Electrical and Computer Engineering Commons^™

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Integrated Power, Energy, And Thermal Management For Autonomous Hybrid Off-Road Vehicles: Multi-Timescale Modeling, Predictive Control, And Resilient Thermal Design, Anirudh Sundar

All Dissertations

Electrification and autonomy are increasingly important for off-road vehicles operating in construction, agriculture, mining, defense, and other demanding environments. These platforms must deliver high tractive power under unstructured terrain, harsh ambient conditions, low-speed operation, and large auxiliary loads. While hybrid and electrified powertrains offer improved efficiency, mobility, and auxiliary power capability, they also introduce significant challenges in managing tightly coupled power, energy, and thermal subsystems. In particular, lithium-ion batteries, power electronics, electric machines, and internal combustion engine-generator systems operate across different temperature limits and timescales, requiring coordinated management to ensure efficiency, durability, and safe operation. This dissertation develops modeling, planning, …

Efficient And Scalable Visual Computing For Nanoscale Imaging, Hao Wang

All Dissertations

Nanoscale analysis often relies on instrument-mediated scientific imaging methods to capture visual signals that are difficult to observe, interpret, or quantify through ordinary perception alone. These domains are often characterized by low signal quality, limited annotations, complex morphology, non-natural visual statistics, and strong dependence on physical acquisition processes. This dissertation focuses on efficient visual computing for nanoscale imaging, with an emphasis on the representation, reconstruction, and analysis of high-resolution scientific visual data. In our early work, we relied on rule-based algorithms and conventional machine learning methods for feature extraction. However, these approaches struggle to scale with the increasing complexity and …

Optimization Of A Cryogenic Electrical Characterization System And Its Application To Thermal Admittance Spectroscopy, Angel Efren Garcia

Open Access Theses & Dissertations

Defect characterization in semiconductors relies on locating trap levels through the temperature dependence of carrier emission, which makes the accuracy of the device temperature a limiting factor in every extracted parameter. This work addresses the limitations in the cryogenic electrical characterization system at The University of Texas at El Paso, where Deep-Level Transient Spectroscopy (DLTS) had been established but produced activation energies that disagreed with literature values by as much as 0.33 eV. The discrepancy was traced not to the technique but to the transfer of heat to packaged devices in a probe station designed for on-die measurement. The cryogenic …

Electrical Characterization Of Wide-Bandgap Devices Via Laboratory Measurements, Tcad Simulation, And Analytical Modeling, Sebastian Alessandro Mimbela

Open Access Theses & Dissertations

Gallium nitride (GaN) devices are important for high-power, high-frequency, and harsh-environment applications because of their wide bandgap, high breakdown capability, and electrical performance. This thesis focuses on the electrical characterization of GaN-based devices using laboratory measurements, analytical modeling, and TCAD simulation. Current-voltage (I-V) and capacitance-voltage (C-V) measurements were performed on a GaN Schottky diode. The measured data were analyzed to extract key parameters such as ideality factor, Schottky barrier height, series resistance, donor concentration, built-in potential, depletion width, and maximum electric field. A TCAD process was also developed in Synopsys Sentaurus to recreate the main geometry, layer structure, contacts, and …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Deep Multimodal Sensor Fusion For Autonomous Driving: A Real-World Deployment On Little Blue, Raphael T. Pamie-George

Electrical & Computer Engineering Theses & Dissertations

Accurate perception and control systems are essential for autonomous vehicles to safely interpret and navigate complex environments. Individual sensing modalities such as cameras, LiDAR, and inertial measurement units (IMUs) provide valuable environmental and vehicle state information; however, each sensor exhibits inherent limitations when used independently. Camera performance can degrade under varying lighting conditions, LiDAR measurements may be sparse or affected by environmental noise, and IMU measurements are susceptible to drift over time. Little Blue, a research autonomous vehicle platform from ODU (Old Dominion University), previously relied primarily on camera-based data for neural network training, limiting the system’s ability to exploit …

Policy And Regulation In Virtual Power Plants Development, Hemlal Bhattarai, Aziz, Stefan Lachowicz

Research outputs 2022 to 2026

Electricity systems are changing due to the rapid deployment of distributed energy resources (DER), which also presents significant regulatory obstacles to their coordinated integration into energy markets and power grids. However, the majority of current material in publications concentrate on operational optimization and technical architectures, with little systematic synthesis of the legal and policy frameworks governing the deployment of VPP on a broad scale. To provide grid services, improve flexibility and support decarbonization objectives, virtual power plants (VPP) have become a crucial aggregation method. To close this gap, this research critically looks at the institutional roles, market structures, global policy …

