Computer Engineering Commons^™

Codelympics: An Educational Game, Shreyas Raghunath, Riley Guioguio

Computer Science and Engineering Senior Theses

This thesis addresses the growth of Computer Science and the increasing demand for resources that educate people about programming. The central problem is that existing resources either fall short in engaging the user, or are ineffective at communicating the basics of programming. Through a year of development and testing, we developed an application to serve as a bridge between games and educational content, making programming skills fun and accessible for younger students with no prior experience.

This thesis details the development of Codelympics, an educational game designed to teach the basics of computer programming, including control flow, functions, variables, and …

Bronconest, Jake Esperson, Andrew Collins, Anish Katragadda

Computer Science and Engineering Senior Theses

Selecting suitable housing is a critical yet often overwhelming aspect of the college experience, particularly for incoming students who lack access to transparent and meaningful information about residential life. Existing platforms, such as official university housing portals or external real estate websites, fail to capture the nuanced, day-to-day experiences that influence student well-being, including cleanliness, social atmosphere, and sense of community. This issue is further compounded by the growing prevalence of remote decision-making and scattered, unverified sources of housing feedback.

To address this challenge, we developed BroncoNest, a scalable, cross-platform mobile application designed to centralize and personalize the student housing …

Dna Storage Of Images: From Pixels To Molecules, Cihan Ruan

Engineering Ph.D. Theses

DNA storage is rapidly emerging as a transformative solution for long-term, ultra-dense, and energy-efficient archival systems. This dissertation builds upon a deep understanding of image compression principles to design encoding frameworks that are uniquely attuned to the biochemical constraints of DNA storage. By fusing insights from traditional coding with molecular-level design, we develop a series of technically advanced solutions tailored for this emerging medium.

Our first contribution introduces Dynamic DNA-Fountain, a constrained codec that maps H.266 /VVC-compressed bitstreams to quaternary DNA sequences, optimizing for both information density and biochemical synthesis constraints. Building upon this foundation, we shift focus toward robustness—leveraging …

Understanding And Enhancing Linux Kernel-Based Packet Switching On Wifi Access Points, Shiqi Zhang

Computer Science and Engineering Master's Theses

As the number of WiFi devices and their traffic demands continue to rise, the need for a scalable and highperformance wireless infrastructure becomes increasingly essential. Central to this infrastructure are WiFi Access Points (APs), which facilitate packet switching between Ethernet and WiFi interfaces. Despite APs’ reliance on the Linux kernel’s data plane for packet switching, the detailed operations and complexities of switching packets between Ethernet and WiFi interfaces have not been investigated in existing works. This paper makes the following contributions towards filling this research gap. Through macro and micro-analysis of empirical experiments, our study reveals insights in two distinct …

A Step Towards Automated Ethical Analysis In Journalism: Measuring Llms’ Performance In Extracting Sourcing Information, Jingsen Wang

Computer Science and Engineering Master's Theses

This thesis explores the potential of Large Language Models (LLMs) in automating the extraction of sourcing information from news articles, a crucial step towards enhancing transparency and ethical analysis in journalism. We evaluate the performance of two state-of-the-art LLMs, GPT-4 and Claude 3, in identifying and categorizing various source types across four diverse news articles. The thesis employs a zero-shot learning approach with two different prompt designs, assessing the models’ ability to adapt to varying source structures and prompt instructions.

Our findings reveal that while LLMs show promise in extracting sourcing information, their performance varies significantly across different article types …

Corridor Counting, Anthony Bryson, Vincent Zhou, Amy Ha

Computer Science and Engineering Senior Theses

Information on traffic patterns is essential for identifying and addressing sources of traffic congestion and informing future road layouts to create safer and more efficient roads. To this end, we develop a Corridor Counting, or Multi- Camera Vehicle Counting, algorithm that quantifies the number of vehicles traveling along a specific stretch of road. Our work builds upon the related problem of Multi-Camera Vehicle Tracking and draws inspiration from methods used for Single-Camera Counting. We propose a six-step solution comprising Vehicle Detection, Feature Extraction, Single- Camera Vehicle Tracking, Re-Identification, Movement Matching, and Multi-Camera Vehicle Counting. Finally, we adapt an evaluation metric …

Two-Step Hierarchical Multi-Camera People Tracking, Eerina Haque, Eric Huang, Sihang Li

Computer Science and Engineering Senior Theses

The possibility of an efficient and accurate solution for multi-camera people tracking (MCPT) is enabled by the improvement of computing power and the advancement of machine learning technologies. The problem of multi-camera people tracking serves as a cornerstone of real-world applications such as video surveillance or warehouse automation. The current solutions for MCPT suffer from problems such as appearance inconsistency, object occlusion, etc. Our work targets tackling the challenges faced by modern MCPT algorithms to bring a more robust, efficient, and accurate solution.

