Northeastern University College of Engineering

Jinkun Zhang PhD Proposal Review
2023-08-11 14:00 - 15:00 (America/New_York)
Location: ISEC305
Title: Low-latency forwarding, caching and computation placement in data-centric networks
Committee Members:
Prof. Edmund Yeh (Advisor)
Prof. Stratis Ioannidis
Prof. Kaushik Chowdhury
Abstract:
With the exponential growth of data- and computation-intensive network applications, such as real-time augmented reality/virtual reality rendering and large-scale language model training, traditional cloud computing frameworks exhibit inherent limitations. These limitations include significant round-trip delays caused by backhaul network capacity bottlenecks and exorbitant costs associated with centralized computing power, e.g., training GPT-4 requires over 16,000 A100 GPUs.
To address these challenges, dispersed computing has emerged as a promising next-generation networking paradigm. By enabling geographically distributed nodes with heterogeneous computation capabilities to collaborate, dispersed computing overcomes the bottlenecks of traditional cloud computing and facilitates in-network computation tasks, including the training of large models.
Furthermore, in data-centric networking, communication and computation are resolved around data names instead of host addresses.
The deployment of network caches, by enabling data reuse, offers substantial benefits for data-centric networks.
For instance, consider a scenario where multiple machine learning applications seek to train different models simultaneously. These application could (partially) share data samples and intermediate results, and carefully designed data-reusing mechanisms become necessary. Optimal caching of data or intermediate results can significantly reduce the overall training cost, compared to each application independently gathering and transmitting data.
To efficiently manage computation and storage resources in heterogeneous data-centric networks, several frameworks have been proposed with different design objectives, such as optimizing throughput or incorporating multicast flows. However, previous approaches have failed to minimize average user delay despite the latency sensitivity of numerous real-world applications.
This proposal aims to address this gap by introducing a low-latency framework that jointly optimizes packet forwarding, storage deployment, and computation placement. The proposed framework effectively supports data-intensive and latency-sensitive computation applications in data-centric networks with heterogeneous communication, storage, and computation capabilities.
Specifically, to minimize user latency in congestible networks, we model delays caused by link transmissions and CPU computations using
traffic-dependent nonlinear functions. We formulate the joint forwarding, caching, and computation problem as an NP-hard mixed-integer non-submodular optimization, for which no constant-factor approximation algorithms are currently known. To make progress, we approach the joint problem by dividing it into two subproblems: the joint forwarding/computation problem and the joint forwarding/caching problem. Despite the non-convexity of the former subproblem, we provide a set of sufficient optimality conditions that lead to a distributed algorithm with polynomial-time convergence to the global optimum. For the latter subproblem, we demonstrate its NP-hardness and non-submodularity, even after continuous relaxation. We show that the objective function is a sum of a convex function and a geodesic convex function, and propose a set of conditions that provide a finite bound from the optimum. To the best of our knowledge, our method represents the first analytical progress in addressing the joint caching and forwarding problem with arbitrary topology and non-linear costs. Furthermore, our theoretical bound leads to a constant-factor approximation under additional assumptions.
As future work, we propose to develop a novel in-network large model training framework, building upon the aforementioned method.
Due to the substantial model size and extensive data samples required for training, centralized model storing and training are nearly infeasible for small and intermediate service providers.
Consequently, we will adopt horizontal model partitioning and distribute different model layers across the network nodes through caching.
Data samples or batches are input into the network and undergo the forward-backward procedure for training. Our objective is to jointly optimize data forwarding and model/computation placement, thereby minimizing the total cost of transmission, computation, and storage.
Furthermore, we introduce several network resource allocation optimization problems related to data-centric networking, thereby expanding the scope of our proposal.

