies of data-intensive services and infrastructures contribute to DIS’s development and raise challenges. An ecosystem has been constructed considering performance, scalability, sustainability, and reliability to provide a high-quality service to DIS applications. The ecosystem consists of services exposed to users for application deployment and infrastructures to support data storage, transfer, and management from the system’s perspective. DIS applications share typical features, such as memory and I/O intensity. Thus, addressing the bottlenecks triggered by memory-intensive or I/O-intensive workloads in services and infrastructures is essential to improve the performance and cost-efficiency of the whole ecosystem. In this dissertation, we investigate the characteristics of various DIS applications and design new resource allocation and scheduling schemes for the services and infrastructures in the DIS ecosystem.
We first investigate memory optimization in DIS ecosystems. In-memory data analytic frameworks are proposed to cache critical intermediate data in memory instead of in storage drives. Apache Spark is a commonly adopted in-memory data analytic framework with two memory managers, Static and Unified. However, the static memory manager lacks flexibility. In contrast, the unified memory manager puts heavy pressure on the garbage collection of the Java Virtual Machine on which Spark resides. To address these issues, we propose a new learning-based bidirectional usage-bounded memory allocation scheme to support dynamic memory allocation considering both memory demands and latency introduced by garbage collection. Distributed data-processing workloads in container-based virtualization take advantage of resource sharing, fast delivery, and excellent portability of containerization but also suffer from resource competition and performance interference. This inevitably induces performance degradation and significantly long latency, even worse when over-provisioning. Motivated by this problem, we design an efficient memory allocation scheme (RITA) for containerized parallel systems to improve data processing latency. RITA monitors applications’ memory usage and cache characteristics and dynamically re-allocates memory resources.
We also propose I/O optimizations for DIS applications and infrastructures. Distributed Deep Learning (DDL) accelerates DNN training by distributing training workloads across multiple computation accelerators, e.g., GPUs. Although a surge of research has been devoted to optimizing DDL training, the impact of data loading on GPU usage and training performance has been relatively under-explored. When multiple DDL applications are deployed, the lack of a practical and efficient technique for data-loader allocation incurs GPU idleness and degrades the training throughput. In this dissertation, we thus investigate the impact of data-loading on the global training throughput and design a resource allocator that uses the data-loading rate as a knob to reduce the GPU idleness. Finally, designs and optimizations on disaggregated storage systems supported by cutting-edge storage and network techniques emerge dramatically. Disaggregated storage systems can scale resources independently and provide high-quality services for hyper-scale architectures. The traditional congestion control mechanism relieves congestion by limiting the data-sending rate of senders. However, such a design scarifies the storage drive’s performance as data are generated but stalled on storage host nodes if network congestion happens. To solve this issue, we design a storage-side rate control mechanism to mitigate network congestion while avoiding sacrificing I/O performance.
Committee:
Prof. Ningfang Mi (Advisor)
Prof. Xue Lin
Prof. David Kaeli

Chuangtang Wang's PhD Proposal Review
2022-12-08 14:00 - 16:00 | 138 ISEC, 360 Huntington Ave, 138 ISEC, Boston, MA, 02115, United States
“All-optical Control of Magnetization in Nanostructures”
Committee:
Prof. Yongmin Liu (Advisor)
Prof. Don Heiman
Prof. Nian X. Sun
Abstract:
The switching of magnetization by a femtosecond laser within several picoseconds has recently gained substantial attention, because it promises next-generation, energy-efficient, and high-rate data storage technology. One of the most intriguing demonstrations is the helicity-dependent switching (HD-AOS) of a ferromagnet, in which the magnetization states can be deterministically written and erased using left- and right-circularly polarized light. However, the challenge is to realize a single-pulse HD-AOS. Controlling the spin angular momentum transfer from light to magnetic materials in nanostructures is the key to advance this field.
In my thesis research work, I will study the all-optical control of magnetization in different nanostructures, aiming to better understand the underlying mechanisms of HD-AOD and accelerate the technology development. Firstly, helicity-driven magnetization dynamics in heavy metal/ferromagnet Au(Pt)/Co bilayer by the optical spin transfer torque (OSTT) is experimentally explored. The wavelength-dependent measurement of OSTT reveals that the quantum efficiency of OSTT strongly depends on the interface electronic structure and pump energy. The Inverse Faraday effect (IFE), which is believed to be the driving mechanism of HD-AOS, is subsequently investigated in an Au thin film. The dependence of IFE on photon energy implies that the orbital angular momentum contribution to IFE is dominated by the excitation of laser pulses. To the best of our knowledge, it is the first demonstration of this phenomenon. Lastly, I will discuss our recent results on plasmonics-enhanced all-optical control of magnetization. Light can be tightly confined in plasmonic structures, which can potentially enable low-energy and high-density magnetic data storage.

