Engineering Commons^™

Analyzing Patterns In Hofstede’S Cultural Dimensions Towards Individual Ai Receptiveness For Affective Experiences, Maggie Yang

Master's Theses

The use of artificial intelligence (AI) has significantly advanced efficient decision-making, with trust in algorithmic decisions shown to vary by cultural upbringing [1]. As AI becomes increasingly embedded in everyday life, it is essential to examine how cultural values affect trust in AI in subjective contexts that extend beyond purely quantitative analysis, like the personal interpretation of art. This work utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards AI predictions during art interpretation, providing insight into individual susceptibility to bias in AI-assisted affective analysis.

The study leveraged a cultural dimension survey and a custom Java program connected …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Per- And Poly-Fluoroalkyl Substances Fate Across California Wastewater Treatment Plants: A Meta-Analysis Of Formation, Distribution, And Persistence, Elizabeth Reineke

Master's Theses

Per- and poly-fluoroalkyl substances (PFAS) are persistent contaminants that move through municipal and industrial wastewater systems with limited attenuation. As a result, they are increasingly detected in drinking water supplies. Despite growing regulatory concern, a systems-level understanding of PFAS behavior across multiple treatment facilities and watershed settings remains incomplete. This study compiled influent, effluent, and biosolids datasets from more than one hundred California wastewater treatment plants to evaluate PFAS occurrence, transformation, and partitioning across diverse treatment configurations. Analytical steps included calculating removal efficiencies, assessing precursor-to-product oxidation, evaluating co-contaminant correlations, and grouping facilities by process design to quantify configuration-specific fate patterns. …

Hallucination Techniques For Self-Supervised Synthetic Datasets For Mobile Robots, Wyatt D. Colburn

Master's Theses

Classical techniques in autonomous navigation struggle in tightly constrained spaces. Machine learning has been shown to perform better in these difficult environments but most techniques require large amounts of navigation experience for training. Using a new machine learning paradigm learning from hallucination (LfH), training data can be collected in a safe environment and not require supervision. Data is collected in real time while an agent performs a random walk in free space, supervision is not required as there are no obstacles for the robot to run into. After a random walk a post processing pipeline will hallucinate a safety corridor …

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.

Development Of A Colorectal Cancer Spheroid Model To Improve The Accuracy Of Preclinical Drug Testing, Jillian Trilevsky

Master's Theses

Colorectal cancer is the second leading cause of cancer related deaths worldwide. It currently affects millions of people across the globe and is only expected to increase in impact over the coming years. The most common treatment for metastatic colon cancer is chemotherapy, however, the development of chemotherapeutic drugs is a long and expensive process. A large portion of this development process is spent in preclinical drug testing. However, the models used often lack enough physiological relevance to guarantee the drug’s success in a clinical trial. Due to this gap in testing, researchers seek to develop a more physiologically relevant …

Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran

College of Engineering Summer Undergraduate Research Program

This research project will develop and evaluate a smartphone-based, AI-powered system to crowdsource and analyze accessibility features and barriers in public spaces. Using computer vision and geospatial mapping, the system will identify and categorize issues such as uneven sidewalks, missing or inadequate curb ramps, damaged tactile paving, obstructive overhangs, and the absence of visual or auditory wayfinding cues. The overarching goal is to generate a dynamic, real-time accessibility map that empowers individuals with diverse mobility, sensory, and cognitive needs to navigate public spaces more safely and confidently. The project will integrate technologies and methods from applied machine learning, mobile computer …

A Computational Approach To Space Trajectory Optimization, Cliodhna Mcguigan, Daniella Luciani

