Digital Commons Network^™

Executive Committee - Agenda, 11/04/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

A Convolutional Neural Network Approach To Breast Cancer Tumor Boundary Detection, James Leah Matlosz

Master's Theses

Breast cancer is the second most common form of cancer and often goes undetected in its initial stages due to its subtle symptoms. As the tumors grow, they become more difficult to surgically remove with clean borders. To minimize the chance of recurrence, a 2D convolutional neural network is developed in this work for delineating tumor boundaries. Specifically, the U-shaped network model is trained, validated, and tested with longitudinal MRI scans of patients diagnosed with breast cancer and undergoing neoadjuvant therapy. For training, image masks were generated as ground truths using signal enhancement ratio segmentation, thresholding, and contour detection. The …

Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil

Master's Theses

Healthcare remains a prime target for cyberattacks, with insider misuse and credential compromise posing major risks to Electronic Health Records (EHRs). This thesis introduces a role-aware, explainable anomaly detection and response framework integrated with OpenEMR to address post-authentication threats. Four models—Local Outlier Factor (LOF), Isolation Forest, Autoencoder, and Graph Neural Network (GNN)—detect behavioral deviations across temporal, device, and role-based features, with LOF serving as the primary runtime detector. A configurable policy engine maps anomaly severity to proportional actions, from email alerts to read-only restrictions or account suspension, all reversible and auditable. Evaluation on real EHR logs shows the system’s operational …

Cal Poly (Cp) Legged Robot, Sebastian Barboza, Jonathan Mchale, Isabella Sorensen, Isaac Golan

Mechanical Engineering

The Navy spends $60 billion annually on dangerous ship maintenance performed by sailors. To save lives and resources, the Naval Surface Warfare Center (NSWC) is looking for robots to replace sailors and navigate ships to perform various tasks. Robots with tracks and wheels have been most recently explored by NSWC, however they have encountered significant problems navigating the ships, especially through naval ship doorways with a significant ledge. By using a legged robot, our team hopes to solve these problems and have a robot that can navigate the ship with relative ease and stability.

Reviving Motion: Rebranding More Than Motion Dance Intensive, Ava Zamoff

Graphic Communication

For my senior project, I will lead a full rebranding initiative for More Than Motion Dance Intensive, an international dance convention that occurs annually across the US and other countries, connecting dancers and professional choreographers through a transformative weekend of dance. The main goal of this project is to turn the company’s outdated Wix website into an innovative site with a brand new visual identity. Additionally, the original site’s accessibility is lacking in terms of layout orientation and marketing strategy as it doesn’t convey the modern, dynamic feel the intensive is meant to embody. My goal is to complement the …

Academic Senate - Minutes, 10/07/2025, Academic Senate

Academic Senate Minutes

No abstract provided.

Accelerating Metal Extrusion Additive Manufacturing Process Development With Citrine Machine Learning Tools, Sam Moran, Andrea Patin, Tyler Seto, Cam Sherry

College of Engineering Summer Undergraduate Research Program

Material Extrusion (MEX) is a low-cost approach to metal additive manufacturing that involves extruding a metal-polymer composite filament to create a part comprised of polymer-bound metal powder, which is subsequently debound and sintered to produce a fully metal component. A major barrier to broader implementation of metal MEX is the time-intensive process for determining printing and sintering process parameters. To consistently produce sintered parts that satisfy geometric and materials properties requirements, trial-and-error experimentation is required to develop process parameters, correct shrinkage variability, and mitigate defects. This project aims to leverage Citrine Informatics’ machine learning (ML) tools to accelerate development of …

Evaluating Machine-Learning Models For Drone-Based Image Analysis Of Coastal Ecosystem Dynamics, Katharine Mcdaniel, Pragati Toppo

College of Engineering Summer Undergraduate Research Program

Previous work from our group utilized drone-based images and a novel machine learning classification model to quickly and accurately quantify spatial variability in eelgrass in Morro Bay. In this SURP project we aim to develop and evaluate quantifiable estimates of the model’s prediction uncertainty. Our model produces a binary labeling indicating the presence or absence of eelgrass at each pixel. However, internally the model produces a probabilistic output indicating the likelihood of detection at each pixel that we propose to use to produce uncertainty estimates and a confidence interval for the cumulative extent of eelgrass detected. This would allow for …

Mixed Reality In Human–Robot Interaction For Collaborative Applications, Evan Reid, Caitlin Osorio

