Other Computer Sciences Commons^™

Breadquest: Enhancing Roguelike Accessibility Through Procedural Generation And Thematic Design, Hahns Pena

Computer Science and Software Engineering

BreadQuest is a top-down roguelike dungeon crawler with a whimsical dessert theme that aims to make the genre more accessible while preserving strategic depth and replayability. Players explore procedurally generated dungeons, fight pastry-themed enemies, and collect bakery-inspired items that support a flavor-elemental combat system, with each run offering unique layouts, encounters, and rewards. Built in Unity with a modular, data-driven architecture, the game uses procedural generation techniques like Binary Space Partitioning, Voronoi diagrams, and Perlin noise to create varied and replayable levels. The project emphasizes approachable gameplay, cultural dessert inspiration, and replayability, with success evaluated through playtesting and player feedback.

A Scalable Iteration Of The Horizon Simulation Framework Using Multithreading Techniques, Jason E. Beals

Master's Theses

The Horizon Simulation Framework (HSF) occupies a unique space in the modern aerospace modeling landscape, enabling flexible, modular modeling of mission-level agent behavior through an object-oriented, hierarchical design. HSF's hallmark breadth-first search scheduling algorithm explores a "multiverse" of possible mission execution pathways, enabling exhaustive evaluation of schedule combinations against user-defined heuristics.

As aerospace systems become increasingly complex, HSF faces critical challenges in establishing verifiable, deterministic behavior. The framework's core scheduling algorithm had not undergone systematic validation, leaving questions about temporal consistency, state management correctness, and reproducibility across different program executions. Furthermore, the exponential growth of schedule combinations creates computational bottlenecks …

Declined Charge: An Attempt At The Horror Game Genre, Fernando Sepulveda Guizar

Computer Science and Software Engineering

Books and movies are a great medium for people to experience new worlds and experiences through a usually passive method. This can be great for stories with a set story and have all the pieces fall into place as the author intended. Video games on the other hand can give players a more active role in the worlds and stories that they experience. Players have direct control over the player character, and their actions have consequences that may or may not persist throughout the entire game, which is not usually the case with movies or books. This is why horror …

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 …

Targeting Federated Learning: A Study Of Membership Inference Attacks On Healthcare Data, Brett W. Hillyard, Aditi S. Lappathi

College of Engineering Summer Undergraduate Research Program

This study investigates the vulnerabilities of federated learning models in the healthcare domain, specifically focusing on membership inference attacks (MIA). Federated learning allows local models to train on sensitive healthcare data without sharing the data itself, making it an attractive method for protecting privacy. However, even in this decentralized framework, models remain vulnerable to MIAs, where attackers can infer whether certain data points were used to train a model by analyzing model updates. Using the Texas100 dataset, this study demonstrates that as the number of local models increases, the attack accuracy of MIAs also increases due to higher bias …

Enhancing Place-Based Interaction With Emotion Ai And Augmented Reality, Jake Maier, Ivan Martinez

College of Engineering Summer Undergraduate Research Program

This project explores the integration of augmented reality (AR) and Emotion AI technologies to enhance user experiences in physical environments. By seamlessly merging virtual elements with real-world contexts, we aim to deepen individuals’ interactions and perceptions of their surroundings. Leveraging AR technology enables users to access contextual information, engage with interactive content, and navigate spaces with heightened immersion and understanding. Additionally, Emotion AI enhances these experiences by detecting and responding to users’ emotional states, fostering personalized and emotionally resonant interactions. We aim to integrate digital content within physical environments using mixed-reality headsets equipped with eye-tracking capabilities and consumer-grade wireless EEG …

Combining Cloud Architecting With Education, Sharon P. Pagidipati

Liberal Arts and Engineering Studies

I pursued the AWS Solutions Architect Professional Certification while applying my knowledge to build and revise technical solutions for an educational company known as EDFX.

Legislative Language For Success, Sanjana Gundala

Master's Theses

Legislative committee meetings are an integral part of the lawmaking process for local and state bills. The testimony presented during these meetings is a large factor in the outcome of the proposed bill. This research uses Natural Language Processing and Machine Learning techniques to analyze testimonies from California Legislative committee meetings from 2015-2016 in order to identify what aspects of a testimony makes it successful. A testimony is considered successful if the alignment of the testimony matches the bill outcome (alignment is "For" and the bill passes or alignment is "Against" and the bill fails). The process of finding what …

Comparing Learned Representations Between Unpruned And Pruned Deep Convolutional Neural Networks, Parker Mitchell

Master's Theses

While deep neural networks have shown impressive performance in computer vision tasks, natural language processing, and other domains, the sizes and inference times of these models can often prevent them from being used on resource-constrained systems. Furthermore, as these networks grow larger in size and complexity, it can become even harder to understand the learned representations of the input data that these networks form through training. These issues of growing network size, increasing complexity and runtime, and ambiguity in the understanding of internal representations serve as guiding points for this work.

