The Graduate School Collaborative Webinar: Why consider Graduate School?
2023-12-06 19:30 - 21:00 (America/New_York) | MA
Think graduate school is just for future faculty? Think again!
Join us as we demystify what it takes to be and become a graduate student (MS and PhD), as well as the many career avenues that you can take with a graduate school degree. Come learn about the following topics from some of the top Engineering Graduate Programs in the country!

What is graduate school
What to expect
Why consider graduate school
How to prepare
Thinking ahead to the application process

What: Seminar on “Why consider Graduate School?”
When: Wednesday December 6th, 2023; 7:30 – 8:30 p.m. Eastern Time
For Who: Undergraduate Freshman, Sophomore, and Juniors
Sponsored by: UC Berkeley, Georgia Tech, John’s Hopkins university, University of Michigan, Northeastern, NYU, Ohio State, University of Oklahoma, Purdue University, Rice University, University of Southern California
Where: Zoom – Register using the Link below
Questions about accessing the webinar? Contact Nina Parshall at parshall.8@osu.edu

Note: There will be breakout sessions with each school for 30mins following the presentation (8:30pm – 9:00pm Eastern). Register to join for some exclusive networking!

Mauro Belgiovine PhD Proposal Review
2023-12-07 10:00 - 11:00 | MA
Title: Wireless Intelligence: A Comprehensive Exploration of AI-Driven Solutions in Channel Estimation, Beam Refinement, and Protocol Classification for Next Generation Networks
Committee Members:
Prof. Kaushik Chowdhury (advisor)
Prof. Stratis Ioannidis
Dr. Chris Dick
Abstract:
his thesis explores the transformative impact of artificial intelligence (AI) on wireless systems through model-driven simulations and real-world datasets, with a focus on enhancing both local and cellular wireless networks through the deployment of highly customized deep learning solutions that target specific bottlenecks affecting traditional signal processing based communication.
The research delves into three key areas that address critical challenges in the current wireless landscape. The first focal point of the investigation involves channel estimation using deep learning techniques to denoise pilots and expedite the accurate estimation of Channel State Information (CSI). By leveraging deep learning methodologies, the proposed solution aims to enhance the reliability and computation for MIMO and massive MIMO channel estimation, thereby contributing to improved communication efficiency and reduced errors. The second major topic encompasses the application of reinforcement learning for 5G New Radio (NR) millimeter-wave (mmWave) beam refinement. The study aims to develop a Deep Reinforcement Learning algorithm capable of adjusting beamsteering angles, starting from a coarse beam scanning procedure and further refining them for higher transmission efficiency. This innovation is expected to substantially decrease traffic overhead while simultaneously enhancing beam steering precision, thus optimizing the performance of mmWave communication. The third and final area of focus introduces a transformer-based WiFi multi-protocol classifier, strategically deployed on a DeepWave Air-T edge device, which is equipped with Module on Chip (MoC) low power CPU-GPU and programmable Software Defined Radio (SDR). This classifier outperforms existing modulation classification models and legacy methods under lower SNR conditions, leveraging TensorRT’s model compression capabilities to efficiently process extended sequences of raw IQ samples, ensuring high performance at a low computational cost. The proposed solution addresses the growing demand for efficient and adaptable wireless communication systems, paving the way for advancements in edge-based processing and intelligent protocol classification.
This work seeks to contribute significantly to the ongoing AI revolution in wireless systems by addressing crucial issues in channel estimation, beam refinement, and protocol classification. The outcomes of this research hold the potential to redefine the landscape of wireless communication, offering enhanced performance, reduced overhead, and increased adaptability in both local and cellular networks.

Yisi Liu MS Thesis Defense
2023-12-07 14:00 - 15:00 | MA
Title: Experimental research on the Nonlinear Magnetoelectric Effect of the VLF ME Antennas
Committee Members:
Prof. Nian Sun (Advisor)
Prof. Yongmin Liu
Prof. Xufeng Zhang
Abstract:
Magnetoelectric (ME) coupling effects in ferromagnetic and piezoelectric composites involve the control of electric polarization (P) by applying a magnetic field (H) (direct ME effect), or the manipulation of magnetization (M) through an electric field (E) (converse ME effect) . These effects are facilitated by the mechanical deformation in the ferroic phases resulting from the combination of magnetostriction and piezoelectricity. In single-phase materials, the breakthrough in achieving large ME coefficients has further advanced the development of ME materials and devices. Consequently, numerous multifunctional ME devices, such as mechanical antennas, magnetic sensors, tunable inductors, and filters, have been developed. This thesis has provides a summary and categorization of these devices based on their physical mechanism and type of ME effects. The inclusion of mechanical ME antennas based on piezoelectric/magnetostrictive heterostructures with acoustic actuation reflects the significant interest in this topic. Notably, a maximum communication distance of 120 m for a very low frequency (VLF) communication system has been achieved using a pair of mechanical ME antennas. Subsequently, we will focus on introducing and reviewing the materials and devices related to the ME effect, as well as the application of ME mechanical antennas in very low frequency (VLF) communication systems.
In addition to that, we developed a transmitter with a Metglas/PZT/Metglas structure antenna. Our study focuses on investigating the transmission effects of this antenna when employing direct antenna modulation techniques to enhance data transmission. Through our research, we have introduced a novel modulation method by modulating the antenna. We observed that this modulation method produces a more stable and stronger signal.

