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Ai Institute Summer Camp Academic Preview Webinar: Curriculum, Research, And Outcomes, Paul English Applied Artificial Intelligence Institute

Paul English Applied Artificial Intelligence (AI) Institute Publications

This webinar presents an academic preview of the AI Institute Summer Camp hosted by the Paul English Applied Artificial Intelligence Institute at the University of Massachusetts Boston. The session introduces the program’s curriculum, structure, and student outcomes, providing insight into a hybrid learning model that combines faculty-led lectures, hands-on labs, and guided project development. The webinar highlights the program’s five-week structure, covering topics such as machine learning, neural networks, computer vision, speech and language processing, and generative AI. Participants learn how students engage in real-world AI applications, complete portfolio-ready projects, and develop research and presentation skills. This session is designed …

Turbulent Plenum Jet-Crossflow Validation Via Subgrid Scale Model Variation And Upstream Forcing Under Dynamic Hybrid Rans-Les, Cole W. Mccallum

Mechanical Engineering Undergraduate Honors Theses

In modern gas turbine design, film cooling has become ubiquitous as a method for limiting heat transfer between high temperature gases post-combustion and the surface of downstream blades. This paper validates the use of various computational fluid dynamics techniques in recreating an experiment measuring adiabatic effectiveness over a surface downstream of a compound-angle N2 plenum jet incident on a turbulent-air boundary layer [1]. To do this, both RANS and Dynamic Hybrid RANS-LES (DHRL) methods are implemented and compared to previous research [2]. The latter method is then modified through implementation of a different subgrid scale (SGS) model and through addition …

Enhancing Control Charting Schemes And Exploring New Assessment Metrics To Advance Quality Control And Cyber-Attack Detection In Manufacturing, Ahmad Al Majali

Dissertations

The increasing integration of digital technologies and industrial control systems in modern manufacturing has introduced new cybersecurity vulnerabilities within cyber–physical production environments. Malicious actors can exploit these vulnerabilities to induce subtle process deviations that degrade product quality while remaining undetected by conventional statistical monitoring tools. Such attacks can be deliberately engineered to manipulate process behavior through transient shifts that vary in magnitude, duration, and frequency. Despite extensive research on transient shifts caused by assignable causes in Statistical Process Control (SPC), limited attention has been given to intelligently designed cyber–physical attacks that exploit the structural characteristics and limitations of control charting …

Designing Enhanced Nonlinearity In Plasmonic Devices With Epsilon-Near-Zero Films, Kevin Tran Le

Electrical Engineering and Computer Science (MS) Theses

The growing demand for energy-efficient optical information processing motivates compact nonlinear photonic devices that can operate at low power. Silicon photonics is a mature platform for linear optical functions, but nonlinear operation remains challenging because of its weak Kerr response, two-photon absorption at telecommunication wavelengths, and limited compatibility with deeply subwavelength plasmonic confinement. This thesis computationally investigates epsilon-near-zero thin films integrated into plasmonic waveguide architectures as a route toward stronger light–matter interaction in compact nonlinear devices.

Two waveguide geometries are examined: a hybrid metal-insulator-metal plasmonic slab waveguide incorporating an ultrathin indium tin oxide epsilon-near-zero layer (5–50 nm), and a dielectric-loaded …

A Multi-Objective Optimization Framework For Equitable Stormwater Management In Urbanizing Rural Communities, Harry L. Wilson

Industrial Engineering Undergraduate Honors Theses

Due to limited technical and financial resources, urbanizing rural communities often face growing stormwater management challenges while undergoing rapid development. This thesis proposes a mixed-integer linear programming (MILP) framework that integrates topography-driven stormwater flow behavior, infrastructure placement constraints, and multiple planning objectives to support cost-effective stormwater infrastructure decisions. Our model accounts for budget constraints, gravity-driven surface water flow, infiltration capacity, and spatial contiguity requirements to determine optimal pond placements that balance flood reduction and implementation costs. A synthetic discretized grid representing a small municipality is used to demonstrate model behavior under varying rainfall and topographic conditions. Results demonstrate the framework's …

Uav Blast Load Characterization For Structural Design, Jalee Grace Spain

Civil Engineering Undergraduate Honors Theses

As the use of drones, or UAVs, increases, so does the risk of collision with infrastructure. When drones collide with a building, an impact or blast load is applied. Using current literature and structural analysis, a load case can be defined for a blast load induced by a drone.