In this thesis, we create a neural network that …

Patterns Of Academic Help-Seeking In Undergraduate Computing Students, Augie Doebling

Master's Theses

Knowing when and how to seek academic help is crucial to the success of undergraduate computing students. While individual help-seeking resources have been studied, little is understood about the factors influencing students to use or avoid certain re- sources. Understanding students’ patterns of help-seeking can help identify factors contributing to utilization or avoidance of help resources by different groups, an important step toward improving the quality and accessibility of resources. We present a mixed-methods study investigating the help-seeking behavior of undergraduate computing students. We collected survey data (n = 138) about students’ frequency of using several resources followed by one-on-one …

Analysis Of The Slo Bay Microbiome From A Network Perspective, Lien Viet Nguyen

Master's Theses

Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and …

A Survey Of Computer Graphics Facial Animation Methods: Comparing Traditional Approaches To Machine Learning Methods, Joseph A. Johnson

Master's Theses

Human communications rely on facial expression to denote mood, sentiment, and intent. Realistic facial animation of computer graphic models of human faces can be difficult to achieve as a result of the many details that must be approximated in generating believable facial expressions. Many theoretical approaches have been researched and implemented to create more and more accurate animations that can effectively portray human emotions. Even though many of these approaches are able to generate realistic looking expressions, they typically require a lot of artistic intervention to achieve a believable result. To reduce the intervention needed to create realistic facial animation, …

Pilltank, Lucas Chang, Hayden Tam, Aaron Teh, Krista Round

Electrical Engineering

Imagine an elderly family member, going through their daily routine of taking their pills. They find their pill box; however, they are having trouble identifying all the pills in there. Is there a name on the tablet? Can they read what it says? Do they just trust that the medication in their box is correct? How can they properly take care of themselves if they can not even confirm that what they are taking is the right medication? To combat this issue that many face, we present PillTank.

To decrease the risk of consuming the wrong medication, PillTank identifies the …

A Study On The Mental Health Of Women In The Csse Department Of California Polytechnic State University, Sophia Lao, Gabriella Garcia Nobili

Computer Science and Software Engineering

The goal of this paper is to explore the perceived effect that the Computer Science Curriculum has on the mental health of female students. To discover these effects we conducted 50 interviews over a period of several months with the female students of the Computer Science and Software Engineering (CSSE) department at California Polytechnic State University in San Luis Obispo. The total amount of Computer Science (CSC) majors at this institution is approximately 680, with 150 of them being female, so we were able to gather responses from 33.3% of the female CSC students from our interviews. It is worth …

Identifying Hourly Traffic Patterns With Python Deep Learning, Christopher L. Leavitt

Computer Engineering

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.

Grammar-Based Procedurally Generated Village Creation Tool, Kevin Matthew Graves

Computer Engineering

This project is a 3D village generator tool for Unity. It consists of three components: a building, mountain, and river generator. All of these generators use grammar-based procedural generation in order to create a unique and logical village and landscape each time the program is run.

Evaluating Projections And Developing Projection Models For Daily Fantasy Basketball, Eric C. Evangelista

Master's Theses

Daily fantasy sports (DFS) has grown in popularity with millions of participants throughout the world. However, studies have shown that most profits from DFS contests are won by only a small percentage of players. This thesis addresses the challenges faced by DFS participants by evaluating sources that provide player projections for NBA DFS contests and by developing machine learning models that produce competitive player projections.

External sources are evaluated by constructing daily lineups based on the projections offered and evaluating those lineups in the context of all potential lineups, as well as those submitted by participants in competitive FanDuel DFS …

Cleaver: Classification Of Everyday Activities Via Ensemble Recognizers, Samantha Hsu

Master's Theses

Physical activity can have immediate and long-term benefits on health and reduce the risk for chronic diseases. Valid measures of physical activity are needed in order to improve our understanding of the exact relationship between physical activity and health. Activity monitors have become a standard for measuring physical activity; accelerometers in particular are widely used in research and consumer products because they are objective, inexpensive, and practical. Previous studies have experimented with different monitor placements and classification methods. However, the majority of these methods were developed using data collected in controlled, laboratory-based settings, which is not reliably representative of real …

Finding Spanning Trees In Strongly Connected Graphs With Per-Vertex Degree Constraints, Samuel Benjamin Chase

Computer Science and Software Engineering

In this project, I sought to develop and prove new algorithms to create spanning trees on general graphs with per-vertex degree constraints. This means that each vertex in the graph would have some additional value, a degree constraint d. For a spanning tree to be correct, every vertex v_i in the spanning tree must have a degree exactly equal to a degree constraint d_i. This poses an additional constraint on what would otherwise be a trivial spanning tree problem. In this paper, two proofs related to my studies will be discussed and analyzed, leading to my algorithm …

Topographic Maps: Image Processing And Path-Finding, Calin Washington

Master's Theses

Topographic maps are an invaluable tool for planning routes through unfamiliar terrain. However, accurately planning routes on topographic maps is a time- consuming and error-prone task. One factor is the difficulty of interpreting the map itself, which requires prior knowledge and practice. Another factor is the difficulty of making choices between possible routes that have different trade-offs between length and the terrain they traverse.

