Digital Commons Network^™

Motivation And Engagement In Outreach Activities, Aurora Geisen

College of Engineering Summer Undergraduate Research Program

If the four elements of motivation and engagement are present in engineering outreach activities, does this affect the desire to become an engineer? Four elements: Autonomy, Purpose, Community, Mastery.

If the four elements of motivation and engagement are present/increased, and thereby motivation and engagement increase, do more students attending an engineering outreach event want to become engineers? If yes, then those activities where the four elements are increased/present should show an increase in students who are engaged and motivated to become engineers. If no, then the design of activities is not a major deciding factor in whether a student wants …

Building A Smart Transportation Network To Prevent Multi-Vehicle Collisions During Sudden Slowdowns, Leo Huang, Patrick Zhao

College of Engineering Summer Undergraduate Research Program

This proposed SURP project aims to design and evaluate a smart transportation network capable of preventing multiple-vehicle collisions due to sudden slowdowns in traffic. This project will simulate abrupt braking scenarios and implement adaptive vehicle-to-vehicle (V2V) communication protocols. By enhancing real-time awareness and responsiveness among vehicles, the system will reduce pileup risks and improve road safety.

Performance Dashboard Design For Radiologists: Highlighting What Matters & Fostering Improvement, Trevor Knotts, Jemma Simpson, Coleman Hawkins

College of Engineering Summer Undergraduate Research Program

TurboRad has developed a system with proven results that streamlines radiology report creation and improves radiologist productivity. A study performed in 2023 found that “the advanced macro-button toolbar system has great correlation for both lower report completion times and increased wRVU productivity. The benefits of the toolbar system are most evident in the simpler XR reports. Though they are simpler to read and complete reports, the greater quantity of XR reports contributes to a greater overall wRVU completion rate throughout the day as radiologists can spend more time on more complex examinations and reports” (Chow, Speece, & Holtzman, 2024). Since …

Certifiably Robust Input-Dependent Randomized Smoothing Via Lipschitz Standard Deviation Networks, Faith Bergstrom, Ben Sager

College of Engineering Summer Undergraduate Research Program

Modern artificial intelligence (AI) systems exhibit highly sensitive and unsafe behavior when subjected to undetectable cyberattacks. For instance, human-imperceptible manipulations of the pixels in image data can cause traffic sign classifiers to mispredict stop signs as yield signs. In this project, we will design and analyze new methods to robustify machine learning (ML) models against these adversarial threats. Specifically, we will explore randomization techniques that "smooth out" the ML model's decision making process by intentionally corrupting input data with small amounts of noise. Optimizing this noise to enhance resilience against attacks while maintaining the system's accuracy poses a major open …

Math+Cs Integrated Curriculum For K-12 Computer Science Education, Amogh Arora

College of Engineering Summer Undergraduate Research Program

This is a proposal for an activity to initiate an effort to create a series of X+CS integrated curricula for learning Computer Science (CS) in K-12. As a start, we examine Mathematics and CS standards, to find the cross-cutting concepts between the two fields. By leveraging these concepts, we bring to the foreground the ways CS can be used in the mathematical context. The goal for this research is to create a 15-week teacher training curriculum that will expose teachers to the CS concepts of Abstraction, Data Representation, Problem Comprehension and Decomposition, Control Structures, Functions and Generalization. Historically, Mathematics and …

Executive Committee - Agenda, 09/30/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

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. …

Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain

Master's Theses

Accurately pricing American options with market data presents a significant challenge, as foundational models like the Black-Scholes-Merton (BSM) model rely on assumptions that deviate from real-world financial data -- such as log-normal returns, constant volatility, and no dividends -- and fail to account for the key early exercise feature of American options. While parametric models can adjust for these features, the complexity of the resulting models renders them prohibitively difficult to apply in practice for nonspecialists. In response, modern machine learning (ML) techniques provide a set of flexible and powerful alternatives, and recent research has explored the application of ML …

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 …

Alpine Plants And Climate Change: Tracking Community Shifts In Yosemite National, Brooke L. Wallasch

Master's Theses

As climate change progresses, alpine plant communities are predicted to shift upslope as they track temperature over time. Relative to lowland environments, alpine areas are experiencing a faster rate of temperature change due to a phenomenon referred to as elevation-dependent warming. A common approach for tracking plant communities shifts over time, is to conduct resurveys of the same area at several time points, as the Global Observational Research Initiative in Alpine Environments (GLORIA) has done on mountain summits around the world since 2001. In 2011-2013, GLORIA developed a supplemental survey method whereby belt transects were established downslope of summits in …