College of Engineering Summer Undergraduate Research Program

This project explores the use of Extended Reality (XR) technologies to enhance human- robot interaction in industrial contexts. Building upon prior research in affective and cognitive state recognition during human-cobot collaboration, this study investigates how natural hand and head gestures, captured through Meta Quest passthrough mode, can be used to communicate human intent to a Universal Robotics e-Series collaborative robot. The XR system provides users with an immersive, real-world visual interface while tracking motion and position in real time. The captured gestures are interpreted through a custom software pipeline that integrates machine learning models and rule-based logic to trigger adaptive …

Analysis And Evaluation Of Backtracking Settings For Energy Yield Optimization At The Cal Poly Solar Farm, Kayla Go-Oco

College of Engineering Summer Undergraduate Research Program

The Cal Poly Solar farm has been built as a single axis tracking facility with two different types of panels. Both conventional single cell solar panels and twin cell solar cells have been used in its construction. Twin Cell panels typically perform better than their conventional counterparts when shaded by other panels in the row in front of them in a fixed tilt system. However neither module performs well when even a small portion is shaded. This project will access the system API to access data for the field and process to determine the energy yield improvements that can be …

Mastering Undergraduate Algorithms: Improving Problem-Solving Skills And Fluency Through Scaffolding Learning Modules, Anissa Soungpanya

College of Engineering Summer Undergraduate Research Program

The primary objective of the undergraduate algorithms course is to equip students with the ability to design and analyze algorithms, prove theorems about computation, and effectively communicate these algorithms and proofs to a human audience. In addition, the course aims to help students foster their fluency in the process of formulating and solving computational problems. Scaffolding exercises and activities that focus on these aspects could serve as useful learning tools in providing targeted feedback and helping students develop their confidence and fluency. To address the challenges that students encounter when solving algorithmic problems -- particularly in regard to problem decomposition …

Augmented Reality Application For Real-Time Coastal Data Visualization, Nithyasri Palanisamy

College of Engineering Summer Undergraduate Research Program

This project aims to develop an Augmented Reality (AR) application that overlays real-time coastal environmental data onto physical landscapes when viewed through AR devices such as smartphones and mixed reality headsets. By integrating data from machine learning models, computer vision-based event detection, coastal sensors, and geospatial mapping technologies, the application will provide users with an immersive and interactive experience, enhancing their understanding of coastal dynamics and environmental changes. The application will focus on observing coastal phenomena such as rip currents, tracking endangered coastal species and marine mammals, monitoring crowd levels on beaches, etc. Data sources will include NOAA's National Data …

Evaluating The Accuracy Of Gen Ai Detecting Misinformation, Alan Sebastian

College of Engineering Summer Undergraduate Research Program

This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …

3d Printing Scoliosis Braces, Zak Neddo, Jaylan Mo

College of Engineering Summer Undergraduate Research Program

As 3D printing technology continues to transform the healthcare industry, the need for FDA-compliant additive manufacturing facilities in public universities has become increasingly important. While private companies and medical research institutions have successfully integrated 3D printing for medical device prototyping and surgical planning, public universities—including Cal Poly—lack the dedicated infrastructure needed to support FDA-regulated medical manufacturing and research. This project aims to bridge that gap by researching, designing, and implementing a dedicated FDA-compliant section within Cal Poly’s multi-purpose 3D Printing Facility. Over the course of eight weeks, student researchers will study FDA regulations, design an optimized facility layout, and implement …

Orbital Mechanics And Ai, Daniella Luciani, Cliodhna Mcguigan

College of Engineering Summer Undergraduate Research Program

Traditional orbital mechanics courses typically start with simpler problems that can be solved on paper, gradually progressing to more complex problems that require computational tools. In the AERO department, we have traditionally used MATLAB for these computational tasks. However, the industry is increasingly shifting toward platforms like Python for coding these types of problems. Additionally, with the rapid rise of AI, tools like ChatGPT are now at the forefront of code generation. To stay ahead, students need to learn how to generate code using AI and assess whether the generated code is functioning as expected. This SURP will have students …

Making Lab Manuals For Optimizing Student Engagement And Learning, Carlos Perez, Andrea Bautista Rocha

College of Engineering Summer Undergraduate Research Program

Through the Engineering Possibilities in College (EPIC) program, high school students explore various engineering majors offered at Cal Poly. Survey reports filled out by students reflect areas of growth for the program and the engineering labs that they participate in. We expanded on this feedback by creating an effective lab manual based on the student feedback, aiming to optimize student engagement and learning.

