Computer Engineering Commons^™

A Predictive Model For Multi- Week Respiratory Risk From Red Tide On Florida’S Gulf Coast., Elmer S. Ochaeta

Computer Science and Engineering Faculty Publications

Florida’s Gulf Coast red tide (Karenia brevis) can put toxins into the air, making people cough, irritating the throat, and worsening asthma or other breathing problems especially when winds blow from the ocean toward the beach. Right now, most public updates don’t really help with the question people actually ask when planning a weekend or vacation: “Will going to or close to the beach be risky in the next few weeks?”.

In this project, I build a weekly early warning system that estimates respiratory risk for specific beaches and predicts that risk 2 to 4 weeks ahead. The study covers …

3d Printed Portable Automatic Pill Dispenser​, Amber M. Ocasio

Publications and Research

Medication adherence is a major public health concern, particularly among patients with chronic illnesses. Reports from the National Institutes of Health indicate that adherence rates are significantly lower for chronic conditions, with patients taking only ~50% of medications prescribed. Unintentional non-adherence—such as forgetting doses—is more prevalent (62.9%, 47.1%, 46.9%) than intentional non-adherence, and the consequences include medication waste, disease progression, reduced functional abilities, lower quality of life, and increased reliance on medical resources. Because existing automatic pill dispensers cost over $100 on average, they remain inaccessible for many lower-income patients who could benefit from such technology. This project addresses this …

Bridging Modalities: Enhancing Multimodal Sentiment Analysis For Social Media Networks, Misbah Ul Hoque

LSU Doctoral Dissertations

Social media platforms like X (formerly Twitter) serve as rich sources of textual and visual information, making multimodal sentiment analysis essential for understanding complex human emotions. This dissertation aims to advance multimodal sentiment analysis by improving the semantic alignment and fusion of textual and visual features, thereby enabling more accurate and context-aware sentiment interpretation of social media content.

To address challenges in multimodal integration, this work proposes two complementary MSA approaches. The first approach introduces a similarity-based multi-layer attention neural network (SiMANN) that enhances modality integration through cosine-based similarity fusion and modality-specific attention to emphasize salient features in text and …

“Shaping Academic Teaching At The Crossroads Of Ethics And Artificial Intelligence”, Workshop At Warsaw University Of Technology, Warsaw, 25 September 2024, Julia Braniewska, Bartłomiej Skowron

Yearbook of Antitrust and Regulatory Studies

This document is a report on the workshop, “Shaping Academic Teaching at the Crossroads of Ethics and Artificial Intelligence”, which formed a component of the “Ethics and AI” conference hosted by Warsaw University of Technology.

Rapid Prototyping Of Low-Cost Sensor Systems Towards A Platform For Upper Limb Posture Estimation, Russell Rathbun

Electrical Engineering and Computer Science Undergraduate Honors Theses

Physical therapy requires patients to perform repeated actions to achieve meaningful results in rehabilitation. This thesis explores production methods and various sensor systems by utilizing rapid prototyping, inertial measurement units (IMUs), and capacitive sensor arrays (CSAs). CSAs can be made from a wide ar- ray of materials and techniques including 3d printing and laser ablation–to rapidly create CSAs that can be custom fit to enable proximity, force, and touch detection. IMU and CSA systems individually are able to track upper limb movements, ges- tures, and positions. This combination of sensors enables accurate upper limb pos- ture estimation of patients. This …

Curvilinear Image Segmentation Using Multiscale Variational U-Net, Rebekah Fortes

LSU New Orleans Theses and Dissertations

Segmentation of curvilinear structures such as water contours, cracks in cement, and vascular networks in biomedical imaging, poses unique challenges due to extreme class imbalance, irregular morphology, low contrast against complex backgrounds, and the need to preserve global connectivity while detecting fine-scale details. We propose a Multiscale Variational U-Net (MSVU-Net) architecture designed specifically to address these challenges. The model integrates multiscale convolutional filters to capture both global context and local detail, while embedding a variational model in the bottleneck layer to enhance structural representation. To mitigate class imbalance and improve fidelity, the network optimizes a hybrid loss function that combines …

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …

Llm-Powered Question Answering For Object States In Virtual Reality, Shiyi Ding

Master's Theses

Recent advances in large language models (LLMs) and multimodal large language models (MLLMs) enable natural language–based querying in virtual reality (VR). However, VR environments are highly localized, personalized, and dynamic, making it challenging for general-purpose models to answer environment-specific queries or reason about subtle object state changes. To address these challenges, this thesis develops two systems for 3D question answering in VR.

First, we present RAG-VR, the first retrieval-augmented 3D question-answering system designed for VR. RAG-VR augments an LLM with external knowledge retrieved from a localized knowledge database and includes a pipeline for extracting environmental and user-related information. To improve …

Mozgus, Damian Cerda, Madison Lopez

Computer Science and Software Engineering

The indie game market is flooded with genre experiments, yet few successfully combine fast-paced action with meaningful strategic decision-making. Our project aims to fill this gap by creating a game that fuses top-down action combat with resource-management tycoon mechanics. We found that in many games, the management phases lack mechanical stakes. Our goal was to intertwine these systems so that choices made in one phase meaningfully impact the other.