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

​Autonomous Agentic Orchestration For Physics-Aware Scientific Discovery: An Integrative Multimodal Framework For 2d Material Characterization​, Sankalp Pandey

Electrical Engineering and Computer Science Undergraduate Honors Theses

The advancement of next-generation semiconductor and quantum technologies relies on the scalability of the fabrication of two-dimensional (2D) van der Waals heterostructures. However, this process is severely bottlenecked by characterization workflows. Optical microscopy provides high-throughput imaging of 2D material flakes, but lacks the explicit physical priors required for the discernment of sub-nanometer thickness variations, such as distinguishing monolayers from bilayers. The use of computer vision models to automate the localization and characterization process of the flakes was proposed. As a part of this effort, we develop QuantumFlake, an open-source framework to streamline the integration and deployment of computer vision models …

Shooting For The Stars: Stem Outreach Strategies Between 2nd And 7th Grade, Paige Miller

Chemical Engineering Undergraduate Honors Theses

Engineering and planetary science outreach programs are increasingly important as industries and research organizations face growing demand for STEM professionals. Despite the importance of these fields, many students receive little exposure to engineering careers during their early educational experiences. This honors thesis examines the effectiveness of interactive STEM outreach presentations designed for elementary and middle school students. Specifically, this study evaluates outreach activities centered on chemical engineering applications and the NASA M2M CO₂ regeneration project for Martian environments.

Two student age groups participated in this study: 2nd grade students at Butterfield Elementary School and 7th grade students at Woodland Junior …

Physical And Optical Properties Of The Germanium-Arsenic-Selenium Glass Forming Region For Precision Glass Molding And Infrared Optics, Peter F. Wachtel Ii

All Dissertations

The growth and advancement of infrared optical systems for thermal imaging, multi-band imaging, hyperspectral imaging, medical diagnostics, and chemical sensing are pushing the material science community to better understand existing materials while also developing new materials. Additionally, the thermal imaging market continues to grow, and system designers are continually being asked to reduce size, weight, and power while reducing costs (SWaP-c). Market growth has shifted optics manufacturing towards higher volume processes such as precision glass molding, but this does require most materials to be recharacterized due to property changes resulting from the process. Affecting the SWaP-c requirements, manufacturing tolerances are …

Design And Reliability Analysis Of A Radiation-Tolerant On-Board Computer System For Martian Surface Missions, Jack Ryan

Master's Theses

Space environments present complex challenges for electronic devices, perhaps most notably in the form of radiation effects; the natural protections provided by Earth’s atmosphere and magnetosphere are largely absent in deep space and extraterrestrial environments, making single-event effects (SEE) a critical concern. Although radiation-hardened components offer near-immunity to SEE, they possess tremendous drawbacks in both cost and performance. To circumvent such issues, this thesis investigates the feasibility of leveraging a commercial-off-the-shelf (COTS) device, the AMD KRIA K24 system-on-module (SOM), for use in Martian surface missions.

Detailed models were used to predict SEE rates in the system, and system-level fault tree …

Post-Vote Tampering In Nigerian Elections And The Role Of Blockchain-Enabled Electoral Systems, Ransome Chukwubuikem Enechukwu

Electronic Theses and Dissertations

Post-vote tampering during the collation and transmission of election results remains a persistent challenge in Nigerian elections, enabling manipulation of already-cast votes and weakening public trust in electoral outcomes. Existing technological interventions, including biometric voter accreditation and digital result transmission systems, improve voter authentication but do not adequately secure the post-vote result collation process. This thesis proposes a blockchain-enabled framework designed to protect the integrity of election results during the collation and transmission stages. Using a Design Science Research methodology, the study develops a permissioned blockchain framework based on Hyperledger Fabric that records polling-unit results as immutable ledger entries and …

Adsorption Of Pfas On Bridged Functionalized Organosilica Materials, Elisha Lawerh Kabutey

Electronic Theses and Dissertations

PFAS are hazardous contaminants that have a devastating impact on human health and the environment. Their hazardous nature has led to the development of various adsorption methods for removing these contaminants from water sources. In this study, functionalized organosilica materials were synthesized from bis[3-(trimethoxysilyl)propyl] amine using the sol-gel method. The surface amino groups of the organosilica were converted into amine hydrochloride groups. Their adsorption properties were evaluated using salts of perfluorooctanoic acid, perfluorooctanesulfonic acid, and perfluorobutanesulfonic acid. Results showed excellent adsorption capacity of the materials. Adsorption of PFAS leads to particle agglomeration and flotation of the spent material. A column …