College of Engineering Summer Undergraduate Research Program

With space becoming increasingly accessible, the need for sophisticated space trajectory design has surged, as we challenging existing computational capabilities. This project tackles the intricate and computationally demanding task of spacecraft trajectory optimization and real-time orbit determination by developing and benchmarking advanced numerical algorithms integrated into Cal Poly’s mission design platform, PolySpace. Leveraging cutting-edge Python routines and interfaces with NASA’s General Mission Analysis Tool (GMAT), the research addresses mission-critical scenarios, including multi-gravity-assist interplanetary missions and efficient solar-electric orbit transfers. Benchmarking the solution approach against past missions, the project ensures rigorous accuracy and reliability. This experience will help bring research into …

Multi-Material Printer Development, Jessica Hu, Phoebe Eplett

College of Engineering Summer Undergraduate Research Program

Surgeons require pre-surgical models to practice procedures and improve success rates. However, the current process of creating physical models for practice using 3D printing is limited to producing homogeneous mimics of the human body, while the human body is a heterogeneous structure composed of multiple materials with varying properties, including bones, muscles, and skin. Additive manufacturing methods cannot easily print multiple materials simultaneously, as current AM machines only print homogeneous material, unlike the human body. In this proposal, we aim to develop a multi-material additive manufacturing system, from software to hardware, to manufacture pre-surgical models. We will investigate multi-material AM …

Developing Practical Cfd Skills For Undergraduate Researchers, Max Koerner, Sebastian Macias-Gonzalez

College of Engineering Summer Undergraduate Research Program

As the use of computational fluid dynamics (CFD) grows in the aerospace (and other engineering disciplines), the need for coursework, and in particular labs, that develop the appropriate CFD skills is growing. In the semester transition, the Aerospace Engineering Department will be offering an applied computational aerodynamics class that will have a heavy emphasis on practical CFD applications to realistic problems to be encountered by our students. This research activity will help develop labs that will be used to teach students how to use StarCCM+ (the department’s current commercial CFD tool) starting from simple geometries going up to complete airframes. …

Surp: Space Robotics Laboratory Lab Manuals And Experiment Development, Connell Crawford

College of Engineering Summer Undergraduate Research Program

This SURP project is focused on the preparation of the lab, experiments, and operation procedures necessary for the proposed equipment in the Space Robotics Lab. As such, the primary goal is to create safety and test documentation that shall be used in the lab. Students selected for this project shall gain a hands-on learn-by-doing with equipment that is intended for teaching and research of a simulated planar space test environment for an air-bearing vehicle test bed to be able to test sensors, actuation and deployment of mechanisms, spacecraft collaboration through closed loop control, as well as experimental propulsion systems.

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 …

Design Of Ballistic Armor Using Multi-Composite Sandwich Structures With Nanomaterial Additives, Carmen Alaichamy

College of Engineering Summer Undergraduate Research Program

This study explores the bulletproof capabilities of Kevlar composites fabricated using advanced additive manufacturing techniques. Continuous fiber reinforced 3D printing (CFRP) is employed to produce Kevlar-reinforced polymer matrix composites (PMCs) with optimized structural configurations for ballistic protection. The primary objective is to evaluate the impact resistance of these composites against 9mm projectiles through systematic experimental testing. A series of ballistics tests are conducted using a high-velocity gas-gun system to fire 9mm projectiles at varying speeds angles. The tests will be conducted at the San Luis Obispo Range, with projectiles fired at various angles. The effects of fiber volume fraction, reinforcement …

Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro, Nina St. John

College of Engineering Summer Undergraduate Research Program

Microscopic imaging is essential to characterize multi-scale material behavior and understanding structure-property relationships. Recently our group developed a deep learning approach based on a Generative Adversarial Network (GAN) to reconstruct and artificially generate microstructures of strain-sensing nanomaterial networks based on microscope imagery. In this SURP project we would like to evaluate an alternative approach called diffusion to see if we can improve the quality of our results. Furthermore, we aim to test our approaches on a wider variety of materials, which will have different microstructures, to evaluate how versatile our models are.

