Engineering Commons^™

Photonic Crystal Devices For Chip Scale Sensing Systems, Yudong Chen

Electrical Engineering Dissertations - Archive

This thesis investigates the design and integration of photonic crystal (PC) structures for compact, high-performance optical platforms, with a focus on applications in gas sensing, on-chip lasers, and flat optics. Chapter 1 introduces the fundamental principles of PC design and simulation, highlighting their potential to replace bulky components in micro-gas chromatography (µGC) systems through miniaturization and integration. Chapter 2 explores PC-based nanobeam lasers, including the Lambda-Scale Embedded Active-Region Photonic Crystal (LEAP) laser, which demonstrates strong optical confinement and energy-efficient operation, with energy consumption as low as 8 fJ/bit. These laser designs are evaluated for their suitability in low-power, high-speed on-chip …

Advancing Machine Learning Approaches Through Robust Methodologies In Llm Code Generation, Adversarial Text Classification, And Unsupervised Learning, Anahita Samadi

Computer Science and Engineering Dissertations - Archive

This dissertation combines insights across text, code, and image modalities to advance the robustness, efficiency, and adaptability of machine learning models. Specifically, we address challenges like adversarial vulnerability in text, the impact of test strategies on code generation, and dimensionality in image representation in unsupervised learning domain. These efforts highlight pipelines for designing machine learning systems that are not only efficient, but also adaptable to complex environments. In addition, these efforts together help form the basis for a multimodal AI capable of thriving in medical applications that this dissertation prototypes for future efforts.

Optimizing Architecture And Software For Next-Generation Memory Systems, Lingfeng Xiang

Computer Science and Engineering Dissertations - Archive

The rapid advancement of memory technologies presents new challenges and opportunities for system software and architectural design. This dissertation investigates how to optimize modern computing systems for next-generation memory, mostly focusing on persistent memory and Compute Express Link (CXL)-based memory. First, we conduct a detailed characterization of Intel Optane DC Persistent Memory, identifying the distinct behaviors of its on-DIMM read and write buffers and analyzing their impact on application performance. These insights motivate optimizations that decouple read and write paths, revealing that random read latency—especially in pointer-chasing workloads—is a dominant performance bottleneck. Second, we present NOMAD, a page management framework …

Medical Ai: Solving Healthcare Challenges And Inspiring Ai Innovation, Xiaowei Yu

Computer Science and Engineering Dissertations - Archive

Artificial Intelligence (AI) is transforming healthcare by enabling large-scale analysis of medical data and integrating multimodal information for more comprehensive diagnostics. I present my work addressing fundamental and challenging problems in developing state-of-the-art AI models for medical data analysis, including multimodal brain data and other medical datasets. Additionally, I design brain-inspired AI models by integrating insights from organizational principles of brain networks. Specifically, my research tackles three critical aspects: (1) AI in Computational Neuroscience, where I design deep learning models for brain network analysis to uncover the organizational principles of brain networks; (2) Brain-Inspired AI, where I integrate superior brain …

3d Perception, Mapping, And Navigation For Mobile Cobot, Tuan T. Dang

Computer Science and Engineering Dissertations - Archive

Service robots are migrating from tightly controlled factory lines into offices, hospitals, and homes, where they must perceive, remember, and act amid people, clutter, and perpetual change. Humans solve this daily by forming compact, task-relevant “cognitive maps”: we sample just enough sensory detail to guide the moment, stitch those snapshots into a sparse topological scaffold, and continuously refine it as we move. Guided by that insight, this dissertation proposes a biologically inspired mapping framework that turns partial RGB-D observations into a hybrid temporal-spatial memory—locally metric for centimeter-scale navigation yet globally topological for room-to-building navigation. The system first distills raw depth …

Breaking Granularity Barriers: Overcoming I/O Abstraction Limitations For High-Performance Storage Systems, Chen Zhong

Computer Science and Engineering Dissertations - Archive

Modern storage hierarchies exhibit performance differences spanning eight orders of magnitude. Each tier in the hierarchy presents fundamentally different optimal access sizes and patterns. Most systems read and write data in fixed-size units across different tiers, typically power-of-2 sizes. It simplifies data management but also suffers from large write amplification when handling small accesses in many real-world workloads. This fundamental disconnect between fixed-size I/O design assumption and real-world usage patterns represents the core challenge.