Ate Darabi PhD Proposal Review
2023-12-08 12:00 - 12:30 | MA
Title:
Complex Delayed Networks and Their Application in Epidemic Analysis: Modeling, Analysis, and Strategic Management
Committee Members:
Prof. Milad Siami (Advisor)
Prof. Bahram Shafai
Prof. Rozhin Hajian
Abstract:
In the face of crowd-related disasters like pandemics and mass attacks, the complex dynamics of human interactions demand comprehensive modeling approaches. This proposal adopts a network-based perspective, leveraging the delayed Susceptible-Infected-Susceptible (SIS) model for epidemics and the Predator-Swarm-Guide (PSG) model for crowd movement, to gain insights into the dynamics of these critical situations.
In epidemic networks, time delays and uncertainties can significantly change the epidemic behavior and result in successive echoing waves of the spread between various population clusters. We examine these effects on linear SIS dynamics, evaluating network stability and performance loss. We prove that network performance loss is correlated with the structure of the underlying graph, intrinsic time delays, epidemic characteristics, and external shocks. This performance measure is then used to develop an optimal traffic restriction algorithm for network performance enhancement, resulting in reduced infection in the metapopulation. An epidemic-based centrality index is also proposed to evaluate the impact of every subpopulation on network performance, and its asymptotic behavior is investigated. This index converges to local or eigenvector centralities under specific parameters. Moreover, given that epidemic-based centrality depends on the epidemic properties of the disease, it may yield distinct node rankings as the disease characteristics slowly change over time or as different types of infections spread. This unique characteristic of epidemic-based centrality enables it to adjust to various epidemic features. The derived centrality index is then adopted to improve the network robustness against external shocks on the epidemic network.
The PSG model addresses mass attack scenarios, considering individuals’ efforts to evade adversaries and seek guidance. Environmental factors like impermeable walls and psychological elements are incorporated into this model. The preliminary results highlight the role of coordinated cooperation in minimizing casualties. The objective is to reduce casualties through a hybrid motion optimization approach for individuals and the guiding agent.

Cookies with the Dean: Holiday Edition
2023-12-11 13:00 - 14:30 | The Tents at Robinson Quad, 336 Huntington Ave, Boston, MA, 02115, United States
Join Dean Gregory Abowd for a holiday-themed Cookies with the Dean on Monday, December 11th from 1:00-2:30pm in the Robinson Quad Tent near Curry Student Center.
We will have holiday cookies, hot cocoa, and free Swag available! Swing by for food, fun, and a chance to talk to the Dean.
We hope to see you there!
This is a 100% compostable event. Please place all waste into the marked composting bins for their disposal.

Durga Suresh PhD Proposal Review
2023-12-12 09:00 - 10:00 | MA
Title: Network Security Management and Threat Mitigation in the Open Cloud

Committee Members:
Prof. Miriam Leeser (Advisor)
Prof. Michael Zink
Prof. Xiaolin Xu
Abstract:
Cloud computing and advanced cyberinfrastructures are increasingly vital to the functioning of Internet systems. Every day, more devices are added to the cloud, to provide greater resource utilization, availability, and scalability. Due to the expanding reliance on cloud computing, securing the cloud is paramount. Tackling the issue of securing the cloud is crucial not only for preserving the functionality and reliability of cloud-based systems but also for protecting the critical data and services that depend on these platforms.
Cloud computing models include public clouds, private clouds, community clouds, and hybrid clouds. Private, community, and hybrid clouds provide security, but with an important trade-off; namely, user access restriction in the cloud. The proposed research uses the Open Cloud Testbed (OCT) which is part of the National Science Foundation’s (NSF) Computer and Information Systems Engineering(CISE) Community Research Infrastructure(CRI) program. OCT is an example of a public cloud that allows users two things: 1) an isolated set of nodes to perform experiments with bare metal access, which can potentially lead to security issues, and 2) the ability to test out the solutions for both using the cloud and adding security to it. The proposed research aims to target a system like the OCT, specifically targeting a public cloud environment.
This system will be designed to allow access to the switch, enabling control and management of traffic within the cloud network. This research aims to mitigate network security threats in the public cloud network. The aim of this research is multifold. First, we identify and classify the behavior of users in the cloud. We then provide an approach to creating a network security management policy that will deal with 1)detecting network intruders that scan the cloud network and remove their access to the network, and 2) managing heavy hitters that can cause Denial of Service (DOS) and Distributed Denial of Service (DDOS) attacks in the cloud network by using the heavy hitter detection system and prevent them from putting more traffic on the network. Both network intruder detection and heavy hitter management systems use Access Control Lists (ACL)as a means to prevent the user from putting traffic on the cloud network. Lastly, we perform experiments to handle these threats and measure the success of the experimental setup concerning network attacks. The proposed approach will ensure network security by creating a framework for network security management policy to minimize threats in the cloud network and other resources directly attached to the network. The proposed research aims to enhance cybersecurity by employing network intruder detection techniques to identify potential threats, implementing heavy hitter management to mitigate threats effectively, and developing and enforcing a network security management policy to prevent future threats.

