Computer Engineering Commons^™

Maya Roots, Erin Schmidt, Megu Kanzawa

Computer Science and Engineering Senior Theses

This project focused on the continued development of Maya Roots, a mobile and web-based platform designed for farmers in Tahcabo: a rural agricultural community located in Yucatán, Mexico. Yucatán faces unique agricultural challenges due to its karst limestone terrain and highly variable land conditions that can significantly impact farming outcomes. At the same time, traditional agricultural knowledge such as Milpa farming practices is increasingly at risk of being lost across generations. These environmental and cultural challenges highlighted the need for a portable, accessible system that could preserve agricultural knowledge, improve access to geospatial information, and strengthen communication between farmers and …

Hyperdimensional Computing For Edge And Mobile Devices, Colin Eddy Dupuis

Masters Theses

This thesis presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input. The proposed frameworks utilize HDC’s simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging …

Jsd: Novel Methodology For Synthetic Data Evaluation, Jeffrey Lane, Scott Wang, Vincent Chang, Bojun Zhang

Computer Science and Engineering Senior Theses

The proliferation of sensitive Personally Identifiable Information (PII) on dark web marketplaces has created an urgent need for robust data protection systems, especially for vulnerable populations such as minors. Traditional PII redaction often fails to identify implicit privacy risks—such as author gender indicators or non-fictional child-related context—hidden within large-scale e-commerce datasets. This paper presents JSD, a dual-stage framework for the detection and protection of sensitive text data. The Detection phase utilizes Transformer and CNN-based architectures and Human-in-the-Loop AI to surpass the "semantic ceiling" of traditional NER approaches, enabling context-aware identification of implicit PII. The Protection phase introduces GASE (Genetic Algorithm …

Hemlock, Ephraim Esson, Ambrose Vellequette, Geno Meschi

Computer Science and Engineering Senior Theses

Hemlock is a tool designed to protect musicians from having their work used to train generative AI models without their consent. It works by adding carefully crafted inaudible noise to audio files that disrupts the ability of AI models to learn from them — a technique known as adversarial perturbation. Our system targets three different types of AI model simultaneously: a Music Information Retrieval (MIR) classifier, a sequential audio generation model (Mel-LSTM), and Meta’s AudioCraft, a transformer-based music generator. Testing in twenty songs showed an average 15% reduction in the MIR model’s classification confidence, a 59% increase in Mel- LSTM …

6tisch Based Sensing Network For Smart Agriculture, Riley Heike, Griffin Jones, Justin Odo, Jalen Paige, Rosalie Wessels

Computer Science and Engineering Senior Theses

This project investigates 6TiSCH (IPv6 over Time-Slotted Channel Hopping), a relatively recent IETF networking standard introduced in 2013 that combines deterministic TSCH scheduling, 6LoWPAN header compression, and RPL mesh routing to enable low-power, reliable, multi-hop wireless communication for IoT deployments. Despite its strong theoretical properties, 6TiSCH remains underexplored in practice, and real-world questions around configuration, scalability, power behavior, and end-to-end integration are not well documented. Our primary goal was to build and operate a working 6TiSCH network, characterize its performance through iterative testing, and understand what it takes to go from raw packet delivery to a complete data pipeline.

To …

Mimica, Sean Lai, Gurprasaad Hora, Stephanie Campos

Computer Science and Engineering Senior Theses

Language barriers remain a significant obstacle to natural human communication, limiting access to healthcare, business, travel, and daily social interaction for billions of people worldwide. Existing translation solutions such as smartphone applications and earpiece devices address the functional problem of converting words between languages but fail to preserve the speaker’s voice identity, require hands-on interaction, or depend on proprietary device ecosystems. These limitations disrupt the natural flow of conversation and reduce the human quality of cross-lingual communication.

Mimica is a real-time wearable translation necklace designed to address these shortcomings. Built around an ESP32-S3 microcontroller with an integrated microphone and speaker, …

Trim-Transfer: A Transfer Learning Approach For Cross-Trim Level Can Intrusion Detection, Baylor J. Whitehead

Master's Theses

Modern vehicles contain many Electronic Control Units (ECUs) that communicate through CAN. While CAN enables efficient data communication, it lacks built in authentication and encryption, allowing adversarial actors to inject malicious CAN messages. This limitation has motivated the development of CAN intrusion detection systems (IDS). However, deploying IDS across a vehicle lineup requires collecting large labeled datasets and retraining models, increasing development cost and limiting scalability.