The Impact Of Emojis On User Engagement With Trolling Content In Online Platforms, Diya Saraf

Computer Science and Engineering Senior Theses

This thesis examines the impact of emojis on user engagement within online discussions, particularly focusing on the trolling behavior on social media platforms such as Reddit. The central problem addressed is understanding how different types of emojis—in emotional, informational, and popularity-based categories—affect user interactions and engagement in online communications. Through a robust methodological approach, combining quantitative data analysis and Random Forest regression modeling, this research meticulously analyzes emoji usage patterns and their correlations with engagement metrics like upvotes and comments.

The results highlight that emotional and popular emojis significantly enhance engagement by facilitating emotional expression and connection among users. In …

Ragu Conversational Menu Assistant: An Llm Retrieval Augmented Generation Approach, Sam Abdel, Seth Mak, Aaron Pham, Christopher Michael

Computer Science and Engineering Senior Theses

This project introduces a novel Conversational Menu Assistant leveraging Retrieval Augmented Generation (RAG) techniques within a modified Large Language Model (LLM) framework to enhance dining experiences by providing personalized menu assistance. The main innovation lies in the system’s ability to integrate up-to-date menu information from various sources, including web scraping, into its responses, thereby circumventing the limitations commonly associated with LLMs, such as the need for frequent retraining and the challenge of handling dynamic information. Our solution addresses the pressing issue of reducing the workload on restaurant servers and streamlining the ordering process by offering precise menu details, personalized recommendations …

Naturalistic Driving Action Recognition, Andy Xiao, Antonio Fontan

Computer Science and Engineering Senior Theses

Driving is one of the most tasks people do day to day to get to places more efficiently, but with many people using the road every day, distracted driving can be a big problem. Grothlaw firm states that in the recent years, at least 9 out of 3287 deaths related to auto accidents per day are caused by distracted driving [1]. Distracted driving refers to things that drivers do that are not related to driving [2] This can include texting, eating, talking to passengers, tuning the radios, etc... that can get the driver’s attention away from the road [2]. Many …

Ar Storybook, Priya Jain, Jessica Torres, Melody Trinh

Computer Science and Engineering Senior Theses

Parents often use technology as a digital pacifier or source of entertainment for their children. While excessive screen time for children can be harmful, a digital future seems inevitable. As technology becomes more prominent in everyday life, children should utilize their early years to engage with technology in a way that develops their growing minds. AR Storybook is an interactive storybook that strives to provide children with an active learning experience. The story teaches children computational thinking skills through augmented reality activities embedded into the plot. The activities ask the user to help a character complete a task by using …

Virtual Museum Tours Of The De Saisset Museum, Justin Enciso-Anaya, Karthik Tamil, Quoc Truong

Computer Science and Engineering Senior Theses

Our project transforms the California Stories exhibit at the de Saisset Museum into an immersive virtual tour, integrating Matterport technology and Human-Computer-Interaction (HCI) principles. Matterport’s high resolution 360 degree camera allows us to capture a physical space in high definition into a 3D virtual space while Matterport’s software helps to facilitate the creation and editing for our physical space in a virtual environment. HCI principles focus on how systems should work when direct interaction with users is a key component. We apply the principles of HCI to create a virtual museum tour that offers visitors a culturally enriching, interactive experience, …

Monterecycle: An Application For Streamlining Tracking Of Recyclables In Uruguay, Aayooshi Dharmadhakari, Danny Walsh, Eason Ke, Kamya Krishnan

Computer Science and Engineering Senior Theses

Recycling is a crucial process that has a positive impact on nature, cleans the environment, and saves time and money. Classifying recyclables by material and recycling these items accordingly helps make our world more environmentally-friendly and a better place to live.