Sumegha Singhania MS Thesis Defense
2023-08-15 15:30 - 16:30
Title: Exploring Log of RGB Space as a Better Input for Computer Vision Tasks
Committee Members:
Prof. Bruce Maxwell (Advisor)
Prof. Hanumant Singh
Prof. David Rosen
Prof. Mahdi Imani
Abstract:
There are specific, physics-based rules that govern the interaction of light and matter. Though studied extensively in the greater computer vision community, these rules are largely broken by common image processing techniques like JPEG compression and sRGB conversion. While the reliability and usability of color and intensity found in RAW images might better train networks to successfully complete vision-based tasks, these smaller, more heavily-processed formats have become the standard input for training sets. As a result, many of the images used to train neural networks do not retain the inherent structure that would enable neural networks to learn more general rules that exist in the natural world.
We hypothesize that using linear RGB or log RGB images, which preserve the physics of reflection, can simplify the learning process for certain vision tasks, enhance overall robustness and performance, and provide invariance to visual variations that exist in real-world vision applications. Our research demonstrates that employing linear and log RGB images to train deep networks for the task of object detection improves their performance when using the same network architecture and the same set of training images. Additionally, we also show that the networks trained on linear and log RGB show greater resilience to variations in intensity and color balance. Specifically, the network trained on linear and log RGB inputs shows invariance to intensity and color balance variations that were not encountered during training, while the network trained on the same images in sRGB JPEG format experiences significant performance degradation. To understand the reasons behind this disparity, we analyze and visualize low-level features in log RGB, linear RGB, and JPEG data. Our findings reveal that the log space preserves certain relevant features across variations in intensity and color balance.

Jagatpreet Nir PhD Proposal
2023-08-17 09:00 - 11:00
Title: Low Contrast Visual Sensing and Inertial Navigation in GPS Denied Environments
Committee Members:
Prof. Hanumant Singh
Prof. Martin Ludvigsen
Prof. Pau Closas
Prof. Michael Everrett
Abstract:
Visual inertial navigation has shown remarkable performance in publicly available datasets, assuming certain ideal conditions such as textured scenes, uniform illumination, and static environments. However, real-world scenarios often violate these assumptions, resulting in significant visual degradation. Consequently, the classical visual navigation pipelines fail and produce erroneous results, rendering these systems ineffective for demanding field robotic missions.
This research aims to enhance the robustness of visual-inertial systems in visually degraded situations, taking a comprehensive approach from both systems and algorithm perspectives. The work encompasses two primary objectives. Firstly, it focuses on refining the characterization of MEMS-based inertial sensors and their error propagation in position, while proposing improved dead-reckoning algorithms. Secondly, it explores the performance limits of visual navigation under moderate to extreme visual degradation and investigates novel algorithms that leverage deep learning methods to bolster the visual navigation engine. To validate the efficacy of these advancements, new datasets comprising drone and underwater robot scenarios are utilized, demonstrating the applicability of this work in field robotic applications.
By addressing the limitations of existing visual-inertial navigation systems and developing robust algorithms, this research aims to significantly enhance the reliability and performance of such systems in visually degraded environments, thus expanding their potential for real-world applications in demanding field robotic missions.

Rohit Rajput MS Thesis Defense
2023-08-17 10:30 - 11:00
Title:Towards Autonomous Multi-Modal Mobility Morphobot (M4) Robot: Traversability Estimation and 3D Path Planning
Location: ISEC 632 & Zoom
Committee Members:
Prof. Rifat Siphai
Prof. Hanumant Singh
Prof. Alireza Ramezani (advisor)
Abstract:
This thesis enhances the autonomy of the M4 (Multi-Modal Mobility Morphobot) robot, designed for Mars and rescue missions. The research enables the robot to autonomously select its locomotion mode and path in complex terrains. Focusing on walking and flying modes, a Gazebo simulation and custom perception-navigations pipelines are developed. Leveraging deep learning, the robot determines optimal mode transitions based on a 2.5D map. Additionally, an energy-efficient path planner is implemented and validated in simulations. The contributions demonstrate scalability for future mode integrations. The M4 robot showcases intelligent mode switching, efficient navigation, and reduced energy consumption, bringing us closer to fully autonomous multi-modal robots for exploration and rescue missions. This work paves the way for future advancements in autonomous robotics, with the ultimate vision of deploying the M4 robot for exploration and rescue tasks, making a significant impact in the quest for intelligent and versatile robotic systems.