Deepak Prabhala MS Thesis Defense
2023-12-12 11:00 - 17:00 | MA
Title: “Smart Microwave Devices with Programable Printed Circuit Board (PPCB): Design with Liquid Crystal Elastomer Polymers in Transmission Lines and Circulators”
Committee Members:
1) Professor Nian X. Sun (Advisor)
2) Professor Marvin Onabajo
3) Professor Yongmin Liu
Abstract:
This study explores the innovative application of liquid crystal elastomer (LCE) polymers in the design and implementation of microwave transmission lines and circulators. Liquid crystal elastomers, known for their unique combination of liquid crystalline and elastomeric properties, offer a unique approach to developing flexible and tunable microwave devices. The research focuses on a thorough study of the electro-mechanical properties of LCEs to achieve novel functionalities in the design of transmission lines and circulators for microwave communication systems in HFSS simulations. The first part of the study delves into the characterization of the dielectric and mechanical properties of the chosen LCE polymer. Subsequently, the design and fabrication of a flexible and tunable transmission line using LCE are discussed. The LCE-based transmission line aims to measure the insertion loss and return loss with different widths, lengths, and thicknesses of the LCE polymer. The study investigates the impact of temperature on the transmission line’s performance, offering insights into potential applications in reconfigurable microwave systems. The second phase of the research explores the utilization of LCE in the development of a microwave circulator, a vital component in microwave communication networks. The circulator design incorporates the unique properties of LCE by using a stepped dielectric variation approach for broadband isolation. This innovation holds promise for enhancing the efficiency and adaptability of microwave systems in communication and radar applications. The findings of this research contribute to offering a pathway for integrating liquid crystal elastomers into flexible and reconfigurable microwave devices. This thesis aims to advance the understanding of smart microwave devices and inspire further exploration into the application of liquid crystal elastomer polymers in cutting-edge technologies.

Night of yalda
2023-12-15 12:00 - 13:00 | MA
Honor the longest night of the year in this Persian cultural tradition to offer hope and light.
There will be watermelon, pomegranate, Persian food, and of course Persian music.
Not necessary, but we will be happy if you show up in red.
Location: 111 Snell Library

Xiang Zhang PhD Proposal Review
2023-12-20 14:00 - 15:00 | MA
Title:Confidentiality and Privacy Preserving: Intertwining Deep Learning and Side-channel Analysis
Meeting ID: 976 4324 8925 Passcode: [REDACTED]
Committee Members:
Prof. Yunsi Fei (Advisor)
Prof. Adam Ding
Prof. Lili Su
Abstract:
In the past decade, deep learning-empowered technologies have significantly permeated our daily lives, revolutionizing diverse application domains with superb performance. In hardware security, deep learning has been employed for power or electromagnetic side-channel analysis (SCA) and protection, and the security of deep learning implementations starts gaining traction.
This dissertation delves into the intertwining deep learning techniques and side-channel analysis. It addresses two critical questions: how to extend deep learning to other types of SCAs; what confidentiality and privacy vulnerabilities deep learning models have.
Our research work first explores deep learning-assisted cache side-channel attacks and introduces innovative countermeasures grounded in the principles of adversarial samples against deep learning. We first design a novel high-frequency cache monitor, which runs concurrent to the victim execution and collects run-time timing traces, while previous cache monitors are only able to collect timing samples. Such timing traces facilitate follow-on non-profiled Differential Deep Learning Analysis (DDLA) for secret retrieval. We also propose a novel countermeasure against the new DDLA, leveraging the concept of adversarial examples, which deliberately introduces obfuscation operations in the victim program so as to generate ‘adversarial’ timing traces and therefore circumvent the follow-on DDLA.
The second part of the dissertation addresses the vulnerability of deep neural network (DNN) implementations and presents novel methodologies for enhancing user privacy. It introduces a technique for extracting deep learning models through software-based power side channels. By manipulating model inputs and leveraging the on-chip Intel Running Average Power Limit (RAPL) sensors reporting, the entire model parameters can be extracted when the model inference is executed on modern processors. To protect both the model confidentiality and the input privacy, this dissertation proposes to obfuscate the model inputs while preserving the end-to-end functionality. It introduces an encoder to transform the inputs before feeding the DNN model, and appends a decoder after the model outputs to recover the intended results. The approach, compared to traditional encryption or masking techniques, is more efficient and can effectively protect both user privacy and model confidentiality.
The overall goal of the dissertation is to further investigate the power of deep learning in SCA and countermeasure and safeguard secure DNN implementations.