This thesis investigates the use of transfer learning with LSTM-based deep neural networks to reduce retraining cost while maintaining model detection performance. A baseline LSTM model is trained using CAN data from a base …

A Study On Quantization And Hardware Cost Tradeoffs In A 5g Nr Ldpc Decoder On Fpga, Giancarlo Acosta

Master's Theses

The fixed-point implementation of a 5G New Radio LDPC decoder forces a tradeoff between precision and hardware cost, governed by the variable node word length W_L, the check node message width W_R, and the normalized min-sum correction factor α. This thesis characterizes how these three parameters affect both error correction performance and FPGA resource utilization for an LDPC decoder on an established LDPC decoder architecture. A bit-accurate MATLAB core model records bit error rate (BER) and frame error rate (FER) while a verified HDL Coder model generates synthesizable VHDL for Vivado synthesis, and both are swept …

Trustworthy Intelligence Fusion For Search And Rescue: Designing Grounded And Secure Multi-Agent Ai For Mission Decision Support, Yayun Tan

Master's Theses

Search and rescue (SAR) operations require teams to integrate uncertain information under severe time pressure. Large language model (LLM)-based multi-agent systems (MAS) can support decision-making, but they also risk producing hallucinated outputs and processing unreliable or malicious data. This thesis addresses these risks through three linked studies. First, it proposes a modular eight-agent SAR MAS architecture that reflects the structure of real SAR missions by assigning specialized roles to different agents. Second, it introduces a post-hoc probabilistic verification framework that checks LLM agent outputs against a probabilistic knowledge graph built from historical SAR incidents.  Third, the thesis examines indirect adversarial …

Integrating Sustainability Into Engineering Education, Riley R. Moller

Master's Theses

Engineering decisions shape lasting technology that affects environmental integrity, public safety, economic stability, and social equity. As global challenges such as climate change, infrastructure vulnerability, and rapid technological advancement intensify, the responsibilities placed on engineers continue to expand. Sustainability provides a framework for addressing these interconnected pressures through systems-based design and long-term thinking. Yet, sustainability education within engineering programs remains unevenly integrated, often positioned as elective or peripheral rather than as a foundational component of professional preparation.

Prior research shows that sustainability is most frequently addressed through stand-alone courses rather than embedded across required curricula, reflecting disciplinary structures that prioritize …

Reproducing And Evaluating Charger Surfing: Robustness Of Smartphone Charging-Line Side-Channels, Colby M. Watts

Master's Theses

Smartphones are frequently connected to external, untrusted charging hardware, creating opportunities for side-channel attacks that do not require malware or direct access to device data. Charger Surfing, a recently proposed charging-line power analysis side-channel attack, reported high accuracy in inferring touchscreen input from voltage measurements collected from a smartphone’s charging cable; however, the reproducibility and robustness of these results under different conditions remain unclear. This thesis presents an independent replication and evaluation of Charger Surfing, including the development of an end-to-end data collection pipeline consisting of a modified charging cable, oscilloscope-based recordings, custom Android app, automated trace processing, and convolutional …

Preserving Structural Alias Information Across The Mlir-To-Llvm Lowering Boundary, Shravan Sheth

Master's Theses

Machine learning training and inference workloads run at massive scale, where the efficiency of generated machine code directly affects throughput and energy consumption. The compilers that lower model specifications to hardware instructions rely on optimization passes that can only exploit information visible in the representations they operate on. MLIR, the intermediate representation framework underlying production machine learning compilers such as IREE and Triton, is designed so that each abstraction level can encode semantics that lower levels cannot represent. One example is memref.subview, which partitions a buffer into typed regions with explicit offsets and sizes, making structural non-overlap provable from the …

Vision-Guided Motion Planning For Autonomous Catch With A Robotic Arm, Kayla Go-Oco, Ashik K. Islam, Raegan Gritzmacher

