Digital Commons Network^™

Leveraging Smartphones For Balance Assessment, Kelly Graham

College of Engineering Summer Undergraduate Research Program

Assessment of human balance provides valuable metrics to track the health, development, and fall risk of individuals. The prominent method for objective balance assessments has used force plates to track the center of pressure (COP) position as a participant attempts to balance during varying tasks. However, the use of force plates is limited by the cost of equipment and expertise required, leading to recent interest in using embedded inertial measurement units (IMUs) in mobile devices instead. Many researchers have explored placing mobile devices close to the subject’s center of mass (COM) to approximate the subject’s COM acceleration and using the …

Modeling An Energy Management System For Residential Hybrid Ac/Dc Power Networks, Theodor Buerchner, Giovanni Malone, Alex Maldonado

College of Engineering Summer Undergraduate Research Program

In pursuit of supporting the global efforts in reducing carbon footprint and reliance on fossil fuels, this project seeks to continue the development of a hybrid AC/DC house prototype at Cal Poly State University. To enhance the power flow to DC loads, a dedicated 48 V DC bus will be constructed to replace the impractical multiple DC buses in the previous system. This iteration will also add a key feature that enables users to monitor real-time AC and DC powers. Another new functionality will involve the provision of a mix of latching and non-latching relays to switch between sources, thus …

Ai Fact-Checking Claims In Videos, Jake Altieri

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 …

Sustainable Development Of Sensing Materials For Structural Health Monitoring, Nat Conti, Matthew Robinson

College of Engineering Summer Undergraduate Research Program

Sensing technologies play significant roles in structural health monitoring (SHM) systems for monitoring and assessing structural conditions in real-time, which can enhance the safety and reliability of various structures. While engineered nanomaterial (ENM)-based sensors have remarkable potential to transform conventional sensing devices, large volume of ENMs released into the environment can significantly jeopardize the environment and public health. Thus, there is a pressing need to develop next-generation sensing materials in a more eco-friendly and sustainable manner. The goal of this interdisciplinary proposal is to sustainably develop sensing nanocomposites for monitoring structural damage by re-using waste materials as nano-/micro-scale functional material …

Computational Investigation Of The Role Of 3d Genome Architecture In The Lifecycle Of The Malaria Parasite, Srish Maulik

College of Engineering Summer Undergraduate Research Program

Malaria, a mosquito-borne infectious disease caused by the Plasmodium parasite, is responsible for more than a half a million deaths per year, the vast majority of which occur in central Africa. The parasite undergoes an incredibly complex cell molecular transformation as it transitions from living in mosquitoes to living in humans with different sets of genes being activated or silenced in order to evade the immune system of the host. Understanding how its genome guides this transition is critical for developing adequate treatments. In this project, we aim to develop a computational framework for investigating the role of the three …

Building Pathways To Computer Science Careers For Latinx Students Through Multilingual Collaborative Block-Based Programming, Cis Garcia, Noemi Corona Calvario

College of Engineering Summer Undergraduate Research Program

The underrepresentation of Latinx students in computer science highlights the need for innovative and inclusive educational approaches. This project addresses challenges such as limited access to educational resources and the demand for multilingual learning tools by developing a co-located, collaborative, game-based programming environment. Designed for use on phones, tablets, and laptops, this tool supports English, Spanish, and Mixtec, facilitating broader engagement. By promoting peer collaboration and interactive learning, our approach challenges traditional notions of solitary programming and reinforces the idea that expertise is shared, fostering an inclusive and equitable learning environment.

Wearable Sensing Systems And Data Analytics For Pressure Sensing Prosthetics, Aiden Freeland

College of Engineering Summer Undergraduate Research Program

This interdisciplinary research, in collaboration with Sony, aims to improve the fit and comfort of socket prosthetics for amputees by utilizing sensing technology and data analytical techniques. Many amputees face issues with prosthetic fit, which can lead to discomfort, pain, and even tissue damage. Our goal is to address these problems by developing a low-cost, universal, and wearable sensing system that can continuously monitor the pressures at the residual limb and prosthetic socket interface. This product will provide feedback to the user, allowing for real-time adjustments, ensuring a comfortable fit, and avoiding injury. Our research group has extensive experience in …

Deterministic Motion Planning For Highly Articulated Multi-Link Robots, Matthew Flynn

College of Engineering Summer Undergraduate Research Program

Slender, multi-link, highly articulated, and extensible robots designed for minimally invasive surgeries have the potential to significantly transform the performance of common medical procedures. These advanced robots can reduce uncertainties and risks associated with surgeries, leading to shorter patient recovery times, accelerated healing, and minimized scarring. Made possible by their numerous mechanical linkages and concentric mechanisms, these multi-link articulated robots can navigate along non-linear paths, a capability that traditional straight probes lack. This flexibility allows surgeons to perform minimally invasive procedures on clinically significant targets that were previously difficult or impossible to access while avoiding vital anatomical structures. Beyond their …

