Electrical and Computer Engineering Commons^™

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

Unified Bayesian And Machine Learning-Based State Of Charge Estimation In A Pv Battery System, Showrov Rahman

Open Access Dissertations

The state of charge (SOC) of a battery indicates the remaining charge in the battery relative to its nominal maximum charge capacity. The accurate estimation of SOC is of utmost importance for efficient energy management as it indicates the level of energy stored in the battery.

Bayesian and machine learning (ML) approaches represent two distinct estimation strategies for battery state estimation. Bayesian filters, such as the Kalman filter (KF) and particle filter (PF), operate sequentially by incorporating physical models of battery dynamics. In contrast, ML-based methods are data-driven, and their performance largely depends on the quantity and quality of training …

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

Delay-Doppler Integrated Sensing And Communications (Dd-Isac) With Predictive Beamforming, Mohammad Abdul Mobin, Yanjun Pan, Jingxian Wu

Electrical Engineering and Computer Science Faculty Publications and Presentations

A new delay-Doppler (DD) integrated sensing and communications (ISAC) framework is proposed for unmanned aerial vehicle (UAV) systems. In the DD-ISAC framework, both sensing and communications are performed by using the orthogonal delay Doppler division multiplexing (ODDM) waveforms, which unify sensing and communication designs through the unique ODDM waveform properties, such as local DD-domain bi-orthogonality and dual-resolution. Specifically, the dual-resolution property enables the generation of a range-Doppler map for accurate and low complexity sensing, and the bi-orthogonality minimizes interference for both sensing and communications. The ODDM waveforms are used in combination with the phase comparison monopulse technique and a scaled …

Printer For Music Box, Chad Lewis, Caleb Murawski, Zion Smith, Bryan Tibbs

Williams Honors College, Honors Research Projects

The traditional method of creating music box sheet music involves manually punching holes into a paper strip using a hand-operated hole punch. This process involves precise knowledge of each note’s location and the ability to achieve perfect accuracy for hours.

The goal of this system is to automate this process, significantly reducing the time required while greatly improving the accuracy of the resulting music box playback. The user simply uploads a MIDI file of their choice into a user-friendly application. Here, the file is modified based on the user’s needs and sent to an automated hole-punching system to punch the …

Adaptive Lighting System, Jacob Samerdak, Ethan Schwartz, Brandon Breen, Matthew Carozza

Williams Honors College, Honors Research Projects

The Adaptive Lighting System is a modular network of components that requires minimal installation in homes. Additionally, all components of the system communicate wirelessly and interface with a mobile application. The system utilizes occupancy and daylight sensors to detect the environment of a room and adjust the lighting accordingly. The system detects ambient lighting as well as occupancy within a room. Using the data collected from the sensors, the system adjusts lighting temperature, color, and brightness. The user can also manually control these settings. The Adaptive Lighting System aims to help regulate circadian rhythm, so there is a configuration in …

Aquaflow Pro, Ashton Henley, Jeannie Fritz, Khalin Rubbo

Williams Honors College, Honors Research Projects

Changing aquarium water is a hassle, and when done incorrectly, it will result in changes in water quality and potential harm to aquatic life. Aquarium water changes are crucial in removing toxins such as ammonia, nitrites, and nitrates. There is a need for an automated, stressless fish tank water-changing solution that ensures aquatic safety. To this end, an automatic temperature-controlled fish tank water changing system was designed, carrying out a water change for a designated main tank in which water heated within an inbound reservoir is pumped into the tank to replace the outbound water, responding to both the tank’s …

C. Difficile Detection Method For First Responder Glove Application, Alli N. Senedak

Williams Honors College, Honors Research Projects

Clostridioides Difficile (C. diff) is a Anaerobic Gram-positive bacillus that is capable of spore formation, making it difficult to control its spread and duration in clinical environments. This phenomenon can provide danger to first responders, healthcare workers, and patients. The goal of this project is to create a biosensor capable of detecting C. diff in a clinical setting that can be applied to a glove apparatus. The project will involve the use of C. diff aptamers activated on the surface of an electrode. Once surface activation has been verified via surface analysis, the electrodes will be exposed to C. diff …

Chronofy: A Temporal-Logical Decay Architecture For Information Validity In Time-Aware Retrieval-Augmented Generation, Muntaser Syed, Marius Silaghi, Sheikh Abujar, Sharun Akter