The Quantum Age: From Bell Pairs to Quantum Computers
2022-12-08 16:00 - 17:00 | 168 SN, 360 Huntington Ave, Boston, MA, 02115, United States
Nobel Physics Colloquium 12.8 @4pm
Every year, the Physics Department celebrates the Nobel Prize in Physics by inviting a renowned expert in the field of the awardees to introduce the ideas and advances that lead to their nomination. This year, we are fortunate to host Prof. Vladan Vuletić, from MIT, and expert in quantum optics and emergent quantum technologies such as quantum computers.
Speaker: Prof. Vladan Vuletić, MIT
Title: The Quantum Age: From Bell Pairs to Quantum Computers
Abstract: Quantum mechanics has not one but two mysteries: the double-slit experiment and quantum correlations (entanglement) between two or more particles. Criticized by Einstein as “spooky action at a distance”, entanglement is now seen as an essential part of the physical world, in part thanks to the recipients of the 2022 Nobel Prize. The Bell inequalities, introduced in 1964 to experimentally distinguish local hidden variable theories from quantum physics, have been confirmed to agree with quantum mechanics in the Nobel-Prize winning and many other experiments.
Building on entangled Bell pairs, the last few years have seen a remarkable development in our ability to control many neutral atoms individually, and induce controlled interactions between them on demand. This progress ushers in a new era where one can create highly entangled states of many particles, break certain limits for quantum sensors, or study quantum phase transitions. I will present results on quantum sensing enhanced by entanglement, and on quantum simulation with atomic arrays containing more than 250 atoms. Finally, I will discuss prospects for near- and medium-term neutral-atom quantum computers with full quantum error correction.
Bio: Professor V. Vuletić earned the Physics Diploma with highest honors from the Ludwig-Maximilians-Universität München, and in 1997, a Ph.D. in Physics (summa cum laude) from the same institution. While a postdoctoral researcher with the Max-Planck Institute for Quantum Optics in Garching, Germany, Professor Vuletić accepted a Lynen Fellowship at Stanford University in 1997. In 2000, he was appointed an Assistant Professor in the Department of Physics at Stanford and in June 2003 accepted an Assistant Professorship in Physics at MIT. He was promoted to Associate Professor in July 2004. He was promoted to Full Professor in July 2011.
Research Interests include laser cooling and trapping, quantum physics, quantum entanglement, quantum optics, quantum information processing. The idea of the research of the Vuletić group is to develop new methods to manipulate many-body states in a regime where the quantum mechanical aspects dominate their behavior and their properties. On the one hand, this should lead to new tools that allow one to probe physical laws and to measure fundamental constants with increasing precision. On the other hand, the progress of experimental methods also drives the advances in our understanding of the ever mysterious, beautiful, accurate, yet deeply dissatisfying structure of quantum mechanics. This interplay between theoretical concepts and experimental realizations promises to be very fertile in fields such as quantum control, quantum feedback and its limits, many-particle quantum systems, and many-particle entanglement (quantum computing). We use various methods, but most include laser-cooled atoms (to be able to keep atoms localized, and attain long coherence time) and laser-light interaction to manipulate the atoms, the photons, or both, at the quantum level. Using internal states of atoms in combination with laser light, which has essentially zero entropy, allows us to reduce thermal noise without having to cool the atoms to very low (sub-microkelvin) temperatures.
Prof. Vuletić was awarded by Lester Wolfe Career Development Chair in 2003, Alfred P. Sloan Research Fellowship in 2003-2004, and APS Fellowship “for pioneering advances across AMO physics, including quantum information and precision measurement with atomic ensembles, cavity QED, atomic collisions and Casimir forces for atom condensates near surfaces” in 2012. He is one of the founders of QuEra Computing, a Boston-based company developing quantum computers based on neutral Rydberg atoms.
168 Snell Engineering Center or Zoom