Zhiyong Zhang PhD Proposal
2023-08-17 13:00 - 14:00
Title: Towards Indoor Mapping and Navigation with Perceptual Aliasing using Visual Semantic SLAM
Committee Members:
Prof. Hanumant Singh (Advisor)
Prof. Huaizu Jiang
Prof. David Rosen
Abstract:
Modern SLAM (Simultaneous Localization And Mapping) techniques allow us to create accurate 3D maps of the environment primarily using visual sensors in GPS-denied regions. In this context, numerous deep learning-based approaches have emerged, enabling the extraction of rich semantic information from images, including shapes, objects, and text.
Leveraging these technologies, our aim is to construct comprehensive 3D maps of indoor environments, which could be utilized by robots for path planning and navigation. Additionally, the solution can be integrated with a large language model, enabling the robot to interact intuitively with people.
This research comprises four main components: Semantic Feature Extraction and Tracking with SLAM: Given that the same semantic features can appear in multiple frames, some of which may not be conducive to feature detection and recognition (such as blurry images or distant views), we are developing a pipeline to ensure the optimal detection and recognition of semantic features within the most suitable frame. The pipeline also involves tracking the same feature across frames while maintaining its 3D location in the global map.
Resolving Perceptual Aliasing: Many indoor places can exhibit high visual similarity, which confuses the robot when powered up with a prior map in its memory. Semantic features can be used to localize the robot in the map, determining its specific floor or room. This capability can also aid SLAM in performing loop closure with high-level information.
Cross-Floor Constraints for SLAM Optimization: Most buildings contain a symmetric layout across floors, which can be exploited to establish constraints between them. For instance, vertically aligned rooms like 425 and 525, as well as elevators, offer opportunities for vertical constraint. Such constraints can enhance SLAM optimization, resulting in improved map accuracy.
Indoor Path Planning and Navigation: Once we have a comprehensive 3D map of the indoor environment, path planning becomes an intuitive way to utilize this map. With semantic features integrated into the map, the robot can associate 3D point clouds with high-level information, such as door numbers or office names. Large language models are available to provide a more human-like way to interact with the robot. For example, a command like “Navigate to Professor Hanumant’s office and locate the book ‘The Hitchhiker’s Guide to the Galaxy'” can be executed by the robot.

Jaehyeon Ryu PhD Dissertation Defense
2023-08-18 10:00 - 11:00
Title: Materials Strategies for Scaling Soft Neuroelectrode Arrays
Location: Snell 012/Teams
Committee Members:
Prof. Hui Fang (Advisor)
Prof. Yongmin Liu
Prof. Ryan Koppes
Abstract:
The evolution of electronics to seamlessly interface with biological tissue hinges on addressing multifaceted material constraints spanning electrochemical, electrical, and mechanical domains. Conventional bioelectronic interfaces, while endowed with established electrochemical functionality, remain hampered by rigidity that contradicts the pliability of surrounding tissue. While conductive materials exhibiting tissue-like softness and stretchability have been realized, their potential for electrochemical probing of tissue is impeded by strain-induced performance degradation and an ill-suited integration with the irregular tissue interface. Nevertheless, a significant challenge in ultrasoft bioelectronics pertains to scalability for achieving cellular resolution, primarily due to mechanical disparities between conventional microelectronic materials and soft elastomer substrates. In this thesis, by using a novel approach involving a multifunctional nanomesh, composed of distinct purposefully designed layers including polymer for mechanical buffering, metal for electrical conduction, and low impedance coating for electrochemical interfacing in the same nanomeshed structure, the resultant microelectrodes, scalable down to 20μm at cellular resolution, exhibit comparable performance to rigid devices alongside a stretchablity of approximately 50%, with potential for future enhancement through in-plane structural optimizations. In addition, we introduce a high-density neuroelectronic array featuring 256 filamentary neuroelectrodes on a flexible substrate. These electrodes are integrated with a single-transistor multiplexing acquisition circuit, effectively reducing noise and footprint while potentially extending device lifetime. Remarkably, the array’s rollable contact pad design allows for minimally invasive delivery through a syringe. Experimental validation demonstrates the array’s capability to record neural signals with high tone decoding accuracy. Utilizing high-density arrays of these microelectrode arrays, this unique frame works holds significant promise for advancing the field of neural interfacing, enabling a wide range of application from fundamental neuroscience studies to various biomedical applications.