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 …

Adjoint Enhanced Panel Methods, Christopher Sheehan

Master's Theses

This thesis describes the development, implementation, and validation of an adjoint-enhanced panel method for two-dimensional airfoil analysis. While conventional panel methods are computationally efficient for flow analysis, they typically rely on relatively computationally expensive finite differencing for gradient calculation in design optimization or sensitivity studies, a limitation addressed by employing the discrete adjoint method. The core of this work involves integrating the discrete adjoint method with a Hess-Smith panel code utilizing Class-Shape Transformation (CST) for airfoil parameterization, which requires the analytical derivation of sensitivities for panel geometry, boundary conditions, and the aerodynamic influence matrix with respect to the CST design …

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. …

Enhancing Preparedness: A Genetic Study Of Sar-Cov-2 And Other Microbial Public Health Threats In Wastewater From A College Town, Christian N. Hutchinson

Master's Theses

Problem

The SARS-CoV-2 (COVID-19) pandemic revealed both the systemic vulnerabilities of our healthcare system as well as the importance of timely, localized data for informing public health responses. Traditional testing approaches were essential but often failed to capture the full extent of viral spread, especially in those with mild or asymptomatic conditions that relied on at home testing. This underreporting hindered effective allocation of resources and made developing effective intervention strategies difficult. We also realized the potential for wastewater surveillance to be applied to tracking antimicrobial resistance gene markers. Taken together, this approach should have important implications for improving public …

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 …

Spatially Resolved Kinematics Of Slacs Lens Galaxies. I. Data And Kinematic Classification, Shawn Knabel, Tommaso Treu, Michele Cappellari, Anowar J. Shajib, Chih-Fan Chen, Simon Birrer, Vardha N. Bennert

Physics

We obtain spatially resolved kinematics with the Keck Cosmic Web Imager (KCWI) integral-field spectrograph for a sample of 14 massive (11 < log₁₀(M₍★₎/M☉) < 12) lensing early-type galaxies at z ∼ 0.15–0.35 from the Sloan Lens ACS (SLACS) Survey. We integrate kinematic maps within the galaxy effective radius and examine the rotational and dispersion velocities, showing that 11/14 can be classified as slow rotators. The data set is unprecedented for galaxy-scale strong lenses in terms of signal-to-noise ratio (S/N), sampling, and calibration, vastly superseding previous studies. We find the primary contributions to systematic uncertainties to be the stellar template library and wavelength range of the spectral fit. Systematics …

Marine Heatwaves Detected By A Network Of Buoys Along The Entire Us West Coast Shelf, Gavin Plume, Ryan K. Walter, Piero L.F. Mazzini, Michael Dalsin

Physics

Marine heatwaves (MHWs), prolonged periods of anomalously warm waters, pose an increasing threat to marine ecosystems globally. While satellite-based data offer insights into MHW patterns, coastal upwelling regions are prone to satellite biases and require long-term in-situ datasets for accurate characterization. Using two decades of temperature data from 22 surface buoys distributed along the US West Coast continental shelf (10–50 km offshore) spanning nearly 2000 km of coastline, we investigated, for the first time, coast-wide patterns of MHWs in this valuable region. The spatial extent of MHWs varied from 100% of buoys during the 2014–2016 North Pacific MHW, to less …

Mentoring In The Undergraduate Classroom And Beyond: Creating A Feminist Praxis, Satarupa Dasgupta

Feminist Pedagogy

In the following critical commentary, it is discussed how mentoring--- in the classroom and in academia---can be a feminist practice that comprises an essential part of being a feminist educator. Mentorship encompasses a process in which the mentor disseminates knowledge as well as psychosocial support that are perceived by the mentee as essential for professional or personal development (Sedlacek et al., 2007). Mentorship has been specifically found to fulfill professional needs for women, while enhancing their self-worth and sense of competence, and providing instances of role modeling and social affirmation (Meschitti & Lawton Smith, 2017).

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 …

Coyote (Canis Latrans) And Non-Target Wildlife Responses To Livestock Guardian Dogs At Sheep Grazing Sites On The California Central Coast, Tricia T. Nguyen

Master's Theses

Livestock depredation is one of the oldest and most widespread forms of human-wildlife conflict. The coyote (Canis latrans), a midsized canid, represents a significant proportion of domestic sheep depredations in the United States, costing livestock producers an estimated 24.6 million dollars annually. Management strategies for coyote-sheep depredation vary widely in their effectiveness and in their level of public support. Identifying appropriate strategies for farms, ranches, and other sheep grazing sites remains a pressing need due to the potentially negative consequences for surrounding ecosystems and socioeconomic outcomes for sheep producers. The livestock guardian dog (LGD) is a nonlethal control …

Executive Committee - Agenda, 08/01/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

Drug Delivery, Disulfide Crosslinked Hydrogel Coating For Polydimethylsiloxane (Pdms) Implant Materials, Paul A. Contos, Paul Anthony Contos