Computer Vision with Small Data (CV4Smalls): A Focus on Infants and Endangered Animals
2024-01-03 - 2024-01-07 | MA
Prof. Sarah Ostadabbas is the general chair of the inaugural workshop on Computer Vision with Small Data (CV4Smalls): A Focus on Infants and Endangered Animals. This workshop is hosted as part of the 2024 Winter Conference on Applications of Computer Vision (WACV) and promises to be a platform for groundbreaking research and insightful discussions. The workshop will take place in person between January 3-7, 2024 in Waikoloa, Hawaii, USA.
Researchers and practitioners are invited to submit original research papers, not exceeding 8 pages, adhering to the WACV template https://lnkd.in/efsp_8qx. Workshop papers will be included in IEEE Xplore, and will be indexed separately from the main conference papers. Submitted papers will undergo a rigorous peer-review double-blind process. For more information please contact: ostadabbas@ece.neu.edu
Important Dates:
• Paper Submission Deadline: 11th October, 2023
• Notification of Acceptance: 9th November, 2023
• Camera-Ready Deadline: 19th November, 2023
• Workshop Date: 3-7th January, 2024

Chemical Engineering Spring Seminar Series: Professor Hongfei Lin
2024-01-17 12:00 - 13:00 | 103 Churchill, 103 Churchill Hall, 360 Huntington Ave, Boston, MA, 02115, United States
Towards Holistic Approach for Decarbonizing Energy System
Decarbonizing the energy system is essential for mitigating climate change by replacing fossil fuels with alternative sources emitting significantly less carbon dioxide. Recognizing that no single alternative energy source can meet global demand, our approach involves utilizing multiple sources for a future carbon-neutral energy system. We focus on developing highly selective and efficient catalytic processes to convert diverse carbon feedstocks, including renewable and waste carbons. In this seminar, I will showcase our groundbreaking biphasic tandem catalytic processes, achieving exceptional carbon-atom efficiencies in converting renewable biomass into biofuels. Additionally, our innovative sequential catalytic process enables highly selective deconstruction of mixed waste plastics into valuable monomers and fuels. The presentation will also delve into the synergy of integrating direct air capture of CO2 for its utilization in producing value-added carbon-neutral products. Ultimately, our research aims to implement a holistic approach, decarbonizing the energy system, and establishing a sustainable supply of low-carbon intensity chemicals, materials, and fuels from renewable and waste carbon resources.

Dr. Hongfei Lin is a Professor at the Voiland School of Chemical Engineering and Bioengineering at Washington State University and Chief Scientist in the Energy and Environment Directorate at Pacific Northwest National Laboratory. He earned his B.E. and M.S. degrees from Tsinghua University, completed his Ph.D. in Chemical Engineering at Louisiana State University, and further honed his expertise as a postdoctoral fellow at the University of California, Santa Barbara. With nearly two decades of multidisciplinary research experience, Dr. Lin focuses on catalysis and sustainability, particularly in developing novel catalytic processes to derive value-added fuels and chemicals from renewable and waste carbon resources. His commitment to a sustainable, low-carbon, circular economy is evident through his numerous publications, multiple patents, and extensive support from entities such as DOE, NSF, and USDA. Dr. Lin actively contributes to the academic community, serving on the international advisory board of Energy Technology, the editorial board of Advanced Composites and Hybrid Materials, and previously as the Program Chair of the Energy and Fuels Division of the American Chemical Society.

BioE Faculty Search Seminar
2024-01-17 12:00 - 13:00 | MA
Join the Department of Bioengineering for weekly faculty seminars in 458 Richards Hall (unless otherwise stated).
1/17: Justin Randall, PhD
1/24: Jean-Baptiste Lugagne, PhD
1/31: Tianqi Song, PhD
2/7: Katheryn Rothenberg, PhD
2/14: Jae-Won Shin, PhD
2/21: Heidi Klumpe, PhD
Friday, 3/1, in International Village 019: Kolade Adebowale, PhD

LinkedIn, CV, Resume: A CommLab Workshop Series
2024-01-17 14:00 - 15:00 | 206 Egan, 360 Huntington Ave, Boston, MA, 02115, United States
Join our empowering LinkedIn, CV, and Resume Workshop series any Wednesday from 2 pm to 3 pm ET. This collaborative space offers valuable tips and peer feedback to enhance your online profile and professional presence. This is a community learning initiative, and together, we strive to make our profiles better. Join this hybrid workshop series either in person in room 206 Egan or through Zoom.