Enabling Engineering Summer Showcase
2023-08-18 11:00 - 14:00 | 002 Ell Hall, 360 Huntington Ave, Boston, MA, 02115, United States
We invite you to the Enabling Engineering Summer Showcase on Friday – August 18th, 11:00am – 2:00pm EST in 002 Ell Hall (360 Huntingtin Ave, 002 Ell Hall, Boston Massachusetts 02115) where students will present their final design projects. We will have our clients present including the director of nurses from Mass Brigham and the Mass Brigham Press.
NU Enabling Engineering works to build devices for individuals with disabilities in Massachusetts and around the world. We maintain relationships with special education schools, community organizations, and individuals, bring projects ideas to campus, and then give students all the resources they need including funding, lab space, equipment, and management and technical support. There’s also a technical elective that students can take for credit to complete projects. Over the past 10 years, more than 1,000 students from across the university have worked on >75 projects.
The overall goal is to train the next generation of engineers, clinicians, and all students to be more knowledgeable about, and aware of, the needs of individuals with disabilities.

Haoling Li MS Thesis Defense
2023-08-18 14:00 - 15:00
Title: Ultracompact and Conformal Magnetodielectric Antennas
Committee Members:
Prof. Nian-Xiang Sun (Advisor)
Prof. Xufeng Zhang
Prof. Marvin Onabajo
Abstract:
Novel approaches are needed for improving antenna performance, enhancing efficiency, and reducing the size, profile, number, and signature of antennas. Efficient conformal antennas are increasingly replacing traditional antennas across platforms such as ships, aircraft, and human interfaces. Magnetodielectric antennas made with high-hesistivity magnetic materials are getting more and more attention. Defined as the maximum magnetic conductivity, hesitivity is directly related to the radiation efficiency of magnetodielectric antennas, with a higher hesitivity corresponding to higher attainable efficiency. In this study, new ultra-compact conformal magnetodielectric antennas are demonstrated, employing commercially available ferrite ceramic substrates. Through rigorous simulation and fabrication, a comprehensive comparison of our magnetodielectric antennas with reference monopole antennas demonstrated superior efficiency, enhanced gain, bandwidth, and a substantial reduction in antenna size compared to monopole antennas. State-of-the-art hesitivity as high as 6×10^6 Ω/m has been reported in CoZrNb alloy films, with an expectation of further 10× improvement in thin carrier substrates. This study forecasts the potential development of new magnetic materials with higher hesitivity, leading to further advancements in magnetodielectric antennas with enhanced radiation efficiency and ground plane immunity.

Xu Yizhe MS Thesis Defense
2023-08-18 14:30 - 15:30 | 532 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
Title:
Integration of Polyimide Flexible PCB Wings in Northeastern’s Aerobat
Location:
Room: ISEC 532, Teams link
Committee Members:
Prof. Alireza Ramezani(Advisor)
Prof. Rifat Sipahi
Abstract:
The principal aim of this Master’s thesis is to propel the optimization of the membrane wing structure of the Northeastern Aerobat through origami techniques and enhancing its capacity for secure hovering within confined spaces. Bio-inspired drones offer distinctive capabilities that pave the way for innovative applications, encompassing wildlife monitoring, precision agriculture, search and rescue operations, as well as the augmentation of residential safety. The evolved noise-reduction mechanisms of birds and insects prove advantageous for drones utilized in tasks like surveillance and wildlife observation, ensuring operation devoid of disturbances. Traditional flying drones equipped with rotary or fixed wings encounter notable constraints when navigating narrow pathways. While rotary and fixed-wing systems are conventionally harnessed for surveillance and reconnaissance, the integration of onboard sensor suites within micro aerial vehicles (MAVs) has garnered interest in vigilantly monitoring hazardous scenarios in residential settings. Notwithstanding the agility and commendable fault tolerance exhibited by systems such as quadrotors in demanding conditions, their inflexible body structures impede collision tolerance, necessitating operational spaces free of collisions. Recent years have witnessed an upsurge in integrating soft and pliable materials into the design of such systems; however, the pursuit of aerodynamic efficiency curtails the utilization of excessively flexible materials for rotor blades or propellers. This thesis introduces a guard design incorporating feedback-driven stabilizers, enabling stable hovering flights within Northeastern’s Robotics-Inspired Study and Experimentation (RISE) cage.