Electrical Engineering

Modern robotic systems are often evaluated using static and highly controlled tasks, such as pick-and-place demonstrations, which do not fully represent the uncertainty and adaptability required in real-world environments. A major challenge in robotics research is enabling robotic systems to perceive, track, and respond to dynamic objects in real time while maintaining accurate and reliable motion control. This project addresses these challenges by developing an autonomous robotic platform in which an OpenMANIPULATOR-Y robotic arm detects, tracks, and attempts to catch a moving tennis ball using a vision-guided control system. The system integrates YOLO-based object detection with an Intel RealSense D455 …

Xylem: A Comparative Analysis Of Gpu Dispatch Pipelines For Large-Scale, Procedural Environments, Srinivas Sundararaman

Master's Theses

The real-time rendering of large-scale, procedural scenes presents a significant performance challenge for traditional CPU-bound rendering pipelines. The high volume of draw calls and the need for complex culling and level-of-detail management create bottlenecks that limit scene complexity and visual fidelity. This thesis investigates the evolution of GPU-driven rendering paradigms via the Xylem renderer within NVIDIA’s Donut rendering framework as a solution to these challenges.

A comprehensive benchmarking framework is developed to implement and quantitatively analyze three distinct rendering strategies for a procedurally generated, parameterizable, large-scale forest scene. The evaluated pipelines include: (1) traditional instanced rendering, (2) compute-driven indirect rendering …

Autonomous Vision-Based Litter Collection Rover, Dante Michael Benedetti, Benjamin Scott Tavares, Nathan Heil

Electrical Engineering

This report documents the design, implementation, and testing of an autonomous litter-collection rover developed as a Senior Project Design Lab (EE 460/463/464) at California Polytechnic State University. The rover integrates autonomy, computer vision, embedded real-time control, mecanum-wheel omnidirectional mobility, and a two-degree-of-freedom robotic arm to detect, approach, and collect small ground-level litter such as bottles, wrappers, and paper fragments.

The system uses a two-layer compute architecture: an NVIDIA Jetson Orin Nano running ROS 2 for perception, SLAM, and path planning, paired with an STM32L4A6ZG microcontroller for real-time motor control and odometry. The robot is built on a multi-level aluminum frame …

Solving Linearly Constrained Quadratic Programs Using Field Programmable Analog Arrays, Tyler Wynn, Alonzo Arroyo

Electrical Engineering

This paper presents a field-programmable analog array (FPAA) implementation for solving linearly constrained quadratic programs (LCQPs) directly in the analog domain. The solver is based on a continuous-time primal-dual control architecture with integral action, anti-windup compensation, and a piecewise-linear nonlinearity for enforcing affine inequality constraints. A switched-capacitor implementation using three AN231E04 FPAAs is developed, and coefficient scaling methods are introduced to keep internal and output signals within the voltage limits of the hardware. A global scaling factor is used to reduce internal signal excursions, while solution-space scaling is shown to modify the implemented optimization coefficients and alter the local closed-loop …

Integration Of Robotic Arm And Conveyor With Programmable Logic Controller, Drake A. Small

Master's Theses

To meet new curriculum demands brought on by Cal Poly's upcoming switch to semesters, a new, cross-disciplinary lab module was developed for EE 435 (Industrial Power Control and Automation). The module emphasizes career-applicable skills, preparing students for the field of controls engineering within the manufacturing industry. These skills include robotic control, computer networking and configuration, and embedded systems. The work focused on integrating a collaborative robot arm to pick-and-place boxes on a conveyor. A myCobot 320 Pi and an Ultimation Powered Roller MDR Conveyor were integrated with the existing PLC system using Modbus RTU and EtherNet/IP communication protocols, respectively. A …

Teaching Multi-Core Architecture: Design And Implementation Of A Cache-Coherent Cpu For Undergraduate Education, Isaac R. Lake

Master's Theses

Modern computing has relied on multicore processors for high performance for nearly two decades, yet undergraduate computer engineering curricula often provide limited exposure to parallel hardware architectures and their design challenges. This thesis presents the design of CPE 433, a course that extends the pipelined and cached OTTER CPU developed in CPE 233 and CPE 333 into a multicore processor capable of running parallel workloads. The thesis documents the architectural changes required to adapt the verified single-core design into a multicore system, including MMIO-based interrupt support, a shared cache hierarchy with cache-coherence mechanisms, and clock-gated modules. It further presents a …