Parentcoach: Designing An Mhealth Parenting App To Enhance Parental Involvement In Adhd Support, Franceli L. Cibrian, Nancy Herrera, Jesus A. Beltran, Lucas M. Silva, Mikaela Pulse, Kayla Anderson, Cassie Zeiler, Luc Rieffel, Daniel I. Lee, Sabrina E. B. Schuck, Kimberley D. Lakes

Engineering Faculty Articles and Research

Introduction: Parents play a vital role in supporting self-regulation and managing behaviors in children with Attention-Deficit/Hyperactivity Disorder (ADHD). However, many face barriers to accessing consistent, evidence-based support. Mobile health (mHealth) technologies offer a promising way to deliver flexible, low-burden guidance for parents on best practices and strategies to support their children's self-regulation. However, designing them is non-trivial.

Objective: This paper introduces ParentCoach, a mobile application designed to support parents of children with ADHD through brief daily lessons, reflection prompts, and skill-building activities.

Methods: ParentCoach was developed in two phases: (1) secondary analysis of qualitative data from over 30 families …

Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes

Engineering Faculty Articles and Research

A variety of digital technologies have been used to support early childhood development (ECD) programs in low-income South African communities. Even though technology has provided opportunities to increase access to health interventions, the lack of trust and socio-economic constraints under which these tools would need to work pose complex challenges. We examine home visitors’ work processes, experiences, and preferences of a conversational agent to support their work of administering social-emotional well-being assessments to young children ages 0-5. Analysis of the results of focus groups with 51 home visitors indicates the need for designing conversational agents that support ECD in the …

Analysis Of A Cloud-Based Robot Motion Planning System, Yusif Mardanzade, Latafat Abbas Gardashova

Chemical Technology, Control and Management

As a result of the integration of cloud computing technologies into the field of robotics, the concept of "cloud robotics" has emerged. Unlike traditional robots, cloud-based robot systems remove computation, memory, and even some software from the local device and rely on remote resources obtained over the network. This approach ensures that robots are not limited only by their internal computing capabilities and allows them to take advantage of the wide range of opportunities offered by the cloud infrastructure. As a result, robots have access to large databases, highly parallel computing, and collective learning capabilities anytime and anywhere. In addition, …

Blockchain-Driven Pharma Supply Chains Towards Industry 6.0, Vijay Ramasamy R

Theses and Dissertations

The pharmaceutical supply chain is undergoing an unprecedented evolution in the wake of Industry 6.0, driven by the need for heightened transparency, security, and real-time intelligence. However, current systems suffer from legacy Enterprise Resource Planning (ERP) constraints, the risk of counterfeit products, temperature sensitivity, and scalability issues due to the surge in Internet of Things (IoT) data.

This research proposes a unified, blockchain-based framework that integrates legacy ERP systems, advanced AI driven forecasting, IoT-enabled traceability, and quantum-enhanced blockchain security to modernize pharmaceutical supply chains.

The study begins by addressing interoperability between ERP and blockchain using middleware and smart contracts, facilitating …

Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre

LSU Master's Theses

Historically, domain scientists faced steep learning curves due to low-level programming models and fragmented tooling. Between 2003 and 2008, Cray, now part of HPE, introduced the Chapel language as part of DARPA’s High Productivity Computing Systems (HPCS) program. Today, Chapel remains under active development and is used across research and production projects. In parallel, the STE||AR Group has advanced C++-based parallel programming through HPX, a standards-conforming runtime that provides lightweight tasking, futures, and distributed execution while abstracting much of the algorithmic “heavy lifting.” Yet for many domain scientists, C++ presents a steeper learning curve than Chapel. To close this complexity …

Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis

Conference papers

The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures …

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 …

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 …

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 …

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 …

Approximating The Maximum Weighted Independent Set Problem Empirically, Sue Sue

College of Engineering Summer Undergraduate Research Program

In this project we investigate approximation algorithms for the maximum weighted independent set (MWIS) problem in random graphs that approximate real-world graphs, such as social networks. The problem involves finding a large collection of nodes in a network (vertices in a graph) such that no two nodes are directly connected to one another. Applications of the MWIS problem are broad and include clique-finding algorithms as well as the use of large independent sets in distributed algorithms. We build on prior work by the mentor with a SURP 2024 and senior project, in which preliminary findings suggested that a standard greedy …

Building Pathways To Computer Science Careers For Latinx Students Through Multilingual Collaborative Block-Based Programming, Valerie Ponce, Priscilla Garcia

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.

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 …

Augmented Reality Application For Real-Time Coastal Data Visualization, Nithyasri Palanisamy

College of Engineering Summer Undergraduate Research Program

This project aims to develop an Augmented Reality (AR) application that overlays real-time coastal environmental data onto physical landscapes when viewed through AR devices such as smartphones and mixed reality headsets. By integrating data from machine learning models, computer vision-based event detection, coastal sensors, and geospatial mapping technologies, the application will provide users with an immersive and interactive experience, enhancing their understanding of coastal dynamics and environmental changes. The application will focus on observing coastal phenomena such as rip currents, tracking endangered coastal species and marine mammals, monitoring crowd levels on beaches, etc. Data sources will include NOAA's National Data …

Machine Unlearning: The Right To Be Forgotten, Colin Ngo

College of Engineering Summer Undergraduate Research Program

The objective of this SURP proposal is to investigate machine unlearning as a viable approach to support the right to be forgotten in artificial intelligence (AI) systems, many of which rely heavily on personal data. The capability to selectively remove user-specific information upon request—without necessitating full model retraining—is critical for safeguarding individual privacy and enhancing computational and energy efficiency. This project will undertake a systematic review of state-of-the-art unlearning techniques, evaluate their performance using standard benchmark datasets, and assess their feasibility in real-world applications. In addition, the project will provide participating students with practical experience in implementing and analyzing machine …

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.

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 …

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 …

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 …

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 …

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 …