Julian Gutierrez PhD Proposal Review
2023-08-25 10:00 - 11:00
Title: Towards Real-Time Safe Flight Paths for Urban Air Mobility
Committee Members:
Prof. David Kaeli, (Advisor)
Prof. Pau Closas
Dr. Evan Dill (NASA)
Dr. Natasha Neogi (NASA)
Abstract:
The emergence and development of advanced technologies and vehicle types have created a growing demand for introducing new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with the challenge of finding methods to integrate these emerging operations without significant additional risk to pedestrians and infrastructure. Predictive and autonomous risk mitigation capabilities become critical to meet this challenge. However, urban environments experience effects that are computationally expensive to model, limiting conventional aviation concepts, policy, and risk prediction tools from being effectively translated into this space. With the emergence of High-Performance Computing (HPC) ecosystems in the last two decades, we can use these software and hardware capabilities to help bridge the gap between real-time predictive responses and modeling accuracy.
In this dissertation we first present a simulation framework to estimate the quality of Global Navigation Satellite System (GNSS) performance for autonomous aircraft in urban environments. We propose a new algorithm designed for HPC to accelerate modeling the characteristic effects of dense urban canyons on GNSS, allowing the extension of established GNSS integrity techniques into urban navigation. Additionally, we provide a thorough validation of the simulator, which proves high-accuracy modeling when compared to sensors in the real world. Second, we use this simulation framework as the input into a new 4D path-planning algorithm based on an adaptation of the Bellman-Ford algorithm. HPC techniques are employed to accelerate the algorithm to produce flight paths that minimize exposure to GNSS risks. We evaluate the computational cost of satellite availability fluctuations by prioritizing events when satellite availability changes as triggers for these updates.

Mostafa Abedi PhD Proposal Review
2023-09-01 13:00 - 14:00 | 532 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
Title: Power-Efficient and Security-Enhancing Techniques for Ultra-low Power IoT Devices
Committee Members:
Prof. Aatmesh Shrivastava (Advisor)
Prof. Marvin Onabajo
Prof. Nian X. Sun
Abstract:
Internet-of-things (IoT) devices often rely on ambient energy sources such as photovoltaic (PV) cells and thermoelectric generators (TEGs) for their operation. Minimizing power loss through ambient energy harvesting optimization can significantly extend the battery life or support battery-free sensor nodes in IoT devices. A maximum power point tracking (MPPT) circuit is often used for impedance matching to maximize energy transfer efficiency. This research proposes an ultra-low power, high-tracking efficiency MPPT circuit based on Hill-Climbing (HC) algorithm suitable for micro-power DC harvesters. The proposed system employs a modified version of the hill-climbing algorithm. In case of input power changes and consequent deviation of the harvester from the MPP, an integrated Power Change Detector (PCD) is proposed to reactivate the MPPT circuit. The PCD detects changes in input power and activates the MPPT circuit, enabling automatic activation and resulting in substantial power savings. Furthermore, due to the proposed power estimation technique, the MPPT is not dependent on the internal structure of the energy source, and its tracking efficiency is unrelated to the conversion ratio of the converter. This approach enables us to achieve a peak tracking efficiency of over 99.9%. To adjust the input power of the harvester to track the maximum power point, we propose a new, efficient Pulse Width Modulation (PWM) circuit. This circuit exhibits a wide duty cycle range, low power consumption, linearity, and robustness against variations.
This research also focuses on increasing the security of IoT devices. In the past, chip fabrication was mostly done internally by semiconductor firms. Now, it is more collaborative, pulling in designs from various sources and having a few factories produce them. This new way of working means that companies that only handle design might face more challenges like the threat of hardware Trojans (HT) being added either during the design phase or production. With that in mind, we introduce a different circuit design approach. We aim to find these Trojans, particularly the newer analog Trojans. The idea is to boost the security of IoT devices by detecting these issues early. In addition, to improve the security of IoT systems, we propose an ultra-low power energy monitoring system (EMS) to detect and mitigate denial-of-sleep (DoSL) attacks. In this project, we explore a new method of defense against DoSL attacks by monitoring energy consumption. We will implement a low-power system to monitor the lifetime of the IoT node by continuously evaluating the harvested, stored, and consumed energy in the node.

NOBCChE 50th Annual Conference
2023-09-11 - 2023-09-14
Join the College of Engineering’s Chemical Engineering department at the NOBCChE’s Annual Conference! Graduate Admissions will be in attendance to answer all your questions about our graduate Chemical Engineering programs during the Exhibit Fair on September 14th.

CommLab Writing Group
2023-09-11 14:00 - 16:00
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).
COE graduate students are invited to 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 in 306 Egan for 2 hours; you do not have to attend all the sessions or participate for the full 2 hours. (Note we will be in 336 CSC on 9/18 and we will not meet on Monday, Nov 6).