Summer 1, 2023 Panama DOC: International Applications of Fluid Mechanics – Info Session
2022-12-08 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 Thursday, December 8th 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.

Bin Sun's PhD Dissertation Defense
2022-12-09 11:00 - 13:00
“Factorization guided Lightweight Neural Networks for Visual Analysis”
Committee:
Prof. Yun Fu (Advisor)
Prof. Ming Shao
Prof. Lili Su
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.
We also tried to factorize the features for single image super resolution (SISR). Factorization on features will reduce the feature size in order to reduce the computation costs. However, the reduction of the spatial size is counter-intuitive for the super resolution task. With our exploration, we demonstrated a network named Hybrid Pixel-Unshuffled Network (HPUN), which factorized the features to achieve the lightweight purpose while keeping high performance. Specifically, we utilized pixel-unshuffle operation to factorize the input features. After the factorization, we improved the performance by the grouped convolution, max-pooling, and self-residual. The experiments on popular benchmarks showed that the factorization strategy could achieve SOTA performance on SISR.

Alexey Tazin's PhD Dissertation Defense
2022-12-09 12:00 - 13:30
“Composition of UML Class Diagrams Using Category Theory and External Constraints”
Abstract:
In large software development projects there is always a need for refactoring and optimization of the design. Usually software designs are represented using UML diagrams (e.g class diagrams). A software engineering team may create multiple versions of class diagrams satisfying some external constraints. In some cases, subdiagrams of the developed diagrams can be selected and combined into one diagram. It is difficult to perform this task manually since manual process is very time consuming, is prone to human errors, and is not manageable for large projects. In this dissertation we present an algorithmic support for automating the generation of composed diagrams, where the composed diagram satisfies a given collection of external constraints and is optimal with respect to a given objective function. The composition of diagrams is based on the colimit operation from category theory. The developed approach was verified experimentally by generating random external constraints (expressed in SPARQL and OWL), generating random class diagrams using these external constraints, generating composed diagrams that satisfy these external constraints, and computing class diagram metrics for each composed diagram.
Committee:
Prof. Mieczyslaw Kokar (Advisor)
Prof. David Kaeli
Dr. Jeff Smith

Daniel Uvaydov's PhD Proposal Review
2022-12-15 09:00 - 11:00 | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
“Real-Time Spectrum Sensing for Inference and Control”

Abstract:
Spectrum sensing can enable the next generation of wireless applications ranging from opportunistic spectrum access to cognitive radio networks. The key unaddressed challenges of spectrum sensing are that (i) it has to be performed with extremely low latency over varying bandwidths and must guarantee strict real-time processing constraints; (ii) its underlying algorithms need to be extremely accurate, and flexible enough to work with different wireless bands and protocols to find application in real-world settings. We address these challenges in multiple wireless applications by utilizing Deep Learning techniques as the main vehicle of spectrum sensing for both inference and control. By leveraging mechanisms such as data augmentation, channel attention, voting, and segmentation we are able to push beyond the capabilities of existing Deep Learning techniques and create generalizable spectrum sensing algorithms. Furthermore we deploy different spectrum sensing solutions in real testbeds for over the air evaluations and applicable proof-of-concepts.