Macroscopic Classical And Quantum Models Of Inverse Compton Scattering, Emerson Penn Rogers

Physics Theses & Dissertations

Inverse Compton sources — in which a relativistic electron beam scatters a laser pulse to produce tunable, collimated, high-energy radiation—have emerged as among the most promising compact radiation sources, with applications ranging from nuclear photonics to medical and nanoscale imaging and metrology. The most viable current tabletop configuration couples laser-wakefield acceleration with inverse Compton scattering, producing GeV-scale electron beams over millimeter distances. As laser intensities increase and electron energies grow, the interaction enters the radiation reaction regime, where the energy radiated by the electron becomes a significant fraction of its kinetic energy. Predicting the scattered electron energy spectrum — the …

Modeling Power Distribution Architectures And Maintaining Constant Power With Misalignment In Dynamic Wireless Charging Systems For Electric Vehicles, Mayank Chawla

All Graduate Theses and Dissertations, Fall 2023 to Present

With increasing demand for wireless power transfer systems from phone charging and medical devices, in-motion wireless charging of electric vehicles offers a unique advantage of charging the vehicle while in motion on an electrified roadway. Compared to the stationary or wired charging, electric vehicle users can significantly save time and cost with a reduction in the battery size. However, with large-scale infrastructure required for a wireless charging roadway and the driver’s ability to align with the electrified roadway, come significant challenges for the practical implementation of in-motion wireless charging systems.This dissertation aims to solve some of the problems associated with …

Enhancing Stem Education With Modeling, Simulation, And Ai Technologies: From Virtual Laboratories To Intelligent Teaching Assistants, Yiyang Li

Electrical & Computer Engineering Theses & Dissertations

Rapid advancements in modeling and simulation (M&S) and artificial intelligence (AI) present new opportunities to enhance various aspects of STEM education, from virtual laboratories that simulate physical lab environments in software to intelligent teaching assistants that provide on-demand, curriculum-aligned instructional support. Virtual laboratories offer a potential solution to the access and scalability challenges of laboratory courses by allowing students to conduct experiments without physical equipment or geographical constraints. AI-powered teaching assistants, particularly those grounded in course-specific materials, can help mitigate the instructional support gap that arises when students work independently in digital learning environments. This dissertation presents three-phase research into …

Experimental Investigation Of The Discharge Modes Of Nanosecond Pulsed Plasmas At Atmospheric Pressure, Md Ziaur Rahman

Electrical & Computer Engineering Theses & Dissertations

The generation of repeatable and stable nanosecond pulsed atmospheric pressure plasmas is important to non-thermal plasma applications in various fields including medicine, material processing, food processing, and plasma ignition for combustion. This dissertation investigates the atmospheric pressure plasma initiation and formation under 10 – 200 ns pulsed power for electrode configurations applicable for transient plasma ignition (TPI) for combustion. The impacts of pulsed power parameters, gas condition, and electrode geometry on the discharge initiation and modes (i.e., streamer, transient spark and spark) are systematically evaluated for applying TPI for combustion. We evaluated the discharge modes driven by both longer and …

Load Balancing Algorithms For Cloud Computing Systems, Mark Rakesh Christian

Electronic Theses and Dissertations 2020 - Present

Cloud computing depends on load balancing to allocate user requests among virtual machines (VMs), affecting response time, utilization, and scalability. Round Robin, Equally Spread Current Execution, and standard Throttled scheduling are widely used; however, standard Throttled selects among eligible VMs using an implementation-dependent order with no explicit preference. This thesis proposes the Weighted Throttled Load Balancing (WTLB) algorithm, which introduces an explicit, deterministic selection priority among eligible VMs, implemented by modifying the Throttled scheduler within CloudAnalyst.

Evaluated under an identical six-region, multi-data-center configuration against Round Robin, ESCE, and standard Throttled, WTLB preserves the aggregate response-time, processing-time, and cost profile of …

3d Electromagnetic Simulations Of A 1.6 Cell S-Band Photoinjector: Emittance Studies For Electron Microscopy, Trudy Bolin

Electrical and Computer Engineering ETDs

Modern beam-based materials research demands electron sources with increasingly precise time resolution, high brightness, and stability. For example, there are various instruments across the U.S. dedicated to ultrafast electron diffraction (UED), but fewer are dedicated to ultrafast electron microscopy (UEM), which demands beam stability. Modeling femtosecond electron bunches with ultra-low emittance < 50 nm-rad inside a 1.6-cell S-band (2856 MHz) rf photoinjector with full 3D electromagnetic simulations can require high-performance computing (HPC) environments due to the scale disparity between the macroscopic cavity geometry and the femtosecond-scale bunch kinematics. To enable optimization in a desktop computing environment, this work presents a streamlined 3D electromagnetic Particle-in-Cell (PIC) simulation framework optimized for 400-femtosecond bunch regimes. The covariance method was employed to study emittance properties for electron bunch counts ranging from thousands to millions and has successfully resolved highly transient, pure rf phase-space rotations, such as a localized energy-spread minimum occurring at the gun exit iris. To overcome the computational cost of these simulations, a machine-learning-based Bayesian optimization approach was deployed to construct multi-objective Pareto fronts from sparse datasets. Because the simulation software is scalable from desktop to HPC facilities, the framework is ready for experiments at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