Fatigue And Cyclic Loading In Aircraft Engine Turbomachinery, Sarah Hilliard

Senior Honors Theses

The fatigue and cyclic loading of aircraft engine turbomachinery was explored in order to better understand and predict its failure. This exploration included a review of central topics such as aircraft engine components, fatigue, and the microstructural nature of metal. Also, the ANSYS Mechanical microstructural crystal plasticity tool was evaluated for its utility in fatigue prediction studies. No validation of the tool in question was possible within the scope of this thesis. Numerical fatigue life prediction methods were discussed, and current advancements in metal coatings and surface treatments for prolonging the life of certain superalloys were investigated. Further work in …

A Machine Learning-Based Apogee Prediction Methodology For Experimental Student Rockets, Price Hamilton Drawdy

Senior Honors Theses

The ability to predict the maximum altitude of a rocket (apogee) in real-time is incredibly useful for collegiate-level competition rockets. This project creates a machine learning-based real-time apogee prediction methodology. Three model types were tested: linear regression, random forest, and a 3-layer multi-layer perceptron (MLP) neural network. These models were trained on a large dataset of simulated flights. All models performed well on simulated test flights, with the linear regression model showing most promise for use on edge compute. More development and real-world testing are necessary to determine how applicable this method is for real-time operation. Nevertheless, this methodology provides …

Analyzing The Writing Style Of Generative Ai When Prompted With Writing Samples, Samuel Mcdowell

Senior Honors Theses

Authorship attribution is an important topic in today’s world of Large Language Models (LLMs). It is the technology that helps to verify the author of a written work. This study explores whether LLMs can successfully mimic an individual’s writing style if they are given a text sample. A dataset of human-written texts was collected and used to prompt several LLMs to generate new texts that attempt to replicate the original author’s stylistic characteristics. The generated texts were then tested with modern authorship attribution models to determine whether they would be identified as being written by the original author. The results …

Clear-Air Turbulence Climatology And Trends, Liam Rodgers, Mark Sinclair

Publications

Clear‑air turbulence (CAT) is a major aviation hazard that occurs near airline cruising altitudes in both cloud and cloud‑free environments. Its lack of a distinct visual signature makes detection and avoidance difficult. CAT is associated with wind shear near jet streams, gravity waves, and Kelvin–Helmholtz instability and may be further enhanced by climate change. This study examines the climatology, spatial distribution, seasonal variability, and trends of CAT over the contiguous United States.

Pilot Reports (PIREPs) from 2001–2025 between 100 and 400 hPa are analyzed alongside jet stream, shear, and stability diagnostics derived from NCEP–NCAR Reanalysis data. Proxies such as inverse …

Improving Fairness On Semantic Segmentation Using Large Language Models, Samuel E. Burggraf

Electrical & Computer Engineering Projects for D. Eng. Degree

As machine learning systems are increasingly integrated into critical decision-making processes, ensuring fairness in their design and implementation has become a significant concern. While fairness research has primarily focused on specific protected attributes, less attention has been given to spatial fairness, which can affect individuals at specific locations. If fairness is not addressed, models may systematically underperform in certain regions or across populations which can lead to unequal access to accurate predictions and potentially biased decision-making. Fairness considerations should extend across all machine learning applications to align with the National Institute of Standards and Technology (NIST) guidelines of fair and …

Harness: Hybrid Architecture For Resilience In Networked Engineering System Simulations, Daniel Scott

Graduate Theses and Dissertations

This dissertation presents the development of HARNESS, a unified, domain-agnostic framework for the modeling, optimization, and evaluation of complex systems under conditions of degradation and uncertainty. The research addresses a persistent challenge in systems engineering: the lack of a generalizable, behaviorally grounded approach for quantifying resilience and robustness across diverse domains. HARNESS integrates graph-theoretic dependency modeling, GPU-accelerated evolutionary optimization, and agent-based simulation into a modular architecture that enables both system design and diagnostic analysis. The framework models system interdependencies through user-defined components, parameters, and constraints, allowing architectures to evolve dynamically while maintaining structural validity. A mutation-only genetic algorithm with a …