Committee:

Prof. Tommaso Melodia (Advisor)
Prof. Francesco Restuccia
Prof. Kaushik Chowdhury

COE FacDev Friday: Award Compliance 101
2022-12-16 13:00 - 14:00

Ali Al Qaraghuli's PhD Proposal Review
2022-12-16 14:00 - 15:00 | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
“Terahertz Communication for Space Systems”
Abstract:
With the ultimate vision of ubiquitous egalitarian worldwide coverage driven by the rapid proliferation of high-speed satellite networks, private companies are launching satellites into orbit at unprecedented rates. The main goal of such networks enabled by dense constellations in space is to build a more robust telecommunications infrastructure and provide worldwide internet access to users on Earth. Similarly, small satellites are included in the vision of non-terrestrial networks (NTN) for 6G networks which promise for more connectivity on Earth. The significant projected traffic in the orbital uplink, downlink, and crosslink communication will demand more spectrum to suit more users and satisfy the need for higher data rates. Similarly, the push towards using smaller satellites in the form of CubeSats will require the hardware to be more compact than ever. This introduces the terahertz band (0.1-10THz) as a candidate technology to satisfy both large bandwidth and device compactness requirements due to the smaller wavelength of terahertz signals. These two advantages, however, come at the cost of high propagation losses and impose the use of very high-gain directional antennas, leading to limitations in constellation network design. This proposal evaluates terahertz communication in space in contrast to competitor technologies such as microwaves and free-space optical communication, and establishes the feasibility of terahertz networks in space. Next, the areas of research and innovation required to realize terahertz space communication systems are identified and explored. Finally, advancements in those areas are presented, and the next steps are identified to transform terahertz space communication systems into reality.

Committee:
Prof. Josep Jornet (advisor)
Prof. Tommaso Melodia
Prof. Kaushik Chowdhury

Library Webinar: Python and Text Analysis for Absolute Beginners
2023-01-05 13:00 - 15:00
Pondering Python? Tantalized by text analysis? Wondering how Jupyter notebooks work? Read on!
In this hands-on session, attendees will learn some basic Python while working in Jupyter notebooks, an interactive web tool for running and writing about code. Next, we’ll use Python and Jupyter to run a simple text analysis on a custom dataset built with Constellate, a text mining platform for building and analyzing textual datasets from sources such as JSTOR, Portico, Chronicling America, and Reveal Digital. We will close by discussing opportunities to further expand attendees’ coding and text analysis skills after the session.
No prior experience with Python, JSTOR, or Jupyter is necessary, and no programming skills are needed or assumed for this session.
Register at the Northeastern University Library events calendar.
Please note:

This session will not be recorded. If you’re interested in learning the material but don’t plan to attend, please don’t register for the session as seats are limited. We welcome you to access and work through our workshop materials available via this link.

This event is co-sponsored by the NULab for Texts, Maps, and Networks (CSSH) and Research Data Services (Northeastern University Library). Please contact Jen Ferguson with any questions.

Summer 1, 2023 Panama DOC: International Applications of Fluid Mechanics – Info Session
2023-01-10 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, January 10th 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.

Yukui Luo's PhD Proposal Review
2023-01-11 10:00 - 12:00
“Securing FPGA as a Shared Cloud-Computing Resource: Threats and Mitigations”
Abstract:
With the widespread adoption of cloud computing, the demand for programmable hardware acceleration devices, such as field-programmable gate array (FPGA), has increased. To further improve the performance of FPGA-enabled cloud computing, one promising technology is to virtualize the hardware resources of an FPGA device, which allows multiple users to share the same FPGA. This solution can provide on-demand instances at the FPGA resource and time levels, significantly improving the utilization and energy efficiency of the FPGA devices. However, due to the hardware reconfigurability of FPGA, current virtualization methods for multi-tenant GPU and TPU instances are incompatible with multi-tenant FPGA virtualization.We define the threat model for multi-tenant FPGA and discuss the security issues related to Confidentiality, Data Integrity, and Availability. Based on an analysis of potential attacks, we present our latest research results and propose two future research directions for mitigations: (1) a multi-tenant FPGA plug-to-play obfuscation module and (2) a hardware-software co-designed multi-tenant FPGA virtualization system, which includes a hypervisor and a smart multi-tenant FPGA platform.