Acoustic-Based Quality Monitoring In Fused Deposition Modeling (Fdm) 3d Printing, Madeleine Howard

College of Engineering Summer Undergraduate Research Program

This project investigates the use of acoustic signals captured during Fused Deposition Modeling (FDM) 3D printing to predict part quality and detect process anomalies. Traditional quality monitoring in FDM often relies on visual inspection or post-process evaluation, which can be slow and inconsistent. This research explores a low-cost, non-contact alternative using microphones and accelerometers to capture real-time audio and vibration signatures of the printing process. By applying signal processing and machine learning techniques to these acoustic signals, the project aims to classify part quality and identify defects such as under-extrusion, layer misalignment, or nozzle clogging. The outcomes have potential applications …

Optimizing Object Detection For Remote Monitoring With Owl Ducklink Radios, Colin Ren-Jin Babian

Electrical Engineering

This project develops an AI powered object detection system integrated with OWL DuckLink radios to enable real time remote monitoring. The system benchmarks multiple AI accelerators using a Raspberry Pi 5 to determine their efficiency in low power, long range communication environments. By evaluating the Raspberry Pi 5 CPU (7.62W, 14.5 camera FPS, 3.8 inference FPS), Raspberry Pi AI Camera with Sony IMX500 (6.45W, 30 camera FPS, 9.2 inference FPS), and Raspberry Pi AI Hat with Hailo-8L chipset (7.80W, 30 camera FPS, >30 inference FPS), this project identifies the most effective combination of hardware and software for edge AI applications. …

Restoration Of 6-Axis Industrial-Grade Robotic Arms, Bryce Andrew Paulson, Warren Douglas Howard

Electrical Engineering

The Staubli TX60 and TX60CR are industrial-grade, six-axis robotic arms originally designed to perform complex automation tasks in manufacturing environments. Following their retirement from active industrial use, both units were restored to full operational status. As part of this project, they were reprogrammed to execute a pick-and-place routine using kids shape-sorting toys that mirrors typical workflows found in factory settings. The six degrees of freedom afforded by each robot enable a wide range of motion, making them well-suited for tasks such as material handling, product sorting, and repetitive operations typically carried out by human workers. Each model is equipped with …

Gene Expression Of Anthocyanin Pigments In The California Native Plant Leptosiphon Parviflorus: Interactions Between Flower Color Morphology And Abiotic Stressors, Weston Gonor

Master's Theses

For plants to survive in harsh conditions imposed by abiotic stressors, they must develop mechanisms of adaptation. One of the common types of adaptation seen in plants is the production of anthocyanin pigments, which have been shown to protect plants from UV radiation, metabolic stress, and drought. In this study, we used the flower color polymorphic species Leptosiphon parviflorus to investigate the role of anthocyanin pigments in protecting plants from abiotic stress. To accomplish this, RNA samples were taken from flower, leaf and root tissue of different flower color morphs of Leptosiphon parviflorus (Polemoniaceae) grown in high magnesium and water …

Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff

Master's Theses

Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …

Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach

Master's Theses

As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …

Sparse-Data Orbit Estimation In Low Earth Orbit Using The Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter, Nicholas J. Oden

Master's Theses

The number of space objects (SOs) in low Earth orbit (LEO) continues to increase rapidly, creating challenges for the current ground-based tracking network, which cannot accommodate the projected growth in SOs. Catalog maintenance relies on frequent observations for reliable reacquisition, with Two-Line Element (TLE) sets typically generated daily to mitigate rapid error growth from poor TLE accuracy. This constraint limits the ability to track more objects with existing infrastructure. This work evaluates the Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter (MCMC EnGMF), a nonlinear, non-Gaussian filter well-suited for sparse tracking scenarios where higher post-update accuracy is needed to reduce …

Building A Novel Question-Answering System Using Retrieval-Augmented Generation For The California Fair Political Practices Commission, Saanvi Dua

Master's Theses

The California Fair Political Practices Commission (FPPC) receives a high volume of inquiries via email from public officials, the general public, and other agencies, which currently requires staff to manually search through informational documents and manuals to provide timely responses. This process is both labor- and time-intensive.