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 …

Augmented Biomechanics Integration For Real-Time Movement Optimization, Jack Bergfeld, Liyen Ho, Dylan Featherson

College of Engineering Summer Undergraduate Research Program

This project aims to integrate OpenCap, a markerless motion capture system, with augmented reality (AR) to optimize real-time human movement. By leveraging biomechanics principles, AR visualization, and machine learning (ML), the system will provide instant feedback to users, improving movement efficiency while minimizing joint and muscle stress. Previous research in 2024-2025 has successfully demonstrated 2D motion tracking and AR-based mapping onto another person for interactive comparison. This project will build upon that foundation by enhancing real-time 3D motion tracking and developing an advanced AR interface to guide users in sports training, rehabilitation, and workplace ergonomics. The integration of ML will …

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 …

Developing An Inclusive Computational Platform For Aerospace Education Using Nasa’S Emtg, Tia Bajaj

College of Engineering Summer Undergraduate Research Program

This project will establish comprehensive guidelines and a strategic action plan for developing an inclusive and accessible computing platform that integrates NASA's Evolutionary Mission Trajectory Generator (EMTG) software with PolySpace, Cal Poly’s in-house space mission design toolkit. Employing Universal Design for Learning (UDL) principles, the project will ensure equitable access and participation for diverse undergraduate aerospace engineering students, emphasizing inclusion for women and underrepresented groups in aerospace. Inclusivity will be promoted by creating detailed guidelines for remote software interfaces and visualization layers specifically designed for diverse learning styles and accessibility needs. A blueprint for an inclusive curriculum module will also …

Hands-On Microgrid Education: Using Programmable Dc-Dc Converters To Teach Power & Energy Systems, Alejandra Zuniga

College of Engineering Summer Undergraduate Research Program

This project will develop an analog computing circuit that can accelerate power system simulations used for grid interconnection studies. The project will leverage analog computing to create a specialized circuit capable of simulating large-scale power networks with detailed models of power electronics-based loads, such as those found in data centers and manufacturing plants. A software application programming interface will be developed to integrate this circuit with a desktop computer, where simulations can be run by the user. The project team will also work with industry partners and utilities to evaluate the feasibility of the proposed technology for conducting real-world grid …

Investigating Engineering Students Responses To Failure, Denis Gonzalez-Reyes

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 …

Characterization Of Zwitterion/Salt Electrolyte Blends For Organic Solid Electrolytes In Lithium-Ion Batteries, Sage Alling, Will Vasser

College of Engineering Summer Undergraduate Research Program

Progress toward durable and energy-dense lithium-ion batteries has been hindered by instabilities at electrolyte–electrode interfaces, leading to poor cycling stability, and by safety concerns associated with energy-dense lithium metal anodes. Organic Solid electrolytes (OSEs) can help mitigate these issues; however, OSE conductivity is often limited by sluggish dynamics through rubbery domains. Recent work has suggested that zwitterionic OSEs can self-assemble into superionically conductive domains, permitting decoupling of ion motion and liquid rearrangement timesscales. Although crystalline domains are conventionally detrimental to ion conduction in SPEs, we this work suggests that properly designed semicrystalline OSEs with labile ion–ion interactions and tailored ion …

Human-Ai Collaboration For Creative Design, Antony Chen

College of Engineering Summer Undergraduate Research Program

Design-by-Analogy (DbA) is a powerful design tool that uses analogical reasoning to help engineers develop groundbreaking innovations, such as cyclonic separator inspired bagless vacuum cleaner or gecko inspired adhesives. DbA leverages the natural, human process of analogical reasoning in a systematic manner in three phases namely: retrieval (what prior knowledge/experience is relevant to a design problem?), mapping (what elements of the design problem align with the retrieved knowledge?), and evaluation (how applicable is the retrieved knowledge to solving a design problem?). To date, most DbA techniques support one or two phases of analogical reasoning and therefore overlook important opportunities for …

Analysis Of Student Inclusivity In Computing Education: Eeg-Based Prediction Of Student Belonging, Alec Odell

College of Engineering Summer Undergraduate Research Program

This project focuses on the use of Natural Language Processing (NLP) techniques to analyze text stimuli used in cognitive research. Specifically, the project involves analyzing text that presents different types of mindsets, such as growth and fixed mindsets, to understand their impact on cognitive state. Students will apply various NLP methods, such as tokenization, text classification, and sentiment analysis, to analyze the language used in different types of mindset stimuli. The goal is to understand how text-based stimuli can influence cognitive responses and to extract meaningful features from the text that can be used to predict outcomes like engagement or …