Building Bridges, Bridging The Gap: Measuring Engineering Confidence Across Ses, Amori Waller

College of Engineering Summer Undergraduate Research Program

Learning from failure is an essential component of both learning and practicing engineering. However, failure is often stigmatized and avoided in engineering education. This project aims to better understand how to support students throughout their engineering education to help them learn from their failures, rather than become frustrated or discouraged by them. The project will build on prior research in students’ responses to failure experiences to specifically analyze students who respond to failure in different ways and build on these experiences to help students in similar situations. During the SURP project, the student will use qualitative methods to analyze interview …

Safety-Critical Formation Control Of Non-Holonomic Multi-Robot Systems In Communication-Limited Environments, Logan Beard

College of Engineering Summer Undergraduate Research Program

This project explores advanced methodologies for distributed planning, formation control, and coordination in heterogenous multi-agent robotic systems consisting of small mobile robots and nano unmanned aerial vehicles (UAVs). Leveraging decentralized control theories and optimization techniques, the research aims to develop robust algorithms for real-time collaborative task execution, efficient formation maintenance, and adaptive coordination strategies. Python and ROS will be used extensively to simulate, validate, and experimentally deploy distributed robotics algorithms. The student researcher significantly contributes to the theoretical and practical advancement of multi-agent system technologies.

Behind The Prompt: The Environmental Impact Of Llm Inference, Lucy Hegenderfer, Isaac Huang

College of Engineering Summer Undergraduate Research Program

As the size and demand for large language models (LLMs) increase, the environmental impact of computational inference often exceeds training; yet industry lacks a standardized method of calculating this expanding environmental footprint. Complexity arises with task-specific computational demands, infrastructure overhead, and various GPU architectures, making cross-model assessments burdensome. Combining environmental engineering and computer science principles by validating Jegham et al.’s meta-model, we predict the carbon emissions and water consumption during inference, providing metrics to raise user awareness of AI’s growing environmental footprint. Additional work supports integration into a multi-agent conversational system that encourages responsible scheduling and prompting, guiding the user …

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 …

Constructing A High-Performance Iot Pipeline For Smart Manufacturing Environments, Seth Langel

College of Engineering Summer Undergraduate Research Program

The Fourth Industrial Revolution, or Industry 4.0, integrates a range of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Cloud Computing, and Data Analytics to improve the efficiency, productivity, scalability, and security of modern manufacturing systems. Smart manufacturing leverages these technologies across various domains to enhance data-driven decision-making and quality control in production processes. In a smart manufacturing environment, heterogeneous IoT sensors interact with each other and control systems to automate real-time monitoring, analysis, and decision-making. This integration enables manufacturers to optimize production, quickly detect and address anomalies, reduce environmental impact, and adapt rapidly to changing …

Eggbeater Antenna Design 915 Mhz, Anshul Deshmukh

College of Engineering Summer Undergraduate Research Program

The Sal-E cube sat mission that is planned for launch in 2026 includes a 902-928 MHz receiving module called the Space Quacker Advanced Development (SQUAD) module. The SQUAD module uses the LoRa modulation format for unlicensed uplink to the satellite using the 902-928 MHz Industrial, Scientific, and Medical (ISM) band. The goal of the SQUAD module is to demonstrate the link robustness of the LoRa communication standard to a low earth orbit (LEO) satellite using this ISM band. To demonstrate this communication link, a 902-928 MHz uplink ground station needs to be established at Cal Poly. The goal of this …

Ai-Driven Embedded Camera System For Real-Time Traffic Anomaly Detection, Isaac Pruett

College of Engineering Summer Undergraduate Research Program

In this project, we will collaborate with Caltrans District 5 (covering San Luis Obispo County and surrounding regions) to develop a small, battery-powered, camera-based embedded system utilizing an NVIDIA Jetson board and neural networks to detect highway traffic anomalies. The device will analyze real-time traffic flow patterns and send alerts regarding detected anomalies. Unlike the stationary commercial camera systems currently in use, the proposed system offers increased mobility, affordability, and will give Caltrans engineers improved access over system outputs.