Poster Design and Editing: A CommLab Workshop Series
2023-09-11 15:00 - 16:30 | 344 CSC, 360 Huntington Ave, Boston, MA, 02115, United States
COE Graduate students are invited to learn techniques, develop, edit and practice delivering your poster. Join the CommLab’s weekly workshop to improve your poster design and communication skills. Drop in for as many workshops as you want to get your poster ready. You can also join any time between 3:00-4:30pm ET. This is a hybrid opportunity. Join us on Zoom or in 344 Curry Student Center. We will be in room 435 on Monday 9/11 and 9/30. We will meet virtually only on Monday, 11/6.

College of Engineering Global Co-op Info Session
2023-09-12 17:30 - 18:30 | 168 SN, 360 Huntington Ave, Boston, MA, 02115, United States
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Spring/ Summer I 2024! Topics discussed will include:

Search techniques and global positions in your field
Locations that students have co-oped in the past
What to consider when interested in a global co-op
Information on logistics, including visas and housing
Tips and resources for self-developing global positions

Attendance to one of these information sessions is required if you plan to do a global co-op in Spring/ Summer I 2024. 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.

Bioengineering Fall Seminar Series
2023-09-13 12:00 - 13:00
Join the Department of Bioengineering for our Fall Seminar Series, where we host scholars from outside institutions to come to campus and give a seminar on their research.
Every Wednesday, 12-1pm in Shillman Hall 335, unless otherwise stated. Schedule below.
September 13th:

Speaker: Associate Professor Nikolai Slavov
Institution: Northeastern Department of Bioengineering

September 20th:

Speaker: Associate Professor Erel Levine
Institution: Northeastern Department of Bioengineering

September 22nd (*Friday 12-1pm, in SH 305*)

Speaker: Assistant Professor Abbas Yaseen
Institution: Northeastern Department of Bioengineering

September 27th:

Speaker: Marisol Herrera-Perez, PhD
Institution: University of Rochester
Research Focus: Cellular self organization

October 4th:

Speaker: Michele Marcolongo, PhD
Institution: Villanova University
Research Focus: Biomimetic proteoglycans

October 11th:

Speaker: Keith Dunker, PhD
Institution: Indiana University
Research Focus: Intrinsically disordered proteins

October 18th:

Speaker: Tyrone Hayes, PhD
Institution: University of California, Berkeley
Research Focus: Endocrine disruption

October 25th:

Speaker: Lauren Black III, PhD
Institution: Tufts University
Research Focus: Cardiovascular tissue engineering, tissue mechanics

November 1st:

Speaker: Junjie Zhang, PhD
Institution: University of Texas A&M
Research Focus: Computational bioengineering, structural biology modeling

November 8th:

None

November 15th:

Speaker: Ritu Raman, PhD
Institution: Massachusetts Institute of Technology
Research Focus: Adaptive biological actuators

November 22nd:

Thanksgiving Break

November 29th:

Speaker: Debora Marks, PhD
Institution: Harvard University
Research Focus: Computational and systems biology

December 6th:

Speaker: Srivallesha (Valli) Mallidi, PhD
Institution: Tufts University
Research Focus: Photoacoustic imaging

December 13th:

Speaker: Kristin Koutmou, PhD
Institution: University of Michigan
Research Focus: Chemical modification to mRNA

Small Talk for Networking: A CommLab Workshop Series
2023-09-13 13:00 - 14:00
Looking to improve your conversational skills and effortlessly connect with others? This workshop series will equip you with the essential tools, techniques, and practice to connect with others, whether you are attending networking events, social gatherings, or simply looking to strike up conversations with new acquaintances. Join us for these fun-filled sessions where we’ll explore icebreakers, conversation starters, and strategies to keep the dialogue flowing naturally. Don’t miss out on this opportunity to boost your confidence and unlock new connections. This is a hybrid workshop series, Please register and join us on Wednesdays on Zoom from 1-2 pm ET, or join us in person in room 306 Egan, except on Wednesday, September 20, when we will be in 335 Curry Student Center.

NSF GRFP Fellowship Writing Group
2023-09-13 15:00 - 16:00
The CommLab and the Khoury College Graduate Program run a 6-week fall writing group for graduate students applying for the NSF Graduate Research Fellowship Program (GRFP). The virtual Zoom meetings begin Wednesday, September 13 at 3 pm ET. Find out more in the NSF GRFP Fellowships Teams group and RSVP here.