The storage community has recognized the limitations of fixed-size I/O abstractions and is exploring alternatives, like the new emerging NVMe-KV interface and object-based storage, which aim …

Environment And Intention Awareness For Navigation And Collaboration, Bhaskar Chandra Trivedi

Computer Science and Engineering Dissertations - Archive

Unmanned Aerial Systems (UAS) have become increasingly popular as versatile platforms for tasks such as surveillance, inspection, delivery, and maintenance. In many applications, UAS operate in environments frequented by people or containing sensitive infrastructure, which introduces physical risks in case of vehicle failure, as well as psychological and privacy concerns that may limit their acceptability. Ensuring safe and efficient operation thus requires that UAS consider these risks when planning navigation strategies. While prior information, such as city maps and building layouts, can partially inform risk assessment, such data is often incomplete, necessitating real-time augmentation of risk maps using sensor information. …

Graphene-Polymer Nanocomposite For Electromagnetic Interference Shielding, Ravi Venkata Surya Sai Mogilisetti

Mechanical and Aerospace Engineering Theses - Archive

Polymers have widespread usage in most industries, such as aerospace, automotive, telecommunications, and medicine, mainly because they have a positive lightweight nature and excellent mechanical properties. One significant advantage of polymeric materials is their ability to combine nano-fillers, greatly enhancing their mechanical, electrical, and thermal properties. In the category of polymer matrices, polypropylene (PP) is notable for its low cost, ease of processing, and balanced mechanical properties. However, its relatively lower modulus and strength limit their applications in high-performance engineering. This research explores the addition of graphene into polypropylene to improve its mechanical properties and establish a conductive network for …

Materials Reliability In Direct-To-Chip Cooling: A Systematic Study Of Aluminum Corrosion In Next-Generation Data Center Coolants, Fnu Harish Gangadhara

Mechanical and Aerospace Engineering Theses - Archive

Data centers are rapidly scaling to support artificial intelligence, cloud platforms, and other high-performance workloads, driving a sharp increase in chip and rack power densities that are now approaching, and in some cases surpassing, 50–100 kW per rack. In response, direct-to-chip liquid cooling has become a key enabling technology for managing these extreme thermal loads, yet the durability of materials in contact with the coolant remains a major reliability concern over system lifetimes. Copper has traditionally been used for cold plates and cooling-loop components, but its relatively high cost, mass, and supply-chain uncertainty are motivating a shift toward aluminum as …

Comparative Life Cycle Assessment Of Conventional Open-Cut Pipeline Replacement With Trenchless Cured-In-Place Pipe Renewal Method For Wastewater Applications Using Midpoint Approach, Eesha Nilesh Karkhanis

Civil Engineering Theses - Archive

Underground infrastructure development has a significant impact on society, leading to continuous technological advancements. With the rising environmental concerns, novel technology is leaning towards adapting to sustainable practices for pipeline rehabilitation. Conducting a comparative study of environmental impacts produced by pipe renewal and replacement processes is a vital step towards sustainable development of underground infrastructure. Open-cut Pipeline Replacement (OCPR) is the conventional method used for pipeline rehabilitation, which involves the excavation of the ground surface to place a new pipe underground or replace an existing one. This process includes the trenching of ground, followed by surface reinstatement through backfill. The …

Assessment Of Long Term Durability Of Prefabricated Frp Strip Systems For The Rehabilitation Of Concrete, Karunya Kanagavel

Civil Engineering Theses - Archive

Fiber Reinforced Polymer (FRP) composites provide an extremely effective means of rehabilitating deteriorating and understrength concrete elements due to their characteristics of high specific strength and stiffness, corrosion resistance, and potential long-term durability, lightweight nature, and ease of placement in the field. Despite significant use of these materials, there is still a lack of long-term durability data. With this in mind, the current study investigates the impact of environmental exposure and aging on 3 commercially available prefabricated carbon fiber reinforced composite strips and their recommended adhesives used in externally bonded rehabilitation with the aim of providing a comprehensive set of …

Development Of A Design Tool For Tow-Steered Composite Structures With Machine Learning-Assisted Modeling, Bangde Liu

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Fiber-reinforced composites (FRCs) are widely used in aerospace, automotive, and other engineering applications due to their lightweight characteristics and superior mechanical properties. Traditional FRCs employ a fixed fiber orientation in each layer, and while different layup sequences can tailor performance, the mechanical properties remain spatially uniform. Tow-steered composites, which enable fibers to follow curvilinear paths, offer the potential for spatially varying stiffness and strength, improving structural performance.