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 …

Exploring Impact Of Student’S Proximity To Summer Camp And Demographics On Their Interests In Engineering, Yamil Balcells

College of Engineering Summer Undergraduate Research Program

EPIC is a one-week Cal Poly program where middle-and high-school students explore engineering through hands-on projects in a university setting. In partnership with the Migrant Education Program (MEP), EPIC reserves spots for migratory students and provides bilingual counseling and support. These services ensure equitable access and a welcoming environment for students developing English proficiency.

Ai Agents For Search And Rescue (Ai4sar), Nathan Huang, Lakshana Viswa

College of Engineering Summer Undergraduate Research Program

The goal of this summer research activity is to expand the capabilities of a system developed in the larger AI in Search and Rescue project. This project supports volunteer organizations participating in the search for missing persons by providing a basic framework for the collection and organization of relevant information, augmented with specific components that utilize a variety of AI methods. The focus of the summer research will be on the development of agent components for selected roles and tasks in a search and rescue mission. The agents utilize generative AI methods such as Large Language Models (LLMs) to provide …

Stretchable Mechanoluminescent Devices For Energy Harvesting And Real-Time Force Sensing, Lucas Taliaferro, Phoebe Ong

College of Engineering Summer Undergraduate Research Program

Our group has been developing a novel manufacturing technique to fabricate flexible sensing devices using electrostatic force. Previously, we focused on utilizing nanomaterials as the sensing materials to measure strains. Building on our experience with the manufacturing technique, we will move forward to incorporate other smart materials in the flexible device to achieve self-powered sensors. Besides, to better understand the fabricated material properties, we are interested in characterizing the microstructural behavior of the material networks via microscopic imaging and finite element simulations. The students will have the opportunity to closely work with Dr. Wang’s interdisciplinary research group.

Analyzing Wearable Sensor Data From Individuals Undergoing Motor And Neurological Rehabilitation, Nolan William Turk

College of Engineering Summer Undergraduate Research Program

An ongoing study funded by the National Science Foundation (NSF) is focused on developing computational models of rehabilitation for people post-stroke. Stroke affects around 800,000 people per year in the US, and often leaves people with limited motor (movement) and neurological (brain-based) capability. Wearable sensors may allow clinicians to better understand how these individuals recover, and to better design therapies and interventions. We are seeking students who can use existing software, and perhaps adapt the software to extract, analyze, and visualize detail from study participants. This project will involve with the Cal Poly PI, and collaborators from physical therapy. This …

Analyzing Wearable Sensor Data From Individuals Undergoing Motor And Neurological Rehabilitation, Carly Smith

College of Engineering Summer Undergraduate Research Program

An ongoing study funded by the National Science Foundation (NSF) is focused on developing computational models of rehabilitation for people post-stroke. Stroke affects around 800,000 people per year in the US, and often leaves people with limited motor (movement) and neurological (brain-based) capability. Wearable sensors may allow clinicians to better understand how these individuals recover, and to better design therapies and interventions. We are seeking students who can use existing software, and perhaps adapt the software to extract, analyze, and visualize detail from study participants. This project will involve with the Cal Poly PI, and collaborators from physical therapy. This …

Radiative Heat Transfer Using Spectrometers, Metztli Singha

College of Engineering Summer Undergraduate Research Program

Radiative heat transfer and the fundamental understanding of the electromagnetic spectrum, ranging from infrared to ultraviolet, are crucial topics for space environments and aerodynamic re-entry systems. The advancement of the aerospace curriculum in these areas will lay the cornerstone for undergraduate students focusing on experiential learning. A specific laboratory experiment involving black body radiation and modes of heat transfer, with a particular emphasis on radiation, will be scoped, designed, and fabricated during the SURP performance period. The outcomes of this work will standardize the introductory courses on heat transfer specific to aeronautics and astronautics concentrations, which is mainly lacking outside …