LinkedIn, CV, Resume: A CommLab Workshop Series
2023-09-13 17:00 - 18:00
Join our empowering LinkedIn, CV, Resume Workshop series any Wednesday from 5 pm to 6 pm ET. This collaborative space offers valuable tips and peer feedback to enhance your online profile and professional presence. Whether you’re a student or seasoned professional, our community will help you optimize your LinkedIn profile, CV, and resume to stand out in today’s job market. Don’t miss this chance to learn, grow, and build a strong network together! This is a virtual workshop series, you can drop in any time between 5-6pm and any week. Join us virtually on Zoom.

COE Student Club Fair
2023-09-13 18:30 - 20:30 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Learn more about the 50+ COE-affiliated student groups and ways you can get involved.
Location: Curry Student Center Indoor Quad

GEM Annual Board Meeting & Conference
2023-09-14 - 2023-09-16
Join COE Graduate Admissions at the GEM Annual Board Meeting & Conference. Meet us at the Graduate Resource Fair on September 15th to ask your questions about Graduate Engineering programs at Northeastern!

S-STEM Scholars Conference
2023-09-14 - 2023-09-16
Join COE Graduate Admissions at the S-STEM Scholars Conference. We will be at the Career & Education fairs on September 14 & 15 to answer your questions about graduate engineering programs at Northeastern.

Selecting a Major Panel for COE GE1000 Undergraduate Students
2023-09-14 18:30 - 20:30 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Hear from upper-class students about why they chose their major, co-op placements they have completed, and co-curricular activities they’ve participated in related to their major.
Location: Curry Student Center Ballroom

FacDev Fridays: Preparing for Success - Understanding the Pre-Award Process
2023-09-15 13:00 - 14:00
Register for this event

Archimedes Health Care Security Week
2023-09-18 - 2023-09-21
Archimedes is excited to bring members and guests together in a safe space to learn, share and network with the best of the best in health care and medical device security. You can choose to attend one of our two training events led by expert speakers (choose only one) September 18 and 19, and then attend the familiar and highly regarded Archimedes 101 Workshop on September 20-21. Or attendees can choose to solely attend one of the training sessions, or choose to attend only the Archimedes 101 event…the choice is yours!
Two-Day Training Options
September 18-19
Attendees have the opportunity to register for ONE of two training options lead by industry experts.
Archimedes 101 Workshop* $1495
September 20-21
The 2023 Archimedes 101 Conference, hosted by Northeastern University’s Archimedes Center for Health Care and Medical Device Cybersecurity, is a two-day educational workshop for healthcare providers, medical device manufacturers and industry regulators to learn and speak frankly about medical device security threats and solutions.

Why Attend?
Our events do not focus on the latest industry buzz or trendy new product development. We want you to feel comfortable speaking freely about your cyber security issues with trusted and respected professionals who can help you establish best practices for improving medical device security. At Archimedes, we provide a secure forum for you to learn about emerging cyber security issues and then we arm you with the knowledge to better protect both your patients and clients.
Attendees from our previous conferences have included:

Chief information security officers
Directors of product engineering
System engineers
VPs of global product security
IT security managers
Physicians
Chairs of medical device security standards bodies
Security researchers
Front-line engineers from clinical facilities

If you have additional questions, please contact us at archimedes@northeastern.edu
Register

Technical Exchange Program between NU and DFG Delegation
2023-09-18 08:30 - 15:00
8:30-8:50 am: Lab tour of the NU Cleanroom, labs, etc. (Meet at the entrance of Egan Building, 120 Forsyth Street, Boston, MA 02115, Led by Nian Sun)
8:50-9am Move to McLeod Suites, Curry Student Center, Northeastern University
9:00-9:15: Opening remarks from NU and DFG (VPRD Kim Holloway, Senator Professor Marion Merklein)
9:15-10:30: Presentations from NU (9 speakers with 8 minutes each)

Ravinder Dahiya, Electrical and Computer Engineering
Matteo Rinaldi, Electrical and Computer Engineering
Yongmin Liu, Electrical and Computer Engineering, Mechanical and Industrial Engineering
Xufeng Zhang, Electrical and Computer Engineering
Ben Davaji, Electrical and Computer Engineering
Swastik Kar, Physics Department
Paul Stevenson, Physics Department
Ruobing Bai, Mechanical and Industrial Engineering
Hongli Zhu, Mechanical and Industrial Engineering