This dissertation addresses key challenges in modeling and designing tow-steered composite structures, including the lack of commercial design tools, the high computational cost of design optimization, and the need to efficiently evaluate manufacturing …

Characterization And Profile Considerations Of Nickel-Zinc Energy Storage Under High-Power And Pulsed Loads, Benjamin P. Schmitz

Electrical Engineering Theses - Archive

There are many types of energy storage devices that are available for driving high-power electrical loads. Choosing the right chemistry is difficult and factors such as energy density, power density, safety, cycle life, and recharge rate are among the many that must be considered. Lithium-ion batteries (LIB) possess the highest combined power and energy density, making them an attractive option for many applications. Previous studies at the Pulsed Power and Energy Lab (PPEL) characterized lithium-iron-phosphate (LFP) and lithium-titanate-oxide (LTO) battery chemistries. LFP’s and LTO’s have modest power density, modest energy density and modest cycle life. However, there is still potential …

Evaluation Of Electric Vehicle Batteries For Enabling High Power Loads, Maxton K. Manker

Electrical Engineering Theses - Archive

The growing demand for high-power energy storage systems in applications such as artificial intelligence (AI) data centers, industrial backup systems, and grid-level stabilization efforts presents new challenges in technology selection. These loads have a uniquely high continuous or transient power demand that can impact the stability of the electric grid. To mitigate these challenges, energy storage in the form of batteries or supercapacitors has been proposed either as stand-alone or as intelligently controlled grid buffering sources. These same types of energy storage are commonly found in electric vehicles (EV) where they must respond to abrupt throttle and braking behavior, similar …

Smart Irrigation System Using Iot And Lstm For Optimal Water Management, Farley Y. Ruiz

Electrical Engineering Theses - Archive

This thesis presents the design and implementation of a smart irrigation system that combines Internet of Things hardware with a Long Short-Term Memory (LSTM) neural network for predictive soil moisture management. The goal is an affordable and reliable solution that uses real-time sensor data and environmental data to schedule irrigation before the substrate moisture drops below its target range. The system integrates soil moisture, temperature, humidity, and sensors on an Arduino Nano that communicates wirelessly with a Raspberry Pi. The Raspberry Pi runs a Python/Flask backend that collects and processes data, executes the LSTM model, and serves a secure web …

Power Quality Event Diagnosis Using Multi-Rate Neural Networks, Jordan D. Lloyd

Electrical Engineering Theses - Archive

Power quality disturbances (PQDs) are among the primary challenges facing modern electrical systems, as they degrade the performance and lifespan of connected equipment. This thesis investigates the relationship between the rate at which voltage waveform data are sampled, the reliability of these measurements, and the ability of deep neural networks to classify PQDs accurately. A one-dimensional convolutional neural network (CNN) was trained and evaluated across multiple sampling rates and signal-to-noise ratios to quantify how information loss in the temporal and spectral domains affects classification reliability. The results demonstrate that model accuracy degrades nonlinearly as sampling rate and signal-to-noise ratio (SNR) …

Immersive Executive Functions Assessment System (Iexec): Integrating Embodied Cognition And Virtual Reality, Hamza Reza Pavel

Computer Science and Engineering Dissertations - Archive

Executive functions (EFs) are higher-order cognitive processes that include working memory, inhibitory control, and cognitive flexibility. These higher-order processes facilitate the achievement of goal-directed behavior and enable both adaptive decision-making and emotional regulation. Traditional EF assessment tools depend on static pen-and-paper tasks or basic computer-based tasks, which fail to capture real-world cognitive complexity and dynamics. Some of these assessment tools are specifically geared towards children or older adults, while others are more generic and designed to be used for people of all ages. This dissertation addresses these limitations by introducing iExec: The Immersive Executive Functions Assessment System, which functions as …

Enabling Energy And Water Sustainability Through Out-Of-Band Emi Sensing And Infrastructure Modeling, Pranjol Sen Gupta

Computer Science and Engineering Dissertations - Archive

As demand for Internet and cloud services surges, data centers have emerged as critical infrastructure—but they are also among theworld’s most energy- andwater-intensive facilities. Effective power management, particularly at the server level, is essential for improving efficiency, reliability, and sustainability. However, server-level power monitoring remains uncommon due to the high cost of hardware instrumentation and the intrusiveness of software-based solutions, especially in shared colocation environments. My research introduces a novel, low-cost, and non-intrusive method for server-level power monitoring using conducted electromagnetic interference (EMI). By analyzing EMI signals captured from higher levels in the power distribution network, this approach estimates individual …

Plasmonic Nanopore Sensing For The Characterization Of Viruses And Biomolecules, Scott Renkes