In the recycling system in Montevideo, Uruguay, third-party contractors hired by San Vicente transport clients’ recyclables to a central recycling center or to a person that does recycling. In the past, San Vicente has transported recyclables though horse and buggy transportation. However, there has been a push from the city to replace the horses with motorcycles to reduce animal …

Iotsolate: Network Microsegmentation For Managing And Securing Iot Devices, Chloé Morali, Anagha Nair

Computer Science and Engineering Senior Theses

Developing solutions to secure IoT devices is a pressing issue facing us today. Although IoT devices improve everyday life in various ways, they are susceptible to security threats, impacting users in all environments. As the number of IoT devices increases, the attack surface expands exponentially. However, securing these devices proves to be a challenge because they are made with limited processing capabilities, which means they lack necessary security features. They also come in a wide range of variations in terms of operating systems, physical design, and network connectivity which complicates the establishment of standardized security options. Additionally, they tend to …

Performance Evaluation Of Databases For Packet Capture And Analysis, James Vong, Daniel Kareti

Computer Science and Engineering Senior Theses

Today, the presence of smart devices is constantly on the rise, especially for Internet of Things (IoT) devices. However, their utility-based design means that these devices are limited in computing power. Due to this limited computing power, the devices are more prone to cyber-security threats, and it is vital to construct a method to aid in network traffic analysis, bolstering defense mechanisms to thwart any malicious attacks. To analyze their network data efficiently and externally, we constructed a test-bed infrastructure to measure and evaluate the performance of databases. In this thesis, we have chosen to compare two databases which are …

Scdi: Privacy-Preserving Device Identification, Ethan Shenassa, Michael Castillo

Computer Science and Engineering Senior Theses

As internet security concerns grow due to the increasing complexity of cyberattacks, heterogeneity of network-connected devices, and popularity of insecure Internet of Things (IoT) devices, network administrators require more intelligent ways of managing and securing their networks. One crucial step in this regard is the ability to identify and classify devices from the edge of networks. However, many recent advances in network security come at the cost of user privacy, as device classification algorithms often require packet payload data, Internet Protocol (IP) addresses, or other sensitive information. This paper proposes the Shenassa-Castillo Device Identifier (SCDI): a software network device identifier …

Deep Learning Based Single Image Super-Resolution, Samuel Smith

Computer Science and Engineering Senior Theses

Single image super-resolution (SR) involves taking a given low-resolution (LR) image and generating a corresponding high-resolution (HR) image. This is a core task in the computer vision field due to its multitude of applications ranging from helping current-day issues of storage and transfer of data to restoration of low-resolution images. The current strategies, however, struggle to reach the quality needed for their widespread use and are often too resource-intensive for the average consumer. While other lightweight SR techniques exist with different techniques, like Cascading Residual Networks [3], their success comes at the cost of expensive technology inaccessible to most situations. …

Distant Horizon: Exploring Human-Ai Interaction Through Video Games, Gabe Labadie, Dalia Suszko, Max White

Computer Science and Engineering Senior Theses

As the field of Artificial Intelligence (AI) continues to grow and become more and more integrated into our everyday lives, it has begun to raise ethical concerns surrounding authority, autonomy, and responsibility. Researchers and consumers alike have begun to wonder how much trust we are willing to place in a non-human decision maker, especially if an Artificial General Intelligence (AGI) capable of surpassing human cognitive capabilities is ever developed. If we are willing to let an AI write essays for us, are we willing to let it manage a business? A government agency? What about a nuclear reactor?

Our project …

Daily Digest: A News Aggregation Site, Justin Wang, Jack Maguin, George Orloff, Justin Groves

Computer Science and Engineering Senior Theses

A staggering amount of news articles are uploaded every day – approximately 5,000 in the United States alone [1]. That volume of information causes difficulty for many people who try to stay up-to-date with current events. The number of articles and the multitude of sources that they come from can feel overwhelming. In our project, we attempt to tackle this issue. We use web scraping to collect a dataset of news articles and combine it with a Large Language Model (LLM) capable of processing those articles to generate news summaries for the user. The user interacts with the program through …

General Purpose Tuning Data Visualization, Chris Augustine, Francisco Salinas, Aakash Shetty

Computer Science and Engineering Senior Theses

This project centers on the visualization of High-Performance Computing (HPC) data obtained from the GPTune website. GPTune serves as a valuable resource for HPC experiments, providing a wealth of performance data from tuning studies and optimization tasks. Our objective is to develop an advanced data visualization framework tailored to GPTune’s datasets. Utilizing state-of-the-art visualization techniques, we aim to create an interactive platform that allows users to explore, analyze, and derive insights from the diverse tuning experiments conducted on HPC systems. The visualization tool will facilitate the identification of optimal configurations, performance trends, and patterns within GPTune data, empowering researchers and …

Applied Auto-Tuning On Lora Hyperparameters, Darren Inouye, Lucas Lindo, Robin Lee, Edmund Allen

Computer Science and Engineering Senior Theses

This senior design project explores the application of Bayesian optimization-based auto-tuning techniques on the low-rank adaptation (LoRA) fine-tuning of large language models (LLMs), demonstrating how fine-tuning methods can reduce training times and costs, albeit with a slight trade-off in accuracy. However, little is known about the optimal hyperparameters on LoRA and its variants for those methods. This project addresses this lack of knowledge by analyzing data gathered from auto-tuning LoRA hyperparameters to determine the most optimal parameter configurations for a model’s accuracy and training efficiency.