10:30-10:45: Coffee break
10:45-11:45: Presentations from NU and DFG Delegation (7 speakers with 8 minutes each)

Srinivas Tadigadapa, Electrical and Computer Engineering
Srirupa Chakraborty, Chemical Engineering
Nian Sun, Electrical and Computer Engineering
Arne Berger, University of Applied Sciences Anhalt
Robert Böhm, Leipzig University of Applied Sciences
Alexander Prange, University of Applied Sciences Niederrhein
Jessica Friess, University of Applied Sciences Niederrhein

12-1:30pm: Lunch break (working lunch at McLeod Suites)
1:30-2:30pm: Presentations from DFG Delegation (7 speakers with 8 minutes each)

Margit Geißler Bonn-Rhein-Seig University of Applied Sciences
Jens Helbig, Nürnberg Tech
Benjamin Neding, University of Applied Sciences Lübeck
Jörn V. Wochnowski University of Applied Sciences Lübeck
Romana Piat, University of Applied Sciences Darmstadt
Holger Saage, Univ. of Applied Sciences Landshut, Competence Center for Lightweight Design
Julian Tornow, Hochschule Ruhr-West University of Applied Sciences

2:30-3pm: DFG / NU discussions on potential collaborations, programs, etc.

Zhengnan Li PhD Proposal
2023-09-19 10:00 - 11:30 | 432 ISEC, 360 Huntington Ave, Boston, MA, 02115, United States
Title:
Multi-user Communications
Date:
9/19/2023
Time:
10:00:00 AM
Location:
ISEC 432
Committee Members:
Prof. Milica Stojanovic (Advisor)
Dr. Xiaowen Wang (Apple)
Prof. Tommaso Melodia
Abstract:
Extensive research has been conducted with respect to underwater acoustic communications and networking, owing to their profound importance in various applications, such as fish farming and the oil-and-gas industry. Acoustic networks involve scenarios where multiple users necessitate transmitting data to a central base station. Techniques such as time-division or code-division multiple access are commonly employed in such networks. However, these techniques entail a trade-off: each user’s transmission rate remains confined to a fraction of the overall available resources. Consequently, the endeavor to accommodate an increased number of users within the usable resources results in a diminished data rate for each user. Conversely, if the goal is to maintain a consistent per-user data rate, the acquisition of additional bandwidth becomes imperative. Yet, the feasibility of this approach is challenged by the inherent limitations of available bandwidth in underwater acoustic systems.
In this proposal, I will present preliminary findings that involve the utilization of code and space division multiple access systems in conjunction with orthogonal frequency division multiplexing (OFDM), which is a key enabler for the current and future generations of wireless systems. Additionally, the proposal delves into the prospect of establishing an underwater acoustic channel repository—an effort designed to emulate underwater acoustic channels, thereby alleviating the necessity for extensive real-world underwater experimentation. This proposal also includes several recent long-distance underwater experiments carried out in Japan, examining various ideas regarding the frequency offset compensation problem in OFDM systems. Furthermore, beyond the outcomes in underwater acoustic communication, this proposal encompasses a series of explorations involving micro electromechanical systems (MEMS) and the utilization of terahertz frequencies.

Challenging Conversations: A CommLab Workshop Series
2023-09-19 17:00 - 18:00
Join our weekly virtual workshop, “Challenging Conversations,” every Tuesday from 5:00 PM to 6:00 PM. This community of practice helps you build the skill of navigating difficult discussions with peers and individuals of varying authority. Learn practical strategies, engage in role-playing exercises, and connect with like-minded peers to enhance your communication abilities. Register to join us on Zoom now to confidently handle challenging conversations in any context.

University of Miami Graduate School Fair
2023-09-20
COE Graduate Admissions is excited to meet students at the University of Miami’s Graduate School Fair! Join us to learn about our graduate engineering programs and Northeastern’s newest campus in Miami!

Engineering Department Showcases for Undergraduate Students
2023-09-20 12:00 - 13:00 | Curry Student Center, 360 Huntington Ave., Boston, MA, 02115, United States
Connect with department faculty and learn more about the academic opportunities associated with the various COE departments.
Location: Curry Student Center Ballroom