Electrical Engineering and Computer Science Student Publications

Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RAG architectures treat all retrieved facts as equally valid regardless of temporal provenance, leading to temporal hallucination, where plausible but obsolete facts corrupt the output. A clinical lab reading from yesterday is actionable; the same reading from six months ago is noise. We present Chronofy, a three-layer neuro-symbolic framework implementing the Temporal-Logical Decay Architecture (TLDA) that embeds temporal validity directly into the representation, retrieval, and reasoning layers of RAG systems. Layer 1 reserves a dedicated temporal subspace within Matryoshka embeddings to make …

Epistemic Edge: Subjective Logic Guardrails For Llm-Driven Iot Actuation, Muntaser Syed, Marius Silaghi

Electrical Engineering and Computer Science Student Publications

Deploying large language models (LLMs) as decision-making agents in safety-critical Internet of Things (IoT) systems introduces risks that purely behavioral guardrails, such as action whitelists, cannot fully address. This paper presents Epistemic Edge, a four-tier neuro-symbolic pipeline that augments LLM-driven actuation with subjective logic (SL) uncertainty quantification, temporal decay, and dual guardrails combining epistemic threshold checks with behavioral whitelists. We evaluate seven locally-deployed models: three PrismML Bonsai 1-bit models (1.7B, 4B, 8B), three 4-bit quantized models (Qwen3-8B, Llama 3.2-3B, Phi-3.5-mini), and the DeepSeek-R18B reasoning model, across eight ablation conditions and five IoT actuation scenarios (2,800 controlled trials). We further validate …

Towards Optimal And Resilient Ac/Dc Microgrids: Control Design, Analysis, And Implementation, Jun Zhang

Electronic Theses and Dissertations

Microgrids serve as a small-scale power grid for utilizing renewable energy to enhance energy reliability, sustainability, and resilience. As an autonomous system, an islanded microgrid can disconnect from the utility grid and operate independently by maintaining system voltage and frequency. However, this new feature introduces coordination problems among distributed generators (DGs), such as 1) how to make sure the voltage profile and current sharing in DC microgrid with different types of converters; 2) how to reduce the impact of cyberattack when the system coordination is performed based on communication, and 3) how to calculate the steady state under a droop …

Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest

Williams Honors College, Honors Research Projects

This report details the project known as “The BRRBOX”, a reusable, insulated thermoelectric cooler developed to keep internal temperatures at refrigeration levels or cooler for at least 48 hours. The cooler will track its internal temperature during this period and be able to give the data at the end of its delivery cycle to keep up with food and pharmaceutical standards during delivery. The BRRBOX uses Peltier-based cooling alongside vacuum insulation panels and fans to achieve efficient thermal control. An onboard microcontroller will monitor temperature, record the data, and adjust the cooling output to minimize power consumption. The box will …

Automatic Pet Feeder Network, Daniel J. Herttna, David A. Bechtel, Alexander Deskovich

Williams Honors College, Honors Research Projects

This project will describe the design process and research behind the Automatic Pet Feeder Network, otherwise known as The Petwork. The system consists of a tank to hold the food, a latching system to drop the food at the desired time, a weight sensor to verify that the proper amount of food has been dispensed, a power supply unit that steps down 120V AC standard wall outlet power, & a microcontroller that will interpret the user's input from a mobile phone application. The networking portion is covered by having a primary and a secondary feeder. The mobile application will communicate …

Development Of A Scalable 32x32 Capacitive Sensing Array Using Fpga Controlled Multi-Bus I2c Communication, Jonathan Digby

2026 Research Poster Competition

High-resolution capacitive sensor arrays are widely used in applications such as robotics, wearable devices, and biomedical devices where accurate detection of touch, proximity, and motion is crucial. As these systems are scaled up to achieve higher resolutions, challenges pertaining to communication reliability, data synchronization, and system latency become more important. Capacitive sensor arrays detect changes in capacitance caused by disturbances in nearby electric fields. While these arrays are effective at small scales, large arrays often suffer from signal degradation and latency when all sensors rely on a single controller and communication bus. This research addresses these challenges by developing a …

Application Of Matlab Simulation For Quantum Wells And Absorption Modelling, Mohamed Nur

Electrical Engineering Theses

The Quantum-Well User Entered Simulation Tool (QUEST), originally developed at the University of Texas at Arlington in 2005, is a simulation program built in MATLAB for computing energy eigenvalues and wavefunctions in user-defined semiconductor quantum well structures. This thesis presents a new revision and extension of QUEST with three primary contributions: compatibility updates to the existing MATLAB codebase, intersubband absorption modelling, and a redesigned graphical user interface for ease-of-use in testing.