Mock Interview: A CommLab Workshop Series
2024-01-18 14:00 - 15:00 | 206 Egan, 360 Huntington Ave, Boston, MA, 02115, United States
Join the CommLab every Thursday from 2-3pm ET, we’ll delve into the intricacies of interviews, unveiling effective tricks and preparation strategies for any interview scenario. Engage in an interactive setting as we dissect the overall interview experience, discuss common interview scenarios, and share insights on what to do during critical moments. Join this hybrid workshop series either in person in room 206 Egan or through Zoom.

Northeastern NAI annual event
2024-01-18 17:00 - 19:00 | Raytheon Amphitheater (240 Egan), 360 Huntington Ave, 240 Egan, Boston, MA, 02115, United States
Join us for the Northeastern NAI annual meeting, a must-attend event for AI innovation enthusiasts! This in-person gathering will take place at the Egan Research Center, Forsyth Street, Boston, MA, USA. Get ready to hear from an AI expert in the field and an IP patent lawyer in a room filled with passionate individuals who share your love for innovation. This event is a unique opportunity to network, learn from industry experts, and explore groundbreaking ideas. Don’t miss out on this exciting event that promises to inspire and ignite your creativity. Mark your calendars and get ready for an unforgettable experience at the Northeastern NAI annual meeting.

Global Co-op Information Session
2024-01-18 17:30 - 18:30, 2024-01-24 17:30 - 18:30 | MA
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Summer II/ Fall 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 Summer II/ Fall 2024.
Location: Renaissance Park 909. Register on NUworks.
Please reach out to Kristina Hubbard, Global Co-op Coordinator, k.hubbard@northeastern.edu for additional information.

Towards Personalized Medicine in Speech Motor-Impaired Populations
2024-01-19 11:00 - 12:00 | MA
The Bouve College of Health Sciences cordially invites you to attend a presentation by SoCRS Faculty Candidate
Hannah Rowe, PhD, CCC-SLP
Towards Personalized Medicine in Speech Motor-Impaired Populations
Abstract: An estimated 130 million adults worldwide live with a speech motor disorder (i.e., difficulties with coordination, strength, and precision of the muscles involved in speech), which significantly impacts their quality of life. However, substantial heterogeneity across clinical populations and limited mechanistic understanding of speech motor control contribute to diagnostic challenges and a lack of targeted treatments. This job talk describes my long-term research goals to further the field of personalized medicine in speech motor-impaired populations, with a particular focus on individuals with neurodegenerative diseases and adults who stutter. I will talk about using behavioral, neurological, and physiological measures to develop clinical phenotypes for (1) informing diagnostic decision-making and (2) guiding individualized treatment. Towards my first research aim, I will highlight my dissertation work, which explores the efficacy of acoustic-based phenotypes for characterizing and classifying divergent neurodegenerative diseases. Towards my second research aim, I will highlight a project exploring the neural correlates of different disfluency types in adults who stutter, which served as pilot data for a recent grant submission on feedback- and feedforward-based phenotypes of stuttering. I will conclude by discussing future directions that support both aims of my research program.
Friday, January 19, 2024
11:00am-12:00pm
107 Robinson Hall

Graduate School of Engineering Campus Tour (In Person)
2024-01-20 10:00 - 11:00 | MA
Want to learn more about the Graduate School of Engineering on the Boston campus? Then we welcome you to sign up for a Graduate School of Engineering campus tour! Led by one of our expert Graduate Student Ambassadors, we’ll show you key locations on campus, in addition to resources specific to Engineering, and answer your questions about Boston. Please complete the registration form linked below to select the date and time that works best for you. Tours are open to both newly admitted and prospective students. We can’t wait to meet you!