Analyzing Privacy And Usability Tradeoffs In Multi-Party Relay Systems, Jess Alencaster, Leticia Leon-Rodriguez

College of Engineering Summer Undergraduate Research Program

Nearly everything we do on the Internet leaves a trace, and in recent decades the value of user data has proven to be highly profitable and become a fundamental business strategy of the Internet. The only recourse users have in this situation is seeking increased privacy, yet privacy is uniquely challenging on the Internet because we inherently rely on others (e.g., ISPs, content providers, CDNs) to carry and serve our traffic. Recent systems have sought to enhance user privacy without sacrificing performance by adopting Multi-Party Relay (MPR) architectures, including Apple's iCloud Private Relay. These architectures mask user IP addresses by …

Hybrid Machine Learning--Finite Element Solvers For Solid And Fluid Mechanics, Victor Alcantara-Arias, Spandan Suthar

College of Engineering Summer Undergraduate Research Program

The goal of this project is to develop a new class of hybrid solvers for partial differential equations (PDEs) encountered in solid and fluid mechanics that blend traditional finite element methods (FEM) with modern machine learning algorithms. While FEM solvers are well developed, they can be computationally expensive for realistic problems. Machine learning algorithms have emerged as possible new solutions to cut down the computational cost associated with expensive FEM simulations, but these are typically not interpretable. Previous work on this topic resulted in a class of fully interpretable machine learning solvers for PDEs that had two primary drawbacks: (i) …

Motor Subsystem For A Tensegrity-Based Robotic Exoskeleton, Presley Sacavitch, Israel Villegas

College of Engineering Summer Undergraduate Research Program

Tensegrity structures are composed of stiff rods and elastic cables suspended in a flexible tension network. In particular, the biotensegrity model proposes that all biological systems exhibit tensegrity-like characteristics across multiple scales, ranging from the cellular level to the musculoskeletal system of tendons, ligaments, and fascia, to the human body as a whole. Compared to the traditional biomechanical models used in exoskeleton design, it can be a more accurate representation of how motion emerges from natural forms, but further work is needed to fully understand the heterarchical nature of human anatomy. This project will focus on developing a powered electrical …

Feasibility Study On Large-Scale Geologic Carbon Sequestration In Southern Colorado, Yanrui Ning, Ali Tura, David Herman, Jay Bridgeman, Dana Clark

Michigan Tech Publications

This study evaluates the feasibility of storing over 50 million metric tons of CO2 within a 30-year period in southern Colorado. The target for injection is the 7000 ft (2134 m)-deep Lyons saline aquifer formation, with the overlying alternating layers of anhydrite and shale serving as seals. Geological static models were constructed using seismic, well log and core data, followed by fluid flow modeling to understand the CO2 injection strategy, saturation distribution and plume size. The results indicate that approximately 60 million metric tons of CO2 can be injected with 2 wells into the formation over 30 years, with 85 …

Using Advanced Artificial Intelligence Techniques In Pavement Marking Detection For Asset Management, Paul Clement Akpabio

Theses (2016-Present)

Pavement markings are essential roadway assets that enhance driver guidance, reduce collision risks, and support the operational reliability of autonomous and connected vehicle systems. Maintaining adequate marking visibility, particularly retro reflectivity as required by FHWA MUTCD Section 3A.05, is critical for nighttime safety and for minimizing crash severity in adverse conditions. Traditional assessment methods, including manual inspections, retro reflectometers, and service life estimates, offer useful baseline information but remain slow, labor intensive, and unsuitable for large scale or real time asset management. These limitations have increased interest in artificial intelligence solutions capable of automating pavement condition evaluation with greater consistency …

Developing A Low-Temperature Pathway For The Synthesis Of Two-Dimensional Ws2 Nanosheets, Akhil Potdar

Holster Scholar Projects

Since their discovery in 2004, two-dimensional (2D) materials have attracted great attention due to their unique mechanical, electrical, and chemical properties. However, their integration into devices is limited by the high temperatures required for crystalline growth, which prevents the use of flexible and biocompatible substrates like polymers for biomedical and next-generation electronic devices. This project aims to therefore develop a low-temperature synthesis process for two-dimensional tungsten disulfide (WS₂), a material particularly promising due to its tunable bandgap and biocompatibility. We propose that by first depositing an intermediate tungsten oxide film (WOx) via Hollow Cathode Plasma-Assisted Atomic Layer Deposition (HCP-ALD) and …