Trust And Pre-Employment Background Checks When Onboarding And Maintaining Information Security And Cybersecurity Staff, Stanley Mierzwa

Center for Cybersecurity

The realm of trust is broad and can include many facets that are difficult to capture and catalog. In relation to the work roles of information security and cybersecurity, the intersection of trust in human resource management is critical and an evolving area within most modern organizations, in almost any sector, and of any size. A foundational element of trust is fundamental to effective mission and work roles in information security and cybersecurity, as well as to every employee tasked with contributing to the security of an organization’s assets. This chapter will include sections on the role trust can and …

Stock Market Analysis And Volatility Behavior During The Covid-19 Pandemic, Manoj Venkatachalaiah, Soon Leong Yeap, Salman Ahmed Lnu, Sangwhan Cha

Harrisburg University Other Works

This report outlines the structural design, cloud implementation, and analytical findings of a scalable Big Data architecture deployed on Google Cloud Platform (GCP). The primary objective is to investigate the macroeconomic and microeconomic disruption caused by the COVID-19 pandemic on global equities, focusing on two dominant digital business models: online retail/cloud computing (Amazon, Inc. - AMZN) and subscription-based digital streaming entertainment (Netflix, Inc. - NFLX). Through a serverless orchestration pipeline leveraging GCP Cloud Run, automated workflows fetched and blended high-velocity epidemiological metrics alongside daily financial asset layers. Data transformations and parallel analytical calculations were executed utilizing Apache Beam pipelines inside …

Evaluating Design Choices For Gpu-Accelerated Finite-Difference Time-Domain Simulation On Resource-Constrained Devices, Joel Manesh

Master's Theses

The Finite-Difference Time-Domain (FDTD) method is a numerical technique for solving partial differential equations. It was first developed to solve Maxwell’s equations for electromagnetic wave propagation and has since been extended to model other physical phenomena governed by wave propagation. Because the FDTD method is data-parallel, it is well-suited for GPU acceleration; modern FDTD-based simulations run offline on large GPU clusters. There is, however, very little research on running FDTD on resource-constrained embedded GPUs, which are increasingly popular for real-time applications.

This thesis explores a CUDA-based FDTD solver for the 3D wave equation on the Nvidia Jetson Orin Nano. This …

Concrete And Masonry Code (Beams), Michael Alexander Simas Rocha

Architectural Engineering

This report only covers the beam design of the code that was written. The end goal of this project is to write code for concrete and masonry following what was taught in the lecture classes. This project is acting as a foundation for the end goal of a program that can compete with SAP2000, ETABS, RISA, and others. One final goal is to have the print out have the look and feel of having been done by hand. While coding; several factors were recorded including time spent coding, debugging, and then to do three problems by hand vs how long …

Early Dementia Tracking Utilizing Virtual Reality, Gabriel Deguzman, Manuel Hernandez, Ryan Iglesias, Jose Ornelas

General Engineering

This project aims to create a simulation in virtual reality that replicates an activity that older adults are familiar with and presents an objective for the user to complete. The simulation will monitor the user’s cognitive functions based on their performance. The functionality of the designed program includes, but is not limited to: continuous tracking of cognitive behavior, skipped steps, and completion times. The program will take in relevant data and provide results on the monitored tasks and give the user a conclusion for further action. The application of this simulation will not be used as a medical device or …

Polysaber: A Custom Reactive Lightsaber Soundboard, Pedro B. Medeiros

Computer Engineering

The PolySaber project was developed as a custom reactive lightsaber control system built as a fully custom PCB design. The purpose of the project was to create a lower-cost and more customizable alternative to commercially available lightsaber soundboards while simultaneously providing hands-on experience in PCB design, embedded systems development, and hardware integration. Commercial lightsaber soundboards are expensive, proprietary, and difficult for hobbyists to customize. The PolySaber project addresses this by creating a modifiable hardware platform built around the ESP32 microcontroller. The system supports programmable firmware, RGB NeoPixel blade control, motion sensing, reactive swing and clash effects, onboard audio amplification, and …

Lora Networking Hardware Reference Designs For Terrestrial And Low-Earth-Orbit Communications, Kevin Nottberg