CHE PhD Dissertation Defense: Jiaming Xu
2024-01-23 10:00 - 11:00 | MA
PhD Dissertation Defense: Molecular simulations of confined deep eutectic solvents for gas separations and liposomes for drug delivery
Location: ISEC 332 & Microsoft Teams
Abstract: This dissertation leverages molecular dynamics simulations to explore the properties of nanoscale materials and interfaces involving gases, liquids and solids, traversing the realms of environmental and biological science. This work not only demonstrates the expansive applicability of MD simulations across various scientific disciplines but also highlights their capability to provide profound insights into diverse scientific phenomena. In the segment dedicated to deep eutectic solvents, our study investigates the behavior of ethaline (mixtures of choline chloride with ethylene glycol at different molar ratios) confined in graphite and titania (rutile) slit pores, measuring 2 nm and 5 nm in width. This research aims to address the high viscosity issue prevalent in these solvents when saturated with CO2. The results reveal that modifications in the ethylene glycol ratio, variations in pore sizes, and the choice of pore wall materials significantly affect the efficiency of CO2/CH4 separation. These findings offer a deeper understanding of how molecular interactions and structural changes in confined spaces can influence the physical properties of DES.
The dissertation also delves into the domain of liposomes (nanoparticles formed by a lipid bilayer encapsulating an aqueous core), examining the influence of lipid composition and the integration of two distinct small-molecule hydrophobic drugs on their mechanical, spatial, and fluid properties. The study encompasses an analysis of the effects of acyl chain saturation and length, diverse lipid headgroups, and drug incorporation. Experimental validations, conducted in collaboration with Prof. Auguste’s laboratory, support our simulation findings. We discovered that lipids with short-saturated acyl chains and varied headgroups alter the lipid bilayer packing, resulting in decreased liposome stiffness, which has been shown promoted drug delivery efficiency. Additionally, specific drug substances were observed to lower interaction energies within the lipid matrix, which consequently reduces stiffness and enhances lipid molecule diffusion. This segment of the dissertation provides crucial insights into the design of liposomal formulations, particularly for drug delivery purposes, by demonstrating how lipid structure and drug interactions can be manipulated to optimize liposome properties. Overall, this dissertation underscores the versatility of molecular dynamics simulations in elucidating complex material behaviors and offers valuable contributions to the various engineering fields.

CHE PhD Dissertation Defense: Shicheng Yang
2024-01-24 10:00 - 12:00 | MA
PhD Dissertation Defense: Drug Delivery Systems in Oncology: From Polymeric Implants to Nanomedicine Approaches
Shicheng Yang
Location: Hastings Hall 107 & Zoom
Abstract: Molecular inhibitors, including PARP inhibitor talazoparib, CDK inhibitor dinaciclib, and docetaxel, are critical in precision cancer therapy, offering novel therapeutic options for a range of cancers. While demonstrating potent activity as monotherapy or in combination in both preclinical and clinical settings, challenges such as drug resistance and off-target toxicity persist with these small molecule drugs. To mitigate these issues, innovative formulation strategies using implants or nanoparticles have been explored. These formulations are designed to alter drug uptake pathways, resist the emergence of drug resistance, and minimize direct contact with healthy tissues, thereby reducing toxicity. This thesis encompasses several nanotechnology approaches in formulating chemotherapy agents and their application across various cancers, including breast, ovarian, pancreatic, lung, and prostate.
In the context of ovarian cancer, known for its high mortality rate within the realm of female reproductive system cancers, more than 15% of cases involve defective BRCA-mediated homologous recombination repair pathways. Talazoparib, a PARP inhibitor, has been hindered in its clinical application due to severe systemic side effects. The development of a novel TLZ-loaded PLGA implant (InCeT-TLZ) is reported, designed for sustained release over 25 days directly into the peritoneal cavity, targeting BRCA-mutated metastatic ovarian cancer. Results from in vivo experiments indicated a doubling of survival in the InCeT-TLZ treated group compared to controls, with no significant toxicity observed in surrounding peritoneal organs. This suggests that localized and sustained delivery of Talazoparib can enhance therapeutic efficacy without significant toxicity. Additionally, the potential of combining CKD inhibitor and PI3K inhibitor with InCeT-TLZ to counteract acquired PARPi resistance was demonstrated in vitro, indicating a promising approach for enhanced ovarian cancer treatment.
While the biodegradable PLGA implants showed potency, the conventional solvent-based fabrication methods used to synthesize these implants, however, the use of toxic organic solvent and its safety issue pose difficulties for translation to clinical use. To address these challenges, a scalable, solvent-free hot-melt extrusion process was introduced for producing PLGA implants iii with docetaxel. This process ensures uniform dispersion of clinically relevant concentrations of the drug without requiring organic solvents. Results showed the bioactivity of incapsulated docetaxel was maintained during fabrication and controlled degradation, enhancing tumor growth inhibition capabilities both in vitro and in vivo. The implants, when used intratumorally, act as both radiosensitizers and continuous chemotherapy sources, suitable for scale-up in compliance with Good Manufacturing Practices (GMP).
Furthermore, the combination of talazoparib and dinaciclib has been studied to overcome PARPi resistance in tumors. The short blood circulation time of dinaciclib and the high toxicity of combination therapies pose significant challenges. Nanomedicine formulations have been developed to address these issues, creating a nano-cocktail of talazoparib (nTLZ) and dinaciclib (nDCB) to enhance therapeutic efficacy at lower doses. The study showed that these nanoformulations effectively infiltrate tumor cells, with synergistic effects observed in both BRCAmutant and BRCA wild-type cancer strains, particularly sensitizing BRCA wild-type cells to PARPi therapy. This approach demonstrates the potential of nanoformulations in broadening the applicability and enhancing the efficacy of combination cancer therapies.

Poster Design and Content: A CommLab Workshop Series
2024-01-24 17:00 - 18:00 | MA
The CommLab will host a three-part workshop series for poster design to focus on crafting the best visual communication of your research! With the upcoming PhD Research Expo, we will discuss techniques and implement communication strategies to successfully showcase your work. Join us for the first installment on Wednesday, January 24th from 5:00-6:00 PM in Curry Student Center 336 and on Zoom. Also join us on Wednesday, January 31 to polish your poster and on February 21 to practice your poster pitch. See you there!

CommLab Writing Hours
2024-01-29 11:00 - 13:00 | 335 CSC, 360 Huntington Ave, CSC, Boston, MA, 02115, United States
Graduate students, are you looking for a place for focused research writing time? Join the CommLab for writing hours on Mondays from 11 am-1 pm ET. Drop in any Monday and stay for a short time or the whole two hours. CommLab Fellows will be available to provide feedback on your writing. We will be meeting in 335 Curry Student Center.

Global Co-op Information Session
2024-01-30 18:00 - 19:00 | MA
Join the College of Engineering Global Co-op team in learning about global co-op opportunities for Summer II/ Fall 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 Summer II/ Fall 2024.
Location: Virtual- see NUworks for link and to register.
Please reach out to Kristina Hubbard, Global Co-op Coordinator, k.hubbard@northeastern.edu for additional information.

Chemical Engineering Spring Seminar Series: Professor Bryan James
2024-01-31 12:00 - 13:00 | 103 Churchill, 103 Churchill Hall, 360 Huntington Ave, Boston, MA, 02115, United States
Design strategies to minimize the environmental impacts of plastic products
Combatting the existential threats of climate change and pollution requires circularizing and decarbonizing material lifecycles, reducing persistence, and eliminating the toxicity of products and processes. Plastics, the combination of polymer and chemical additives, contribute significantly to both threats. Despite these harms, plastics are crucial materials for modern society. In their recent report, the U.S. National Academies of Sciences, Engineering, and Medicine identified material and product design as one of six key interventions to tackle plastic pollution. With this charge, I will demonstrate how combining concepts learned from the last decade of plastic pollution research with established material selection practices resulted in a quantitative, multi-dimensional framework for use during product design to minimize the environmental impacts of plastic. By taking this approach, a sustainability metric was developed for the design of plastic products with low environmental persistence and uncompromised performance. Applying this methodology to commonly littered plastic products (drinking straws and coffee cup lids) demonstrated that accounting for persistence in product design could reduce the societal impacts of plastic pollution by hundreds of millions of dollars for a single product. My findings identify the materials and their properties that deserve development, adoption, and investment to create functional and less environmentally impactful plastic products.

Dr. Bryan D. James is a Postdoctoral Investigator at the Woods Hole Oceanographic Institution (WHOI). As part of an interdisciplinary team of scientists and engineers within WHOI’s Microplastics Initiative, his postdoctoral research focuses on understanding the fate, persistence, and toxicity of plastic in the ocean to inform the rational design of next-generation materials that are safe for people and the planet. Through this work, Bryan has collaborated globally with academic colleagues, NGOs, and industrial partners and regularly engages with K-12 educators, mentors community college students, and advises policymakers. Bryan received his B.A.Sc. in materials engineering from the University of Toronto and his Ph.D. in materials science and engineering from the University of Florida (UF). At UF, as an NIH F31 Predoctoral Fellow under the mentorship of Prof. Josephine Allen, Bryan pioneered the use of nucleic acid-collagen complexes for hard and soft tissue engineering and championed investigating sex as a biological variable in biomaterials research, identifying mechanobiological sex differences in vascular cells. Bryan has been recognized with multiple early career honors and awards, including being named a Rising Star in Engineering in Health, a CAS Future Leader, a DYSS speaker, and an ACS PMSE Future Faculty Scholar.