Bioengineering Dissertations - Archive

The rapid advancement of nanomedicine has enabled increasingly precise nanotherapeutic platforms, including targeted nanoparticles, monoclonal antibodies, and viral gene delivery vectors. As these technologies mature, quality control and analytical characterization have emerged as critical bottlenecks, particularly in systems where functional outcomes depend on one-to-one molecular or particle–biological interactions. Conventional ensemble-averaged techniques obscure heterogeneity that is often central to therapeutic efficacy, safety, and manufacturability. A prominent example is adeno-associated virus (AAV)–based gene therapy, where production yields heterogeneous populations of empty, partially loaded, and fully loaded capsids. Genome fill percentage and integrity directly influence therapeutic efficacy and dosing accuracy, while limited understanding …

Life Cycle Assessment Approach For Trenchless Cured-In-Place Pipe Sewer Renewal Method, Shiva Mandari

Civil Engineering Theses - Archive

The advancement of underground infrastructure is vital to the development of modern society and continues to inspire technological progress. As environmental concerns grow, innovative approaches to pipeline rehabilitation are increasingly emphasizing sustainability. Assessing and contrasting the environmental effects of renewing existing pipelines versus complete replacement is key to fostering eco-conscious improvements in subsurface utility systems. Cured-in-Place Pipe (CIPP) is a commonly used trenchless method for rehabilitating pipelines. It involves inserting a flexible liner, saturated with resin, into the existing pipe. This insertion can be achieved through inversion using air or water pressure, or by mechanically pulling and inflating the liner. …

Characterization Of Dc Arc Flash Events Generated By Electrochemical Energy Storage, Nicolaus E. Jennings

Electrical Engineering Dissertations - Archive

The increasing rise in the use of electrochemical energy storage (ECES) like in the form of valve regulated lead acid (VRLA) batteries, lithium-ion (Li-ion) batteries, electric double layer capacitors (EDLC), and metalized film, oil filled capacitors prompt new challenges concerning electric worker safety. The primary safety hazards associated with ECES are electric shock and arc flash. The electric shock hazard is well understood to the extent where it is known what potential and exposure duration will cause levels of pain and ultimately fatality. Various personal protective equipment (PPE) like insulating gloves allow electric workers to perform maintenance with sufficient protection …

Enhanced Load Detection With Data-Driven Appliance Signatures Using Mixed Integer Linear Programming In Non-Intrusive Load Monitoring, Marina Materikina

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Despite the numerous research studies and interest in the non-intrusive load monitoring (NILM) area to improve energy efficiency, the problem of accurate and precise disaggregation of electrical devices has not been solved yet. The goal of our research is to build a method with a focus on higher accuracy on complex state-based appliances, which most approaches struggle to detect due to their power signal complexity and low consumption. Our approach is NILM with data-driven signatures (DS), with the ability to potentially predict power usage over time that would work great for suitable applications such as demand response, anomaly detection, and …

‘Waves Of Imagination’ Unconditional Spectogram Diffusion Using Diffusion Architecture., Rahul Vanukuri

Computer Science and Engineering Theses - Archive

The swift evolution of wireless communication technologies,particularly in the field of rf signals or in CBRS bands,demands increasingly sophisticated signal processing techniques to ensure efficient transmission, reception, and spectrum management.Traditional approaches to signal generation and reconstruction, although effective in controlled environments, often struggle to cope with the challenges presented by real-world noisy conditions, hardware constraints, and limited access to large-scale datasets. In response to these limitations, this thesis explores the application of diffusion models—a class of generative models known for their ability to produce high-fidelity samples—to the domain of spectrogram generation for communication signals.

Different from conventional strategies to simulate …

Characterization Of Cancer Cell Migration Through Brain Vascular Endothelium Model, Malak Taysser Al-Noubani

2025 Fall Honors Capstones Projects - Archive

One of the hallmarks of cancer is increased vessel growth to feed the tumor’s rapid expansion. The newly formed blood vessels are immature and often leaky due to structural and functional abnormalities. This leads to ineffective anti-cancer drug delivery and provides tumor cells with additional opportunities to metastasize. We propose to develop an in vitro vascular endothelium model and introduce aggressive triple-negative breast cancer (TNBC) cells to mimic the tumor environment, utilizing a Transwell migration assay. The impact of TNBC cells on vessel permeability will be assessed by staining for tight junction proteins, and the migratory capabilities of TNBC cells …

Representation Learning Of Point Cloud Data For Process Mining And Anomaly Detection In Complex Systems, Yujing Yang