An Energy- And Area- Efficient Two-Stage Latch Comparator Using Common-Mode Reset, Larry Yu

Electrical Engineering Theses and Dissertations

This thesis presents an energy-and-area-efficient two-stage comparator implemented in TSMC 65 nm CMOS that incorporates a Floating Inverter Amplifier (FIA) followed by a latch using a common-mode reset scheme. The FIA improves input sensitivity and reduces kickback noise by isolating the input nodes from large latch voltage swings. The proposed latch resets its output nodes to a common-mode voltage rather than one of its supply rails, thereby reducing switching energy during the reset phase. The comparator can resolve differential input voltages as small as 2 mV with a clock period of 500 ps, achieving 74.33 μV input-referred noise while consuming …

Optimization Of The Baffle Geometry Of A Circular Culvert Outlet Structure To Maximize Energy Dissipation, Kiarash Shirmahi

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

High-velocity flow at culvert outlets can lead to significant soil erosion and damage to downstream infrastructure, particularly in agricultural regions where land protection is critical. Circular culverts, commonly used in transportation systems, are especially susceptible to this issue due to flow acceleration caused by geometric constraints and installation angles. Despite extensive research on energy dissipation in rectangular culverts, limited attention has been given to circular configurations. This study addresses this gap by evaluating the hydraulic performance of baffle systems designed to reduce outlet energy in circular culverts.

A series of laboratory experiments was conducted using a scaled physical model of …

A Full System Co-Simulation Platform For Evaluating Edge Machine Learning Inference Using Compute-In-Memory, Belsen Lee

Electrical Engineering and Computer Science (MS) Theses

We present a full-system co-simulation platform for evaluating embedded machine learning (ML) inference using compute-in-memory (CIM). CIM architectures aim to reduce data movement overhead by performing matrix operations in memory, but end-to-end benefits depend on system-level integration costs that are difficult to assess with isolated hardware models alone. To address this gap, we develop an integrated RISC-V QEMU-SystemC co-simulation environment that allows standard embedded Linux to interact with a transaction-level CIM accelerator model via memory-mapped I/O, direct memory access (DMA), and interrupts. To evaluate performance, we benchmark an MNIST image inference workload and a synthetic fully connected neural network, comparing …

Transformer Vulnerability To Geomagnetically Induced Currents Using Layered Soil Conductivity Models, Junior A. Sterling

Masters Theses

Geomagnetically induced currents (GICs) pose a significant threat to modern power transformers connected to long high-voltage transmission systems, particularly in regions with low subsurface electrical conductivity. During geomagnetic disturbances (GMDs), time-varying magnetic fields induce surface electric fields that drive quasi-DC currents through grounded transformer neutrals. These currents can bias transformer cores, leading to saturation, waveform distortion, and potential system instability. Despite extensive research, the role of regional Earth conductivity in shaping electric fields and transformer response remains an area requiring deeper investigation.

This study analyzes how contrasting Earth conductivity profiles influence GIC magnitude and transformer saturation risk using two representative …

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …

Power System Small-Signal Stability Migration And Metric Trends In A Test System With Increasing Ibr Penetration, Brandon Marshall

LSU New Orleans Theses and Dissertations

With the increasing demand of cleaner energy, inverter-based resources (IBRs) provide a greener alternative to traditional generation methods. IBRs fundamentally work different from traditional generators, though, and power system stability will change as IBRs are integrated into the system. The limitations of IBRs include providing less reactive power support to the system and lacking a spinning rotor for inertia to dampen disturbances. This study examines how small-signal stability is impacted when increasing IBR penetration on a test system. Stability impacts are realized by the migration of eigenvalues and relationships between power system metrics and small-signal stability metrics.

Autonomous Deficiency Detection And Vision-Language Summarization For Underground Infrastructure On Embedded Edge Systems, Johny Lopez

LSU New Orleans Theses and Dissertations

Aging underground infrastructure poses significant risks to public health and environmental safety, yet structural condition assessment remains bottlenecked by labor-intensive manual CCTV inspections. This thesis proposes a comprehensive algorithmic framework enabling fully autonomous, real-time deficiency detection, geometric assessment, and natural language reporting on resource- constrained edge computing platforms. Three core components address this challenge. First, RAPID-SCAN, a novel semantic segmentation architecture utilizing a Dynamic Feature Pyramid Network and Channel-Spatial Attention, achieves real-time, pixel-precise defect localization with dramatically reduced parameters. Second, an Edge-Optimized Vision-Language Model pipeline employing LoRA and 4-bit QLoRA quantization compresses Phi-3.5 for local deployment, en- abling autonomous technical …

Effect Of Composition On Grain-Boundary Chemistry And Fracture Behavior In High-Entropy Carbides, Caleb Schenck, Marium Mostafiz Mou, Elizabeth Pritchett, Fu Yun Tsai, Josephine Hartmann, Michael Lastovich, Sam Daigle, Kayla Yano, Matthew J. Olszta, Sanjit Bhowick, Elizabeth Kautz, Gregory E. Hilmas, William G. Fahrenholtz, Donald W. Brenner

Materials Science and Engineering Faculty Research & Creative Works

High-entropy carbides (HECs) are often treated as a single material class defined by configurational entropy; however, their properties are governed by composition-specific defects and grain-boundary chemistry. This study demonstrates that substituting a single element can qualitatively change grain-boundary structure and fracture behavior in HEC ceramics. Two HECs, (Cr,Hf,Ta,Ti,Zr)C (HEC-Cr) and (Hf,Ta,Ti,W,Zr)C (HEC-W), were examined via electron microscopy, atom probe tomography, and molecular dynamics simulations. Simulations predict preferential segregation of Cr, W, and Zr to grain boundaries. Experiments confirmed Cr enrichment at grain boundaries and the formation of W-rich nanograins along boundary networks. Mechanical testing revealed that these compositional differences translated …

Evaluating The Integration Of Bio-Based Waste Into Cement Production: A Pathway To Sustainable Building, Anja Terzić, Suzana Filipović, Adriana Peleš Tadić, Jelena Živojinović, Ivana N. Jelić, Nina Obradović, William G. Fahrenholtz

Materials Science and Engineering Faculty Research & Creative Works

Rapid urbanization has increased the demand for building materials, depleting natural resources used in cement production and prompting the use of alternative and waste materials. This research verifies that eggshell powder waste can fully replace limestone in clinker synthesis. Five clinkers were produced using eggshell powder, aluminum sources (bentonite, zeolite, fly ash, and kaolinitic–illitic clay), Fe-slag, and quartz sand, with mechanical preprocessing (10–30 min) before sintering at 1300 °C. Experimental tests assessed the effects of mix design and mechanical activation on clinkerization, phase formation, temperature, and mechanical properties. XRD, FTIR, and SEM/EDS confirmed consistent phase compositions and primary cement minerals. …

An Efficient Implementation Of Gibbs-Duhem Integration For Solid-Liquid Phase Coexistence In Binary Lennard-Jones System With Relevance To Aav Capsid Separation, Muhi Muntaka

Graduate Theses and Dissertations

Gene therapy using adeno-associated viruses (AAVs) holds promise for treating genetic diseases, but high manufacturing costs limit its widespread use. A major challenge is separating functional (full) AAV capsids from non-functional (empty) ones, which are produced in similar amounts and have nearly identical structures. Conventional purification methods, such as density gradient ultracentrifugation and chromatography, face drawbacks like low yield, poor scalability, and high cost, often requiring multi-step processes. Recently, selective crystallization has emerged as a promising alternative, offering improved efficiency, scalability, and product quality. However, optimizing this method requires a deep understanding of thermodynamic phase behavior in multicomponent systems. In …

From Data Digitization To Personalized Care: Deep Learning And Decision Analytics In Healthcare Systems, Ahla Ko

Graduate Theses and Dissertations

This dissertation traces a progression from foundational data infrastructure to individualized clinical decision-making, developing and evaluating three computational frameworks that advance healthcare efficiency and personalization through deep learning and decision analytics. The first study presents an end-to-end pipeline for automated recognition of handwritten medical forms, addressing persistent challenges in health data digitization. Integrating a YOLO-based field detection model, a Convolutional Recurrent Neural Network (CRNN) for text transcription, and a confidence-based human-in-the-loop quality assurance framework, the system achieved 99.75\% Exact Match Accuracy and a 0.13\% Character Error Rate on medical forms collected from a tuberculosis research project in Moldova. A GPU-accelerated …