The modernization effort for this program addresses incompatibilities introduced by changes to the MATLAB runtime environment since QUEST’s original release in 2005, including corrections to the self-consistent Schrödinger-Poisson solver …

The Design And Analysis Of Robust Mems Devices For Extreme Space Environments, Joshua Taggart

Honors Undergraduate Theses

The purpose of this study is to analyze aluminum nitride (AlN) micro-electromechanical systems (MEMS) resonators designed for extreme-environment applications. The devices of study are Lamb wave, piezoelectric resonators designed and fabricated using conventional semiconductor manufacturing processes and operating around various frequencies in the megahertz range. The purpose of this study is to advance understanding of MEMS devices in extreme-temperature and radiated environments for outer-space applications.

Devices were tested under vacuum at temperatures ranging from room temperature (~21°C) to 800°C. Under these conditions, the device was measured both as a resonator and in an oscillator circuit. Results show that the resonant …

Distributed Vibration Sensing For Identification Of Loose Connectors In Coaxial Data Transmission Lines, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Jie Huang, Daniel S. Stutts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This study investigates the effect of vibration-induced loose connections on signal reflection (S11) for loose connection identification in aerospace coaxial cables using distributed sensing approach, which is effective in filtering the noise and identifying minor discontinuities. In this approach, a sliding gated window is applied to S11 signal, a fast Fourier transform is performed over the gated windows, cross-correlation is computed between the baseline and vibration-affected signals, and the standard deviation is mapped along the cable length. Sinewave signals from 9 kHz to 5 GHz were swept through cables with vibrating connectors under three conditions: fully tightened, loosened by 180°, …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Hyperglycemia Detection From Single-Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes need to measure their glucose levels in order to determine how much insulin or medicine …

Bi-Level Optimization Of Peer-To-Peer Trading In A Decentralized Energy Market, Marshal Miezah

Graduate Theses, Dissertations, and Problem Reports (ETD)

Distributed power generation based on rooftop photovoltaic (PV) systems integrated with battery storage emerges as a promising pathway for reducing greenhouse gas emissions and im- proving flexibility in modern power systems. This study develops a bi-level optimization model to examine how prosumers maximize profit through peer-to-peer (P2P) energy trading with consumers and the grid, and how consumers minimize cost by leveraging P2P trading. The bi-level problem is reformulated as a single-level mixed-integer programming (MIP) model using Karush- Kuhn-Tucker (KKT) conditions to improve tractability and preserve market-clearing behavior. For the model validation and case study development, prosumer and consumer data are …

Numerical Analysis And Simulation Of Enhanced Performance In Nanowire Cds/Cdte Solar Cells: A Pathway To Greater Than 25% Efficient Cdte Solar Cell, Riasad Badhan

Theses and Dissertations--Electrical and Computer Engineering

This Thesis finds a pathway to a significantly high-efficient CdTe based solar cell by demonstrating and harvesting the advantages of a nano-structure configuration in CdTe based solar cells. Nanowire CdS window layer and the “control”, planar CdS window layer films were fabricated in the laboratory and compared for their optical transmission and other characteristics affecting the performance of the CdS-CdTe solar cell. Numerical simulations were performed for a comparative evaluation of the embedded nanowire CdS-CdTe solar cell device and the traditional planar CdS-CdTe solar cell device. Experimentally measured spectral transmission of nanowire CdS film was used in the simulation environment. …

Robotizing Complex Welding Processes Through Imitation Learning And Generative Models From Human Demonstration, Yue Cao

Theses and Dissertations--Electrical and Computer Engineering

Arc welding processes demand real-time adaptive control that current robotic systems cannot achieve autonomously. This dissertation develops a systematic framework to robotize complex welding by learning from human demonstration, integrating generative modeling, physics-informed reconstruction, and model-based imitation learning. First, human--robot collaboration systems are established for both Gas Tungsten Arc Welding (GTAW) and Double-Electrode Gas Metal Arc Welding, combining robotic teleoperation with virtual reality interfaces to capture high-quality operator demonstrations. Second, a physics-informed neural network framework reconstructs complete molten pool flow fields from high-speed imaging, enriching process understanding beyond direct sensor observation. Third, generative models, including a hybrid latent variational autoencoder …

