Digital Commons Network^™

Advancing Mobileclip Through Hybrid Quantization: A Cpu-Focused Approach, Atiqur Rahman

2025 Fall Honors Capstones Projects - Archive

MobileCLIP is a compact model that connects images and text, enabling it to perform tasks like image identification and question answering without needing to be retrained for each new task. Although it’s designed to be lightweight, it still runs slowly on regular computers without a powerful graphics card (GPU). This research focuses on making MobileCLIP run faster and smaller by using post-training quantization, which reduces the model’s precision after training without hurting performance. We combined several strategies: analyzing which parts of the model are more sensitive to changes, applying targeted adjustments to its structure, and running everything using CPU-only tools. …

2025 Commencement Program - Fall, Morehead State University. Registrar's Office.

Morehead State Commencement Programs

2025 Fall Commencement program for Morehead State University.

Improved Context For Llm Queries On Knowledge Graphs Using The Model Context Protocol, Talha Tahmid

2025 Fall Honors Capstones Projects - Archive

Large Language Models (LLMs) struggle on factual, relation-heavy questions without structured external knowledge. This thesis implements a standards-based pipeline that connects LLMs to Resource Description Framework (RDF) knowledge graphs through the Model Context Protocol (MCP). The system comprises an MCP tool that executes SPARQL against approved endpoints, an Natural Language (NL) to SPARQL step in which the LLM (ChatGPT) generates the SPARQL query using prompt-based templates, followed by a generation stage conditioned on the retrieved graph facts. Final experiments focus on the Rhea knowledge graph. We evaluated the same base model with and without MCP on a 50-question benchmark spanning …

Impact Of Ionizable Lipid Variation On The Immunogenicity Of Lipid Nanoparticles, Chloe M. Krueger, Abbey L. Stokes, Shilpi Agrawl, Christopher E. Nelson

Annual Student Research Poster Session

Lipid nanoparticles (LNPs) are a leading nonviral delivery system for nucleic acid therapeutics due to their scalability and efficiency. However, certain formulations may trigger undesired immune responses. This study aimed to assess the inflammatory potential of LNPs formulated with different ionizable lipids using a murine macrophage reporter cell line (RAW-IRCs). RAW-IRCs express GFP upon successful mRNA delivery and mRFP1 upon activation of inflammatory pathways. A library of LNPs was synthesized via vortex mixing and characterized for hydrodynamic diameter, polydispersity index, and encapsulation efficiency. Treated RAW-IRCs were analyzed by flow cytometry to evaluate GFP and mRFP1 expression. Our results highlight seven …

Design And Development Of An Intervention To Improve The Quality And Safety Of Pediatric Dental Sedation: A Human-Centered Design Approach, Kawtar Zouaidi, Jan Yeager, Suhasini Bangar, Sayali Tungare, Urvi Mehta, Janelle Urata, Alfa-Ibrahim Yansane, Thomas Tanbonliong, Jungsoo Kim, Emily Sedlock, Krishna Kumar Kookal, Yan Xiao, Tokede Oluwabunmi, Heiko Spallek, Amy Franklin, Gregory W Olson, Joel White, Elsbeth Kalenderian, Muhammad F Walji

Faculty, Staff and Student Publications

Background: There are gaps in understanding the experiences of children, parents, and providers during dental conscious sedation. This study aimed to capture and analyze these experiences to identify opportunities for improvement and enhance the quality and safety of pediatric dental conscious sedation.

Methods: A human-centered design approach was used to examine the conscious sedation experience in 2 US advanced education pediatric dental clinics. Researchers conducted field observations, interviews with providers and parents, and providers focus groups to explore experiential factors. Data were transcribed and analyzed using content thematic analysis. Insights from the data were used to explore and generate new …

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 An Inclusive Ai Chatbot For Diverse Student Communities At Cal Poly: Uplift Ai, Gideon Telahun

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 …

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 …

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.

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 …

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 …

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 …

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 …

How Does User Control Reduce Irritation Of Mid-Roll Ads, Elijah Villanueva

College of Engineering Summer Undergraduate Research Program

Large video platforms like YouTube and Twitch rely extensively on advertising for revenue. Often, they deploy mid-roll advertising: ads that play in the middle of video content, interrupting it. Such interruptions can irritate consumers significantly. This project primarily involves conducting user testing of an already-developed YouTube browser extension that that gives users some control over when mid-roll ads play. We hope to ascertain how effectively the design mitigates user irritation from mid-roll ads. Tasks will involve recruiting people into a laboratory setting where they will use the browser extension, interviewing them about their experience, and manually extracting themes from the …

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 …

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 …

Propeller Characterization Lab, Stefanos Rosenbaum

College of Engineering Summer Undergraduate Research Program

This research focuses on creating an experiment to measure performance of an aircraft propeller on a specially designed stand. Results from the wind tunnel experiments measuring thrust, rotation speed and torque will enable students to create a database of propeller characteristics for use in aircraft design projects. Students in aerospace engineering are regularly assigned design projects powered by turboprop or propeller driven engines. There is not an easy way to verify design performance other than simplistic calculations or extrapolation of open-source wind tunnel data, and not a lot of data is available. Being able to correlate actual test data from …

Deep Learning In Eye-Tracking Biomarkers For Anomaly Detection, Jay Rajesh

College of Engineering Summer Undergraduate Research Program

This research project proposes the development of a novel, data-driven framework for detecting concussions using machine learning (ML) and deep learning (DL) models applied to high-resolution eye-tracking data. Unlike traditional concussion assessments that rely on subjective evaluations, this work seeks to identify objective, quantifiable biomarkers derived from ocular dynamics—such as saccadic velocity, smooth pursuit accuracy, and pupillary response—captured through advanced eye-tracking technology. The project will explore state-of-the-art feature extraction techniques and predictive modeling approaches to uncover subtle neuro-ocular signatures associated with mild traumatic brain injury. By combining principles from biomedical signal processing, artificial intelligence, and neurophysiology, this work advances current …

Reinforcement Learning For Autonomous Parking, Ravi Panchal

College of Engineering Summer Undergraduate Research Program

This research project proposes the development of an adaptive reinforcement learning (RL)-based parking system designed to handle complex parking maneuvers that are often unaddressed in existing research. Unlike previous works that focus on isolated maneuvers such as reverse parking or parallel parking, this work presents a flexible framework where multiple parking types (reverse, parallel, diagonal) are addressed through independent agents and then integrated into a cohesive system. The primary gap addressed by this work is the integration of diverse parking maneuvers into a unified RL framework with adaptability to dynamic and varied parking environments. Additionally, this project introduces curriculum learning …

A Novel Hybrid Re-Entrant Double Arrowhead With Active Link Auxetic Metamaterial: Finite Element Approach, April Nguyen

College of Engineering Summer Undergraduate Research Program

Auxetic metamaterials are a category of material that exhibit a negative Poisson's ratio (NPR). NPR materials contract when compressed and expand when stretched. NPR properties are typically produced through a complex unit cell consisting of folds, internal angles, or other specially designed shapes with internal voids capable of collapsing in on themselves. Individual unit cells that display these properties are developed and stacked or layered in a repeating pattern such that a larger body can be manufactured, maintaining the same properties. NPR auxetic structures show either a stretch-dominated mechanism (SDM) or a bending-dominated mechanism (BDM). SDM-based NPR structures are favored …

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 …

Refurbishing And Deploying Oceanographic Equipment, Matthew Moore

College of Engineering Summer Undergraduate Research Program

In this SURP project, a student will help catalog, refurbish, test, and then deploy oceanographic equipment into Morro Bay and nearby coastal regions. In 2024, the Talke lab inherited approximately $300-400k of oceanographic equipment (sticker price) that was originally bought between 2000-2020. Instruments include multiple pressure gauges, velocity instruments, salinity-temperature-turbidity gauges, particle sizers, and a sonar for making bathymetric measurements. Help is needed to check (“talk to”) these instruments, determine which still work, and then field deploy them into the central coast., For some instruments, additional hardware (batteries, cables) and communication adapters may be needed. Because instrument software is often …

Relational Algebra Interpreter, Sydney Lynch

College of Engineering Summer Undergraduate Research Program

We would like to build a compiler for relational algebra that converts it to SQL. This compiler will be used in database labs to give the students hands-on experience to write relational algebra code. Current relational algebra compilers that are open source are not very good and are hard for the students to use.

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. …

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.

Hand-Tracking And Extended Reality Interfa, Alexander Bloomer, Alberto Cornejo

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 …

Hpc Configuration And Automated System Administration, Matty Witt, Deep Singh, Christopher Imirian

College of Engineering Summer Undergraduate Research Program

With the exponential growth in the use of computing, there is a growing need for undergraduate students to enter the workforce with experience with more complicated computing architectures. The CFD research group in the Aerospace Engineering Department received an HPC system and related computing hardware through the Air Force Research Lab. This system consists of three components: (1) a cluster compute engine with 256 CPU cores, 3.2 TB of RAM, 4 Tesla A100 GPUs, and 200 Gbps InfiniBand network backplane; (2) a high performance storage platform with 540 TB of raw storage, 200 Gbps InfiniBand network, and BeeGFS parallel cluster …

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 …

Integrating Mobility Dynamics Into Facility Location Modeling And Optimization, Daniel Hopkins

College of Engineering Summer Undergraduate Research Program

Facility location optimization is a foundational area in operations research and data analytics that is concerned with determining the optimal placement of facilities to serve a spatially distributed demand. However, traditional facility location decision is often approached from a centralized perspective, where the facility planner dictates the allocation of customers to facilities. In this setting, it is typically assumed that customers patronize the nearest facility, and their preferences are not explicitly modeled. This traditional decision-making framework may not accurately reflect real-world dynamics where customers may choose facilities based on a variety of factors beyond proximity. Thus, this project aims to …

Supporting Migrant Education Program Students, Yaneli Cruz

College of Engineering Summer Undergraduate Research Program

This project explored the impact of the EPIC engineering camp on Migrant Education Program (MEP) participants, a group often academically disadvantaged due to frequent moves, limited resources, and lack of encouragement to pursue higher education. Because no new IRB-approved data could be collected during camp, pre- and post-camp surveys that students had already completed were analyzed. I converted the data into CSV files, built SQL tables, and wrote a Python script to automate the process of filtering and comparing MEP students, Session 1, with non-MEP peers. Results showed that 28% of MEP students started camp unsure about engineering, but 11% …