To address this challenge, we design a question-answering (QA) system that drafts responses to emailed questions by retrieving relevant information from the FPPC’s manuals using a retrieval-augmented generation (RAG) framework. Although the current implementation focuses on a single manual, the system is designed to be adaptable to the broader set of FPPC documents. …

Gravitational Torques From Lopsided Young Stellar Component Sustain High Black Hole Accretion Rates In Ngc 4593, N. Winkel, K. Jahnke, J. A. Fernández-Ontiveros, T. A. Davis, F. Combes, M. Gaspari, J. Neumann, M. Singha, J. S. Elford, Vardha N. Bennert, M. A. Malkan

Physics

Context. Supermassive black holes (SMBHs) grow primarily through gas accretion, observed as active galactic nuclei (AGNs). While mergers can drive luminous AGN episodes, secular processes may fuel a substantial portion of cosmic black hole growth. Whether these mechanisms can sustain high black hole accretion rates remains uncertain.

Aims. The aim of this study is to identify the secular mechanism driving high SMBH accretion rates, by targeting a galaxy with a moderately massive SMBH, high central gas densities, accretion rates of a few percent of the Eddington limit, and gas kinematics resolved close to black-hole-dominated scales.

Methods. A blind search led …

Transformative Pedagogy: Going Beyond An Inclusive Curriculum, Heather Mcnamee

Feminist Pedagogy

This critical commentary argues that approaches toward inclusion in higher education, particularly within curriculum design, are insufficient for creating true systemic change. While efforts to include marginalized voices in humanities curricula indicate some progress, the foundational frameworks continue to center privileged perspectives, relegating marginalized voices to mere additions rather than centralizing them. Drawing on examples from history, social studies, and anti-violence work, this commentary contends that higher education must move beyond inclusion and toward a reimagining of curriculum that critically examines and dismantles the power structures underpinning knowledge production. The commentary emphasizes the need for a curriculum that not only …

Using Classroom Response Systems For Feminist Pedagogy In Large Classes, Sarah Rainey-Smithback, Nicole Kalaf-Hughes

Feminist Pedagogy

Most practitioners using feminist pedagogy assert small, discussion-based classrooms are best suited for creating power-sharing spaces where students are co-creators of knowledge. While we do not disagree that small classes are well-matched for feminist pedagogy, we challenge the assumption that feminist pedagogy cannot be practiced in large classes. This article explores how Top Hat, a web-enabled classroom response system (CRS), can be used to facilitate feminist pedagogy in a large Introduction to Women’s Studies class. Using data on student perceptions of the CRS, as well as instructor reflections on a technology-centered feminist classroom, this work suggests CRS can be used …

What Is “So Severe, Pervasive, And Objectively Offensive?”: Defining Sexual Harassment, Investigating Reporting Requirements, And Supporting Disclosures With Communicative Role-Playing, Lauren L. Buisker, Kylie Johnson

Feminist Pedagogy

Despite the pervasive reach of rape culture on college campuses, university sexual harassment trainings frequently fail to provide students with clear definitions of sexual violence, often avoid using intersectional frameworks to teach students about the topic, and obscure the bureaucratic complexities that inhibit survivors’ abilities to seek out appropriate resources when they experience sexual trauma. As such, this article outlines communication strategies for feminist instructors interested in improving their students’ understanding of sexual harassment, given that social science and humanities classrooms provide apt spaces for grappling with difficult topics and the way in which language constructs our reality. We propose …

Spatio-Temporal Variability Of San Francisco Bay Plume From Space, Piero L. F. Mazzini, Cassia Pianca, L. Fernando Pareja-Roman, Kelly L. Cole, Ryan K. Walter, Renato M. Castelao, Elias J. Hunter, Robert J. Chant

Physics

As brackish turbid waters exit San Francisco Bay, one of the largest estuaries in the U.S. West Coast, they form the San Francisco Bay Plume (SFBP), which spreads offshore and influences the Gulf of the Farallones (GoF), an ecologically significant region in the California Current System that is also home to three National Marine Sanctuaries. This paper provides the first observationally based investigation of the spatio-temporal variability of the SFBP, using a plume tracking algorithm applied to more than two decades (2002-2023) of ocean color data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard satellites Aqua and Terra. The …

Owl Integrations Soil Monitor, Derek Chau, Armaan Kahlon

Electrical Engineering

This paper examines the design process and results concerning the OWL Integrations soil monitor. Disaster relief relies heavily on digital communications, especially in environments where conventional methods (e.g. Wi-Fi, cellular, fiber optics) are unusable. To help emergency services assess disaster-stricken areas, a soil monitoring system was developed using LilyGo T-Beams (ESP32), programmed with specialized firmware known as the ClusterDuck Protocol to collect data pertaining to moisture and temperature. The project is sponsored by OWL Integrations, with help from the Cal Poly Electrical Engineering (EE) Department. Results show positive prospects, with the product able to make 4 km transmissions, operate for …