Master's Theses

The work presented here demonstrates a highly robust and tested LoRa networking hardware reference design to meet the needs of the embedded networking company OWL Integrations. The hardware presented integrated a unique combination of features and design choices. The detailing of its unique design is potentially of use to others for use in fielded battery powered terrestrial sensor networking hardware utilizing LoRa. Also, the terrestrial hardware presented is shown to have the capability to support command and control (C2) LoRa links in low-earth orbit beyond terrestrial systems. The design presented has a more U.S. centric component bill-of-materials (BOM), with the …

Gps Tracking Smart Dash Cam Capstone Review, Simrah Saleem

University Honors Theses

This thesis details our design, implementation, and collaborative development of an intelligent vehicle logging system built on a Raspberry Pi 5. Unlike standard consumer dash cams that act as closed "black boxes," our system uses a dual-camera stereo vision setup integrated with centimeter-level accuracy. While we successfully built a functional Proof of Concept capable of event-triggered recording, dual-monitor visualization, and smart detection and recognition, this paper focuses on our engineering journey and the real-world challenges we faced. Using an Agile framework, we split into three specialized sub-teams to handle hardware, database, and interface design in parallel. This structure created unique …

Design And Parametric Study Of A Mems-Based Reservoir Computer For Reinforcement Learning, Andrew P. Carr

Master's Theses

Single-node reservoir computing (RC) is a hardware-efficient approach to machine learning, leveraging the dynamics of physical systems. In this work, two reinforcement learning algorithms, Q-learning and Proximal Policy Optimization (PPO), are applied to a simulated micro-electro-mechanical system (MEMS)-based reservoir computer to solve both discrete and continuous control tasks. MEMS-based reservoirs are low-power, compact, and their natural frequencies (kHz to MHz) pair well with real-time control loops. To explore the relationship between reservoir dynamics and learning performance, a parametric study is conducted on two reservoir hyperparameters, reservoir size and neuron separation, using CartPole-v1 and MountainCar-v0. The RC successfully learns multiple tasks …

Reliable Offline Evaluation Under Exposure Bias: A Cross-Scale Study Of Counterfactual Estimators In Recommender Systems, Lakshmi Pranathi Vutla

Graduate Masters Theses

Offline evaluation underpins model selection in recommender systems, yet historical interaction logs are shaped by prior recommendation policies. Because users only provide feedback on exposed items, logged data entangles user preferences with exposure mechanisms, leading to exposure bias and potentially misleading model comparisons. Counterfactual estimators such as IPS, SNIPS, CRM, and DR offer principled corrections, but their empirical reliability across datasets and exposure regimes remains insufficiently under- stood. We present a systematic, cross-scale study of counterfactual evaluation in recommender systems. Comparing IPS, SNIPS, CRM, and DR on datasets with randomized exposure (Yahoo! R3, Coat, and KuaiRec), we analyze estimator behavior …

Enabling Ml/Ai In 6g And Future Wireless Communication With Privacy Preservation, Mec Offloading And Quantum Computing, Changshi Zhou

Dissertations

The forthcoming sixth-generation (6G) and future wireless networks are envisioned to support an unprecedented range of services, delivering ultra-low latency, massive connectivity, and intelligent real-time responsiveness. These capabilities will enable emerging applications such as extended reality (XR), autonomous vehicles (AVs), industrial robotics, and the Internet of Things (IoT) to reach their full potential. Achieving this vision requires the integration of enabling technologies such as artificial intelligence and machine learning (AI/ML) and quantum computing, which are poised to play central roles in shaping the landscape of wireless communication systems.

In AI-native, data-driven, and computing-centric 6G networks, ML models will be deeply …

Holistic Dram Enhancements: From Intrinsic In-Memory Operations To Robust Security Mechanisms, Ranyang Zhou

Dissertations

Dynamic Random-Access Memory (DRAM) is both the performance bottleneck and a critical security boundary of modern computing systems. Its physical properties make it an attractive substrate for near-data computation—yet those same properties expose it to disturbance-based hardware attacks. This dissertation argues that these two dimensions are not independent: the architectural choices that make DRAM efficient also reshape its threat landscape. Addressing both requires a unified approach to memory architecture and security co-design.

The first part of this dissertation attacks the memory wall through four processing-in-DRAM (PIM) frameworks. ReD-LUT and LT-PIM unify lookup-table arithmetic with charge-sharing logic, achieving up to 37.8x …