Tinyml-Based Embedded Vision System For Ic Detection In Microcontroller Manufacturing, Mark M. Pallones, King Harold A. Recto, Rynne Daven A. Barrios

Electronics, Computer, and Communications Engineering Faculty Publications

Mixing of microcontroller unit (MCU) integrated circuits (ICs) during the final testing stage of semiconductor manufacturing can lead to material waste, production delays, and customer dissatisfaction. This issue often occurs when standard JEDEC Matrix Trays (JMTs) are reused without confirming that all ICs have been removed after testing, a process typically performed through manual inspection and therefore susceptible to human error due to high test volumes, small IC package sizes, and visual similarity between IC packages and tray surfaces. This study develops an automated IC Detection Test System using embedded vision to determine whether JMT trays are empty prior to …

Developing A Dispersion Interferometer For Characterizing Power Flow Plasma Formation And Transport Studies, Nathan R. Hines

Electrical and Computer Engineering ETDs

Sandia's refurbished $Z$-pinch machine experiences persistent current loss in its post-hole convolute and inner magnetically insulated transmission line regions, widely attributed to low-density electrode plasmas whose formation and transport remain poorly constrained by existing diagnostics. This dissertation develops and validates a fiber-coupled, continuous-wave, second-harmonic orthogonally polarized dispersion interferometer for time-resolved measurements of electron areal density in millimeter-scale gaps. The diagnostic employs single-laser second-harmonic generation, non-steering differential phase control, and polarization-based phase retrieval to achieve sub-$10^{15}$~cm$^{-2}$ sensitivity, multi-hundred-megahertz bandwidth, and sub-$200$~$\mu$m effective cross-gap spatial resolution. Performance is benchmarked against a $94$~GHz interferometer on the UNM Helicon-Cathode plasma device and then fielded …

Synergizing Crowd Collaboration: Enhancing Crowdsourcing Matching Via Integration Of Matching Theory And Coalition Games, Rowan Aengus Kinney

Electrical and Computer Engineering ETDs

This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH considers incentives, information availability and cost, and the decisions of fellow crowdworkers to model the utility functions for both the crowdworkers and the crowdsourcers. Specifically, the paper presents an initial Approximate CROWDMATCH mechanism grounded in matching theory principles, eliminating externalities from crowdworkers’ decisions and enabling each entity to maximize its utility. Subsequently, the Accurate CROWDMATCH mechanism is introduced, being initiated by the outcome of the Approximate CROWDMATCH mechanism, and employing …

Development Of Dynamic Proof-Mass Configurations For Broadband Piezoelectric Energy Harvesting, Nico E. Galarza

Electrical and Computer Engineering ETDs

The purpose of this thesis is to investigate and develop dynamic proof-mass configurations for broadband piezoelectric energy harvesting. Conventional piezoelectric energy harvesters are typically limited by narrow operating bandwidths, restricting their performance under variable-frequency excitation. This research presents the design, fabrication, and experimental evaluation of multiple proof-mass concepts intended to increase the usable frequency range of cantilever-based piezoelectric energy harvesters. Several dynamic mass configurations were developed using additive manufacturing techniques and integrated with commercially available piezoelectric cantilevers. Experimental testing was conducted under controlled vibration conditions to characterize voltage response, resonant behavior, and bandwidth performance. The results demonstrate that dynamic proof-masses …

Enhanced Computational Modeling Of Photoionization And Streamer Formation, Anahita Alibalazadeh

Electrical and Computer Engineering ETDs

Photoionization is a key mechanism governing the formation and propagation of streamer discharges in air by generating electron-ion pairs ahead of the streamer front. Accurate and computationally efficient modeling of this non-local process is essential for reliable plasma simulations. However, the widely used Zheleznyak photoionization model relies on empirical assumptions and requires computationally expensive domain-wide integration.

This dissertation advances photoionization modeling in three ways. First, the classical integral model is enhanced by incorporating experimentally measured vacuum ultraviolet (VUV) emission spectra together with photoabsorption and photoionization cross-section data, enabling direct calculation of the photoionization source term as a function of pressure …