To alleviate these difficulties, this thesis presents a system to automate the process of finding routes on scanned images of topographic maps. The system allows users to select any two points on a topographic map and …

Acceleration Of Jaccard's Index Algorithm For Training To Tag Damage On Post-Earthquake Images, Kyle John Mulligan

Master's Theses

There are currently different efforts to use Supervised Neural Networks (NN) to automatically label damages on images of above ground infrastructure (buildings made of concrete) taken after an earthquake. The goal of the supervised NN is to classify raw input data according to the patterns learned from an input training set. This input training data set is usually supplied by experts in the field, and in the case of this project, structural engineers carefully and mostly manually label these images for different types of damage. The level of expertise of the professionals labeling the training set varies widely, and some …

Improving Swarm Performance By Applying Machine Learning To A New Dynamic Survey, John Taylor Jackson

Master's Theses

A company, Unanimous AI, has created a software platform that allows individuals to come together as a group or a human swarm to make decisions. These human swarms amplify the decision-making capabilities of both the individuals and the group. One way Unanimous AI increases the swarm’s collective decision-making capabilities is by limiting the swarm to more informed individuals on the given topic. The previous way Unanimous AI selected users to enter the swarm was improved upon by a new methodology that is detailed in this study. This new methodology implements a new type of survey that collects data that is …

Detecting Speakers In Video Footage, Michael Williams

Master's Theses

Facial recognition is a powerful tool for identifying people visually. Yet, when the end goal is more specific than merely identifying the person in a picture problems can arise. Speaker identification is one such task which expects more predictive power out of a facial recognition system than can be provided on its own. Speaker identification is the task of identifying who is speaking in video not simply who is present in the video. This extra requirement introduces numerous false positives into the facial recognition system largely due to one main scenario. The person speaking is not on camera. This paper …

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.

Procedurally Generating Genetic Keys, Adam A. Levasseur

Computer Engineering

This project presents a method for creating multi-part models based on input keys to generate new, variant models via genetic algorithms. By utilizing 3D models as modular parts, this method allows for the generation of a unique, compound model based on one or multiple input keys. This paper explains the process of creating and testing such generation styles using simple geometry to create more complex, compound models.

Automated Grading Of Handwritten Numerical Answers, Mark T. Brown

Computer Engineering

The objective of this project was to automate the process of grading handwritten numerical answers in a classroom setting. The final program accepts a scanned answer sheet completed by the student along with a description of the correct answers and produces a detailed report describing the confidence of correctness for each answer.

Computer vision techniques are used to automatically locate the locations of the answers in the scan. Each digit is then passed through a convolutional neural network to predict what was written by the student. The individual probabilities of each digit produced by the network are aggregated into a …

Iota Pi Application For Ios, Deborah Newberry

Computer Science and Software Engineering

Kappa Kappa Psi is a national honorary fraternity for college band members. They meet every Sunday night, and during these meetings they plan events (both internal and external) that aim to meet our goal of making sure that the Cal Poly band programs have their social, financial, material, and educational needs satisfied. This paper details the steps I took to create an application for them to use internally to help ease organizational processes.

Gpumap: A Transparently Gpu-Accelerated Map Function, Ivan Pachev

Master's Theses

As GPGPU computing becomes more popular, it will be used to tackle a wider range of problems. However, due to the current state of GPGPU programming, programmers are typically required to be familiar with the architecture of the GPU in order to effectively program it. Fortunately, there are software packages that attempt to simplify GPGPU programming in higher-level languages such as Java and Python. However, these software packages do not attempt to abstract the GPU-acceleration process completely. Instead, they require programmers to be somewhat familiar with the traditional GPGPU programming model which involves some understanding of GPU threads and kernels. …

Implementation And Testing Of A Book Lookup System For The Robert E. Kennedy Library, Casey C. Sheehan

Computer Science and Software Engineering

The goal of this senior project centered around improving the quality of student and teacher experiences when visiting the library. The task of finding a book amongst the shelves is an arduous one, which I felt could be improved upon through implementation and testing of a Book Lookup system for the Cal Poly Robert E. Kennedy Library. Development for this project was done using a Python framework. Testing and earlier designs were also created using JavaScript and PHP. Repeated tests were conducted on the accuracy of the software and its ability to decrease user search-time when compared to conventional methods.

Optimization And Coding Of A Lcls Control Program, Tanner M. Worden

STAR Program Research Presentations

SLAS’s, Linac Coherent Light Source (LCLS) also known as X-ray free-electron laser (XFEL) is the first X-ray laser of its kind. It gave Scientist from around the world the unique ability to observe the world at a subatomic level. Allowing for major advancements in the field of biological chemistry, drug science, material science and many more. Since the LCLS is a fairly unique scientific instrument, the demand for its use by the scientific community has always been high since it turned on back in 2009. This means that any and all time that the laser is not being used for …