An Interdisciplinary Approach to Building up Quantum Science and Technology
2024-02-02 11:00 - 12:00 | MA
The College of Science, College of Engineering, and Quantum Materials and Sensing Institute (QMSI) invite you to a joint special colloquium.
An Interdisciplinary Approach to Building up Quantum Science and Technology
Friday, 2nd Feb, 2024; 11:00 a.m. to 12:00 p.m.
Hosts: Arun Bansil and Matteo Rinaldi
Zoom meeting
Quantum science and technology hold the promise to deepen our understanding of the universe and deliver groundbreaking technical innovations. The opportunity also poses a grand challenge to today’s scientists and engineers because initializing, controlling, manipulating, and measuring the quantum information while maintaining the coherence and entanglement can be very difficult. Therefore, successfully achieving breakthroughs would require an interdisciplinary approach that leverages resources from various disciplines to forge new pathways which cannot be defined by a singular field of study.
In this talk, I will share my interdisciplinary adventure through quantum material and quantum device landscapes. We will start from the study of fundamental characteristics of Dirac and topological materials, and then focus on the material physics that we can exploit to invent single-photon detectors. We will further explore how to utilize the novel properties of the two-dimensional van der Waals materials to miniaturize qubits and develop quantum-noise-limited amplifiers. And finally, we will turn around to apply what we learn from quantum sensing to study the pairing symmetry of novel superconductivities, including the topological Weyl superconductors. We will end by elucidating how to harness the kinetic inductance of these novel superconductors for future flight-missions to explore planetary science and the origins of life.

Dr. Kin Chung Fong is a Senior Scientist at RTX BBN (Cambridge, MA) and a Research Associate at Physics Department, Harvard University. His interdisciplinary research focuses on quantum materials and their applications. KC also studies how to exploit these quantum sensors to investigate the hydrodynamic physics in the nearly perfect fluid, reveal the pairing symmetry of novel superconductors, search for the dark matter axion, and explore the origins of life from the early universe. In addition to his substantial publications in high-impact peer-reviewed journals, he is also a prolific inventor with >10 granted patents. His innovation has been recognized with the Raytheon Intelligence & Space Innovators Award in 2020 and 2022. KC received his PhD from Ohio State University and served his postdocs at Max Planck Institute for Quantum Optics and Caltech.

ChemE Department Town Hall
2024-02-06 12:00 - 13:00 | MA
Join Chair and Professor Rebecca Willits of the Chemical Engineering Department as she provides updates and information about classes and the Department of Chemical Engineering.

Library Webinar: Introduction to Citation Managers
2024-02-06 12:00 - 13:00 | MA
Learn how to manage your references, organize your research and quickly create citations and bibliographies using a citation management program. The session will cover: an introduction to EndNote, Refworks, Zotero and Mendeley; similarities and differences between different citation management programs; how to choose the right citation manager for you; and how to install and use a citation manager.
This workshop is at 12:00pm Eastern Time.
Register at bit.ly/citationmgmtworkshops.
You will receive the Zoom link for this webinar via email one hour before the event.
Related LibGuide: Citations and Bibliographies

2024 Morehouse College Career & Graduate School Fair
2024-02-06 13:00 - 18:00 | MA
COE Graduate Admissions will be attending the Career & Graduate School Fair at Morehouse College in Atlanta, Georgia! We will be meeting Morehouse students and helping answer questions about our graduate engineering programs across the U.S. and Canada from 1pm-6pm on February 6th. We look forward to meeting you there!

Chemical Engineering Spring Seminar Series: Benjamin Decardi-Nelson
2024-02-07 12:00 - 13:00 | 103 Churchill, 103 Churchill Hall, 360 Huntington Ave, Boston, MA, 02115, United States
Optimal Control as a Catalyst for Smart and Sustainable Systems
Sustainability is crucial in modern engineering, particularly in chemical and biological systems. It involves the use of sustainable resources and the development of environmentally friendly, smart, and efficient systems that minimize waste and optimize resource use. Central to engineering smart, sustainable systems is optimal control. However, integrating optimal control technologies into these systems is challenging due to the complexity of managing large-scale, constrained, nonlinear, and interconnected subsystems, particularly under uncertain conditions. In this talk, I will introduce a series of optimal control technologies that contribute to smarter and more efficient systems, enhancing their sustainability. Specifically, I will discuss the development and application of (1) model predictive control and (2) reinforcement learning, which are instrumental in engineering systems that use minimal resources and generate less waste. I will also demonstrate how optimal control is pivotal in advancing sustainable food production in urban areas through the integration of renewable energy and efficient resource management. These advances in optimal control are critical in developing smart, sustainable systems and are essential for a sustainable future.

Benjamin Decardi-Nelson is an Eric and Wendy Schmidt AI in Science Postdoctoral Fellow in Systems Engineering at Cornell University. Benjamin’s research interest in Process Systems Engineering centers around developing novel computational tools to improve the analysis, design and control of complex processes and systems, with the overarching goal of sustainability. Prior to joining Cornell, he earned his PhD in Process Control from the University of Alberta, where he developed efficient algorithms and large-scale optimization models for integrated real-time economic optimization and advanced process control of nonlinear process systems. At Cornell, Benjamin integrates biology-informed AI with optimization to decarbonize future food systems through implicit learning of plant-environment interactions, and renewable energy integration. His work has been recognized by the Schmidt AI in Science postdoctoral fellowship, Natural Sciences and Engineering Research Council of Canada (NSERC) postdoctoral fellowship, among others.