Design Of Energy-Efficient, Scalable, And Flexible Tensor Processing Architectures With Electro-Photonic Integrated Circuits, Oluwaseun Alo

Theses and Dissertations--Electrical and Computer Engineering

In recent years, artificial intelligence has achieved remarkable success across domains such as computer vision, natural language processing, and scientific computing. This progress has been driven largely by advances in deep learning, particularly deep neural networks (DNNs), including convolutional neural networks (CNNs) and transformer-based models. While these models deliver unprecedented accuracy, often surpassing human performance, their computational complexity continues to grow rapidly due to multibillion- and trillion-parameter designs. As model sizes and deployment scales expand, the demand for energy-efficient and high-throughput hardware accelerators has intensified. Conventional electronic platforms based on CPUs, GPUs, ASICs, and FPGAs are increasingly constrained by the …

Efficient And Fair Resource Unit(Ru) Allocation Methods For The Ofdma Mechanism Under Ieee 802.11ax, Yang Yu

Doctoral

The IEEE 802.11ax standard was approved in February 2021. This standard allows users to access different channel bandwidths to transmit their packets under the Orthogonal Frequency Division Multiple Access (OFDMA) mechanism. As the number of Internet users and the number of Internet applications increase, the allocation of channel resources has been a challenge in WLANs. Different types of applications, such as real-time video conferencing, online gaming and large-scale data transfers, generate different requirements in terms of throughput, latency and reliability. Consequently, the diversity in users’ channel bandwidth demands is increasing. Under the OFDMA mechanism, the packets can be allocated into …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs’ consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs’ responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model’s output. The LLM-CXR model is selected as the medical …

Nanomagnet Based Reservoir Computing And Quantum Control, Fahim F. Chowdhury

Theses and Dissertations

Conventional CMOS scaling has driven remarkable advances in computing but faces increasing physical and energy constraints, motivating alternative computing paradigms that integrate memory and computation while improving energy efficiency. Nanoscale magnetic systems offer a promising platform for such approaches because their intrinsic nonlinear dynamics and localized magnetic fields can support both classical and quantum information processing. This thesis investigates nanomagnetic systems for physical reservoir computing and, with primary emphasis, for localized quantum control of spin qubits.

The first part explores dipole-coupled nanomagnet arrays as physical reservoirs. Micromagnetic simulations demonstrate nonlinear dynamical behavior with high short-term memory and parity-check capacity, enabling …

Element-Based Predictive Modeling Of Hydrothermal Liquefaction Bioproducts Derived From Corn Stover, Isamu Umeda, Meicen Liu, Yi Zheng, Jiefu Wang, Zhiwu Wang, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

The hydrothermal liquefaction (HTL) process offers an energetic advantage over pyrolysis because it does not require prior drying of the biomass feedstock. However, there are significant challenges in simultaneously estimating both the yields and characteristics of products from the HTL of biomass with theoretical support. This study developed a unique element-based kinetic model to predict the yields, higher heating values, and fuel characteristics of solid residue and heavy bio-oil, based on the temperature, residence time, solid loading, and elemental composition (C, H, N, and O) of corn stover. Furthermore, the model predicted the weights of dissolved carbon and nitrogen in …

A Comprehensive Survey Of Prompt Engineering Techniques In Large Language Models, Tonmoy Debnath, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Prosenjit Das, Antu Kumar Guha, Muhammad Rezaur Rahman, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

Prompt engineering has arisen as a pivotal discipline in optimizing the performance of Large Language Models (LLMs) by structuring inputs to enhance coherence, accuracy, and task alignment. This paper comprehensively surveys various prompting techniques, systematically categorizing them according to their application domains and methodological foundations. Fundamental approaches like zero-shot and few-shot prompting are examined along with advanced strategies, including chain-of-thought reasoning, retrieval-augmented generation, and self-consistency mechanisms. A rigorous qualitative analysis is conducted to evaluate each technique's strengths, limitations, and optimal use cases, offering a structured framework for selecting the most effective prompting strategies. Theoretical insights and empirical findings are consolidated …

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …