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Leveraging Smartphones For Balance Assessment, Kelly Graham
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 …
Executive Committee - Minutes, 09/30/2025, Academic Senate
Executive Committee - Minutes, 09/30/2025, Academic Senate
Academic Senate Minutes
No abstract provided.
Executive Committee - Agenda, 09/30/2025, Academic Senate
Executive Committee - Agenda, 09/30/2025, Academic Senate
Academic Senate Agendas
No abstract provided.
Executive Committee - Minutes, 09/23/2025, Academic Senate
Executive Committee - Minutes, 09/23/2025, Academic Senate
Academic Senate Minutes
No abstract provided.
Executive Committee - Agenda, 09/23/2025, Academic Senate
Executive Committee - Agenda, 09/23/2025, Academic Senate
Academic Senate Agendas
No abstract provided.
Academic Senate Retreat - Agenda, 09/12/2025, Academic Senate
Academic Senate Retreat - Agenda, 09/12/2025, Academic Senate
Academic Senate Agendas
No abstract provided.
Impact Of Composite Materials Research On Underrepresented Communities, Neil Mahesh Bedagkar, Ramanan Sritharan, Wyatt Barnes
Impact Of Composite Materials Research On Underrepresented Communities, Neil Mahesh Bedagkar, Ramanan Sritharan, Wyatt Barnes
Mechanical Engineering
This research assesses how advancements in composites material research affect communities from lower socioeconomic backgrounds, using a dual track strategy to quantitatively and qualitatively examine their impact. A keyword-based classification algorithm was applied to a sample of research papers from ScienceDirect spanning the last 24 years to quantify which engineering industries benefit most from this research. The findings indicate that the construction industry benefits the most, followed by the automotive, defense, renewable energy, and biomedical sectors. A broader qualitative analysis of the social implications of these industries was also conducted to provide context. Each sector were found to have either …
Executive Committee - Minutes, 09/04/2025, Academic Senate
Executive Committee - Minutes, 09/04/2025, Academic Senate
Academic Senate Minutes
No abstract provided.
Executive Committee - Agenda, 09/04/2025, Academic Senate
Executive Committee - Agenda, 09/04/2025, Academic Senate
Academic Senate Agendas
No abstract provided.
Performance Of Reinforced Concrete Wall With Discrete Frp Boundary Element Retrofit, Katelyn Lowry, Roger Biddle, Peter Laursen, Anahid A. Behrouzi, Cole Mcdaniel
Performance Of Reinforced Concrete Wall With Discrete Frp Boundary Element Retrofit, Katelyn Lowry, Roger Biddle, Peter Laursen, Anahid A. Behrouzi, Cole Mcdaniel
Architectural Engineering
This paper presents experimental results for a lightly reinforced concrete (LRC) shear wall retrofitted with discrete fiber-reinforced polymer (FRP) strips at the boundary zones. The performance of this wall was evaluated through cyclic lateral load testing and compared with a wall retrofitted with continuous FRP at the boundary zones (Duong et al., 2024). Test results showed that the wall retrofitted with discrete strips exhibited a flexural tensile failure characterized by wide flexural cracks confined between FRP strips and rebar fracture at high drifts, while maintaining displacement compatibility and axial load capacity beyond strength degradation. Compared to the continuous FRP retrofit, …
Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain
Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain
Master's Theses
Accurately pricing American options with market data presents a significant challenge, as foundational models like the Black-Scholes-Merton (BSM) model rely on assumptions that deviate from real-world financial data -- such as log-normal returns, constant volatility, and no dividends -- and fail to account for the key early exercise feature of American options. While parametric models can adjust for these features, the complexity of the resulting models renders them prohibitively difficult to apply in practice for nonspecialists. In response, modern machine learning (ML) techniques provide a set of flexible and powerful alternatives, and recent research has explored the application of ML …