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Complex systems, e.g., advanced manufacturing systems, are largely associated with dynamic and transient behaviors, resulting in condition changes and anomalies. Sensor-based condition monitoring is critical in detecting anomalies and supporting process monitoring and performance improvement for complex manufacturing systems. Traditional sensor-based monitoring approaches primarily focus on one-dimensional (1D) signals and two-dimensional (2D) images, which are limited in their ability to capture high-resolution spatial patterns pertaining to anomalies induced by systems’ condition changes, especially subtle ones. Recent advancements in three-dimensional (3D) sensing present a unique opportunity to address this limitation by enabling the capture of 3D point cloud data with micro-level …

Study Of Deep Neural Network Trained With Salient, Compressed Medical Video Data For Enhanced Predication, Aileen Sengupta

Electrical Engineering Dissertations - Archive

The rapid growth of surgical video analysis presents a need for efficient deep learning models for surgical training, while reducing the need for excessive image and video image storage. Traditional training approaches typically rely on uniformly compressed video data, instead of selectively preserving the most surgically relevant regions. This dissertation investigates the impact of training deep neural networks (DNNs), both convolutional and transformer-based architectures, on saliency-guided, differentially compressed surgical video sequences. The study systematically evaluates how such compression influences prediction accuracy, computational efficiency and storage requirements. Experimental results demonstrate that models trained on ROI-focused compressed data combined with motion vectors …

Correlation Of Internal Pressure To The Fundamental Aging Mechanism Of Li-Ion Batteries, Kayla Garcia

Electrical Engineering Theses - Archive

As technology continues to evolve, the demand for more reliable and longer-lasting batteries is growing rapidly in the electronics industry. Batteries are vital for powering a wide range of technologies, from smartphones and consumer electronics to automotive systems and high-end tools used across multiple sectors. Lithium-ion batteries (LIBs) have helped bridge the power and energy gap that these different technologies require while achieving sufficient efficiency and reliability to make carrying them around feasible and long lasting. To further enhance the performance and longevity of a these devices, a deeper understanding of the degradation mechanisms occurring inside LIBs is crucial. The …

Coastal Flooding Along The Lower Brazos During The Landfall Of Hurricane Beryl -A Model-Based Investigation, Sabiha Tasnuva Khan

Civil Engineering Theses - Archive

Hurricane Beryl generated a complex hydrodynamic response along the Texas coast and Lower Brazos River, producing storm surge, elevated coastal water levels, intense rainfall, and widespread inundation. Low-gradient coastal rivers such as the lower portion of the Brazos River are particularly sensitive to the interaction of these drivers, yet the inland decay of surge energy and its interplay with watershed runoff remain poorly quantified. This study aims to characterize the physical mechanisms controlling water-level amplification, flow reversal, surge attenuation, and inundation development during Hurricane Beryl along the Lower Brazos and to determine the relative contributions of surge and rainfall to …

Citizen-Centric Building Energy Retrofits: Understanding And Supporting Citizens As Occupants, Participants, Decision-Makers, And Learners In Home Energy Retrofits, Nikhil Singh Yaduvanshi

Civil Engineering Dissertations - Archive

Residential building retrofits remain significantly under-adopted despite substantial technological advances, economic incentives, and policy efforts, creating a critical gap between technical potential and actual implementation in achieving climate goals. Assessment of citizen involvement in building retrofit processes plays a critical role in formulating effective home retrofit program designs to ensure maximum adoption rates and avoid energy waste. Although, existing retrofit programs and decision-making models recognize the importance of citizen involvement, the extent of citizen capabilities and the effects of citizen-centered approaches on retrofit adoption and building performance has not been comprehensively examined. The adoption and success of retrofit programs depends …

Assessment Of The Feasibility Of Utilizing Plastic Waste In Infrastructure To Promote Circular Economy In Bangladesh, Md Lutfor Rahman

Civil Engineering Dissertations - Archive

This study presents a comprehensive assessment of municipal solid waste (MSW) and plastic waste characterization across Bangladesh, with a focus on circular economy opportunities and the long-term economic viability of plastic road. Using on-site waste characterization data for 13 major cities from four geographic zones of Bangladesh —Northwest, Northeast, Southwest, and Southeast—the research identifies food waste as the dominant component of the national waste stream (67.3%), followed by plastic (12.4%), textiles (7.8%), and paper (4.7%). Among plastics, low-density polyethylene (LDPE) overwhelmingly dominates (89.7%), highlighting the continued prevalence of single-use flexible plastics.

A life cycle cost analysis (LCCA) was conducted comparing …