Master's Theses

Though polydimethylsiloxane (PDMS) is often used in medical devices due to its desirable mechanical properties and biocompatibility, its surface is often prone to bacterial adhesion. This is especially a problem for catheters, where bacteria can adhere and form biofilms that can in turn result in Urinary Tract Infections (UTI). In order to deter the presence of UTI causing bacteria on PDMS catheters, methods were developed to formulate a disulfide crosslinked hydrogel coating and create a methodology to allow adhesion to a PDMS substrate. The hydrogel coating discussed in this paper will be synthesized by chemically crosslinking stimuli-responsive vesicles, that carry …

Using Livestreaming Technology To Answer Novel Questions About The Behavior And Physiological Ecology Of The Prairie Rattlesnake (Crotalus Viridis), Max C. Roberts

Master's Theses

Recent advances in remote monitoring technology are opening up new opportunities for developing innovative natural history and biological research methodologies. In particular, the emergence of livestreaming camera technology has made recording remote video of wild and secretive animals much easier and made it possible to collect data at extremely fine temporal resolutions. In 2024, Project RattleCam launched a livestreaming camera at a Prairie Rattlesnake (Crotalus viridis) den in Colorado. The goal of this work was to study Prairie Rattlesnake behavior 24-7 throughout the species’ active season with minimal human disturbance. Additionally, I used this system to study the …

Investigating Rattlesnake Social Networks And Improving Their Public Image Through Unobtrusive Technologies And Community Science, Owen M. Bachhuber

Master's Theses

While technology is often blamed for humans’ increasing disconnect with nature, it can also serve as a tool to facilitate empathy and conservation action for wildlife. Snakes are among the most feared animals on the planet, though their understudied social interactions provide opportunities to make scientific discoveries and change public perceptions. Project RattleCam was founded as a camera trap project in 2021 and launched the first off-grid livestream on a den of wild Prairie Rattlesnakes (Crotalus viridis) in 2024. Both camera types captured hundreds of Prairie Rattlesnakes gathering in the summer as they prepared to give birth to pups before …

Seconds From Impact: Anticipatory Vehicular Crash Prediction Using Video Vision Transormers, Ryan P. Geisen

Master's Theses

Vehicular collisions represent a significant public health concern, necessitating re search into advanced emergency notification systems. While deep learning has shown promise in accident detection, a research gap persists in applying state-of-the-art transformer architectures to the task of anticipatory, real-time crash prediction from video. This thesis addresses this gap by developing and evaluating a Video Vision Transformer (ViViT) for the binary classification of imminent vehicular collisions. Utilizing a curated dataset of 1,493 unique collision sequences, this study systemati cally investigates the impact of temporal context by comparing the ViViT against a single-frame Vision Transformer (ViT) baseline and conducting comprehensive exper …

Academic Senate - Agenda, 6/3/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

Opensim Analysis Of The Aymara Indigenous People Performing Ancestral Tasks: Exploring Trends Of Muscle Activity With Tiwanaku Skeletal Indicators, Noah M. Taylor

Master's Theses

The Tiwanaku civilization (AD 500-1100) of the Andean highlands exhibited occupational specialization in communities, with archeological evidence suggesting the existence of labor- and residential-communities, or “taskscapes”, based on an individual’s livelihood. Prior bioarcheological studies have examined Tiwanaku skeletal remains for musculoskeletal stress markers, osteoarthritis, and cross-sectional geometry to infer activity patterns. Their descendants, the Aymara Indigenous people, currently live in the same highlands and until recently lived a lifestyle like their ancestors. Over the past 20 years, the global quinoa demand has risen, thrusting the Aymara into globalization and moving them away from the traditional tasks previously performed. This study …

Video Game Hacking, A General Problem With Generalized Solutions, Luke Rowe

Master's Theses

As video games continue to get more popular and lucrative, the number of malicious actors seeking to exploit them grows with it. As this industry expands, so does the importance of securing games against cheating and abuse. This thesis aims to educate developers to help mitigate the abuse of video games by these malicious actors. The goal of this thesis is to provide a foundational framework for thinking like a hacker and how to make games harder to abuse once a hacker bypasses conventional anti-cheat software.

This thesis outlines some of the most common cheating methods and provides general context …

Ecological Footprint Analysis Of Chatgpt (Gpt-3), Isabella Boulais

Computer Science and Software Engineering

Climate change is an escalating crisis that demands immediate action from all sectors, including the rapidly advancing field of artificial intelligence (AI). While AI offers climate solutions, its own environmental impact raises concerns. Unfortunately limited research due to rapid development, system complexity, and lack of standardized methodologies hinders our understanding of AI’s environmental consequences. This project aims to conduct a comprehensive ecological footprint analysis of OpenAI’s GPT-3 model that is used to power ChatGPT, establishing guidelines for assessing AI systems’ environmental impact and proposing a framework for improvement. Going beyond tracking carbon emissions, this project will outline the broader lifecycle …