Committee:

Prof. Xiaolin Xu (Advisor)
Prof. Yunsi Fei
Prof. Xue Lin

NSF TIP Presentation
2023-01-12 13:30 - 15:00 | ISEC Auditorium, 805 Columbus Ave, Boston, MA, 02115, United States
You are invited to a special presentation by Dr. Erwin Gianchandani, Assistant Director of the newly-formed Directorate for Technology, Innovation and Partnerships (TIP) within the U.S. National Science Foundation, focused on the TIP vision and upcoming opportunities with the new directorate. The presentation (with plenty of time for Q&A) is set to take place on Thursday, January 12th from 1.30-3PM at Northeastern’s Boston Campus, in the Auditorium of the Interdisciplinary Science and Engineering Complex (ISEC), 805 Columbus Ave.
Following the session, the community will have an opportunity to sign up for office hours with Dr. Becky Shearman, Program Director for TIP.
Visit tip2023.sites.northeastern.edu to RSVP for the presentation and sign up for the office hour slots.
****Please share this invitation broadly with other interested parties (this event is open to the entire Boston area) and encourage them to a) RSVP for the presentation and b) sign up for one of the office hour slots with our TIP visitors. Now that TIP is an official entity at NSF and has a direct budget, there will be plenty of opportunities to discuss specific programs or ideas with them directly.

COE Global Co-op Information Session
2023-01-12 17:30 - 18:30
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Summer II/ Fall 2023. Topics discussed will include:

Search techniques and global positions in your field
What to consider when interested in a global co-op
Information on logistics, including health and safety
Tips and resources for self-developing global positions
Student perspective from previous global co-op participants

Location: Shillman 305
Attendance to one of these sessions is required if you plan to do a global co-op in Summer II/ Fall 2023. Please reach out to Sally Conant, Global Co-op Coordinator, s.conant@northeastern.edu or Kristina Kutsukos, Global Co-op Coordinator, k.kutsukos@northeastern.edu for additional information.

COE FacDev Friday: Award Compliance 101
2023-01-13 13:00 - 14:00
Concur got you frustrated? Is that charge allowable? Attend the Compliance seminar hosted by the COE Post Award team to learn all about research compliance and your portfolio. Nothing says research without compliance!
RSVP

Alpha Kappa Psi Spring 2023 Rush
2023-01-14 - 2023-01-22
Open to all Majors! Come rush the oldest and largest co-ed professional business fraternity. Our next event is an Info Session and Resume Workshop on Monday, January 16th 8-10pm at 104 West Village G. Check out our Instagram @akpsi_neu for more details!

Leadership Development Workshop
2023-01-15 18:00 - 20:00 | 431 Stearns, 431 Stearns Center, 360 Huntington Ave, Boston, MA, 02115, United States
Earn The Gordon Undergraduate Leadership Development Workshop Certificate
This engineering leadership workshop is designed for Northeastern University undergraduate engineering students during their second co-op experience. Workshop sessions are hosted during the spring and summer semesters and are designed to be completed in parallel with co-op.
The program includes a series of engineering leadership development activities focused on expanding leadership skills, engaging in more meaningful interactions with their supervisors, and taking active roles in shaping their overall co-op experiences.
The primary objective of the workshop is to enhance the value of Northeastern’s world-renowned cooperative education (co-op) program for Northeastern undergraduate engineering students. The workshop offers a supplementary curriculum that makes engineering leadership advancement a focus of the co-op experience.
Register

COE Global Co-op Information Session!
2023-01-18 17:30 - 18:30 | 108 SN
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Summer II/ Fall 2023. Topics discussed will include:

Search techniques and global positions in your field
What to consider when interested in a global co-op
Information on logistics, including health and safety
Tips and resources for self-developing global positions
Student perspective from previous global co-op participants

Location: Snell Engineering 108
Attendance to one of these sessions is required if you plan to do a global co-op in Summer II/ Fall 2023. Please reach out to Sally Conant, Global Co-op Coordinator, s.conant@northeastern.edu or Kristina Kutsukos, Global Co-op Coordinator, k.kutsukos@northeastern.edu for additional information.