Foundations For Multi-Bit-Per-Cell Phase Change Memory Modeling Gst Crossbar Arrays, Sashah Wilson-Thompson

Holster Scholar Projects

This project builds a simulation foundation for selective cell heating in a phase-change memory (PCM) crossbar using Ge2Sb2Te5 (GST) as the active material. Using COMSOL Multiphysics® a 3D modeling software, couples Electric Currents, Electric Circuits, Heat Transfer in Solids, and Electromagnetic Heating for the simulation. A parameterized Tungsten (W)/GST-Amorphous/GST-Crystalline(phases) /W embedded in Silica Dioxide (SiO2) and surrounded in Silica Nitride (Si3N4) is validated at the single-cell level and scaled to small GST crossbars A terminal voltage (V_active/V_inactive, or 0 V if unselected) is applied through MOSFET and diode selector elements at the ends of each word line and bit line. …

Perturbation Solution Of Air-Water Mixture For Jet Noise Reduction, Juan Felipe Uribe Cifuentes

Doctoral Dissertations and Master's Theses

This work investigates passive jet-noise mitigation using externally positioned air–water curtains that attenuate radiated sound without altering the underlying jet dynamics. Two classes of multiphase media are examined: a gaseous carrier phase containing dispersed liquid droplets, and a liquid carrier phase containing entrained air bubbles. For both systems, suspended and dispersed regimes are represented through a generalized perturbation formulation derived from the volume-averaged multiphase equations, incorporating finite volume fractions, interphase momentum coupling, and slip between phases. Analytical and numerical solutions demonstrate that acoustic attenuation is primarily governed by dispersed-phase diameter, volume fraction, and excitation frequency, with additional sensitivity to phase-interaction …

A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane

Doctoral Dissertations and Master's Theses

This research presents a quantitative performance comparison between light detection and ranging (LiDAR) and vision-based sensing for real-time maritime object detection on autonomous surface vessels. Using Embry-Riddle Aeronautical University’s (ERAU) Minion platform and 2024 Maritime RobotX Challenge data, this study evaluates the detection of six maritime object categories using two representative models. YOLOv8 provides a neural network vision-based method, and GB-CACHE provides a deterministic LiDAR-based method. Both models have been previously demonstrated to run in real time on uncrewed surface vessels (USVs). The evaluation methodology encompasses multi-sensor calibration, real-time performance analysis, and the introduction of a late-fusion strategy in the …

Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg

Doctoral Dissertations and Master's Theses

This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …

Autonomous Landing Of An Unmanned Aerial Vehicle On An Unmanned Surface Vessel Using Model Predictive Control With An Adaptive-Covariance Extended Kalman Filter, Jorge Estupinan

Doctoral Dissertations and Master's Theses

This thesis presents the development of vision-based estimation and model predictive control (MPC) strategies to enable an Unmanned Aerial Vehicle (UAV) to land autonomously on an Unmanned Surface Vessel (USV) subjected to wave-induced motion. An innovative Adaptive-Covariance Extended Kalman Filter (AEKF) implementation was developed for the estimation of the 6 degree-of-freedom USV states using GPS and vision-based measurements of AprilTag markers on the USV landing platform. The AEKF employs an uncontrolled 6 degree-of-freedom nonlinear model augmented with second-order harmonic wave-induced motion dynamics. The AEKF implements two correction techniques: an adaptive covariance adjustment and an artificial covariance inflation regulated by a …

Exploration Of Physics-Informed Grid Generation Technique For Wall-Modeled Les Using Eagle3d, Dominic Schneider

Doctoral Dissertations and Master's Theses

Wall-Modeled Large Eddy Simulation (WMLES) is an area of interest due to its ability to lower computational costs of LES. Even with the application of wall models, LES still proves to have practicality issues when it comes to use in industry, due to the expertise, time, and computational resources required. A novel technique for generating a lean, physics based WMLES grid is described.

The technique utilizes a RANS solution to extract turbulence information, user-specified values related to resolution of turbulent energy levels, acoustics waves, and shock waves, to generate a point cloud for producing a lean WMLES grid with in-house …

Unresolved Image Simulation For Space Situational Awareness Applications, Fox Coniglario

Doctoral Dissertations and Master's Theses

The knowledge of what lies in orbit around Earth is at best a guess. Decades of spaceflight, debris buildup, and vehicle collisions have contributed to a large number of objects that are simply not able to be catalogued. Ongoing efforts to catalog debris in orbit have reached limits by conventional measures and as such, research is active in the field of in-orbit space situational awareness. This thesis intends to help fill a hole in the development of such orbital platforms by assisting the development of image processing software pipelines though the simulation of unresolved space imagery. The simulation uses accurate …