Engineering Leadership Professional Development Co-op Workshop
2023-01-18 18:00 - 20:00 | 431 Stearns, 431 Stearns Center, 360 Huntington Ave, Boston, MA, 02115, United States
Earn The Gordon Undergraduate Leadership Development Workshop Certificate
This engineering leadership workshop is designed for Northeastern University undergraduate engineering students during their second co-op experience. This workshop begins January 18th and is designed to be completed in parallel with your co-op.
The program includes a series of engineering leadership development activities focused on expanding leadership skills, engaging in more meaningful interactions with their supervisors, and taking active roles in shaping their overall co-op experiences.
This is a 0-credit hour class that includes two evening sessions, mentoring, and four self-directed modules. Workshop participants will significantly improve their co-op experience and maximize their professional development.
Upon completion, students give a final presentation and earn The Gordon Undergraduate Leadership Development Workshop Certificate. This certificate shows as an achievement student’s transcript.
Students may register for the workshop via the Northeastern Studenthub. To register for this workshop, students should select search for ENLR 3121, CRN 34906. This course is zero credit hours and is being offered for free. Space is limited, register now to reserve your seat.
If you have questions regarding the registration process, please contact Ben Rutledge, Recruitment Specialist, at b.rutledge@northeastern.edu

CommLab Writing Group
2023-01-19 09:30 - 11:30
Join us weekly in the Curry Student Center, room 435.
Setting and sticking to a consistent writing schedule is key to improving skills and accomplishing your writing tasks (don’t just take our word for it ?).
Join the CommLab writing group to share best practices, get feedback from your peers, and work on any writing project (dissertation, thesis, manuscript, fellowship, poster, presentation, or other forms of technical communications). We will meet weekly for 2 hours, you do not have to attend all the sessions or the full 2 hours to participate. Each session will begin with a tip on best practices and goals for the session (5 minutes) followed by quiet writing time (115 minutes).

Adaptable Communication for Leading, Teaching and Mentoring
2023-01-19 16:30 - 17:30 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Location: Curry Student Center 435

Who is your audience, what do you want to say, and what do they want to hear? Many graduate students serve in roles of leadership, teaching and mentoring. This free workshop will give graduate students the tools they need to be an effective leader, teacher and mentor. We will practice using these tools by role playing common challenging situations designed to improve your adaptable communication skills.

RSVP

COE FacDev Friday: Establishing and Managing Your Team (Lab Group or Other)
2023-01-20 13:00 - 14:00
Building a vibrant, inclusive team (lab group or other) is not easy. Please join this panel conversation with COE faculty, led by CHE Professor Rebecca Carrier, to hear best practices and your colleagues’ experiences.
RSVP

January Webinar Week
2023-01-24 08:00 - 2023-01-26 17:00
Join Enrollment Management for their monthly webinar series for prospective students. Topics will include domestic and international application and enrollment success sessions. These sessions will be run by Northeastern’s team of Enrollment Coaches and Northeastern’s global team.
These sessions are open to students interested in any Northeastern University graduate program.
Register for the series to receive the schedule of events.

COE Global Co-op Information Session!
2023-01-24 18:00 - 19:00
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Summer II/ Fall 2023. Topics discussed will include:

Search techniques and global positions in your field
What to consider when interested in a global co-op
Information on logistics, including health and safety
Tips and resources for self-developing global positions
Student perspective from previous global co-op participants

Location: Virtual
Attendance to one of these sessions is required if you plan to do a global co-op in Summer II/ Fall 2023. Please reach out to Sally Conant, Global Co-op Coordinator, s.conant@northeastern.edu or Kristina Kutsukos, Global Co-op Coordinator, k.kutsukos@northeastern.edu for additional information.
COE Global Co-op Information Session!
Join Zoom Meeting
Meeting ID: 920 5193 0716
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