The team has implemented a pipeline utilizing many different technologies. The main technology driving the …

9-Axis Motion Tracking To Aid Therapeutic Recovery Via Visualization, Analysis And Progress Monitoring, Megan Wiser, Liam A'Hearn, Christopher Tamayo, Liam Kelly

Computer Science and Engineering Senior Theses

This paper presents an innovative approach to enhance at-home physical therapy exercises through the development of a wearable motion tracking system. The proposed system utilizes motion tracking bands worn by patients during exercises, specifically focusing on a squat jump for the initial phase of the project. The bands, placed around the ankle and knee, monitor the alignment of the user's motion and transmit data via Bluetooth Low Energy (BLE) to a dedicated webpage. This webpage integrates real-time data analysis, offering immediate feedback to users, enabling them to monitor their form and track progress over time. The collected data is stored …

Hiv3: An Efficient Beehive Monitoring System, Jack Ursillo, Aneal Kuverji, Connor Merhab, Anshuman Sahu

Computer Science and Engineering Senior Theses

Beehive monitoring plays a major role in ensuring the health of beehives by checking for overpopulation or underpopulation within a hive. Beehive monitoring provides beekeepers with the opportunity to take action and save the hive before the problem becomes irreversible. Most solutions are too expensive for everyday beekeepers and lack elements of sustainability, making it impractical for small scale beekeepers. In this thesis, we propose a solution to this problem, demonstrating its sustainability and user-friendliness, which enables us to effectively reach a larger consumer market. We support these claims through the use of sustainable systems such as using a solar …

Enhancing Vqgan-Based Model With Connext For Blind Super-Resolution, Lebin Zhou

Computer Science and Engineering Master's Theses

This thesis presents a novel super-resolution model based on Vector Quantized Generative Adversarial Network (VQGAN) to enhance image resolution. Inspired by recent advancements in the field of image reconstruction, we apply VQGAN to the super-resolution task, leveraging its powerful generative capabilities to produce higher quality high-resolution images.

Building on the VQGAN framework, we propose an improved architecture that incorporates an additional ConvNeXt feature extractor based on Convolutional Neural Networks (CNN) to effectively capture and refine features from low-resolution images. To further enhance model performance, we implemented various strategies to optimize the utilization of the codebook, including capacity optimization, improved initialization, …

Ultra Low-Power, High-Performance Presence Detection System, Dante Bajarias, Cristian Medal, Jashan Kaeley

Computer Science and Engineering Senior Theses

The proliferation of Internet of Things (IoT) devices emphasizes a greater connection between humans and smart technology. From computer peripherals, personal electronics, and domestic appliances to building access management, healthcare, and security systems, modern applications are generating as much data or more than they are receiving from other sources. Human presence is a type of data that is becoming a compelling requirement for a plethora of today’s applications that must ensure seamless interactions of users with the systems and their associated services. The ultra low-power, high performance presence detection system is an accelerometer-based system capable of person detection, people counting, …

Edge-Connected Microcontroller Security, Divya Syal, Gavin Ryder, Neena Ekanathan

Computer Science and Engineering Senior Theses

With a wide range of applications and the rise of cyber attacks, securing microcontrollers has become imperative; however, ensuring microcontroller performance is also crucial given how interconnected today’s systems are. This project examines the security and performance of next-generation microcontroller units leveraging new security solutions for IoT edge applications. By benchmarking these MCUs against key performance metrics, their viability will be assessed to facilitate the widespread adoption of this latest firmware.

Our research focuses on profiling the power consumption and performance of the new STM32H573 and the integrated Secure Manager, a new technology from ST Microelectronics that allows for privileged …

Autonomous Microgrid System, Xavier Kuehn, Brian Xiong

Computer Science and Engineering Senior Theses

Microgrids have made a revolutionary change in the realm of energy distribution due to the features that they offer, including localized, resilient, and sustainable energy solutions. Operating renewable resources in a microgrid while maintaining generation-load balance and acceptable voltage-frequency limits has been an open research problem. This thesis presents smart python agents for microgrid systems to automate the operations and control of microgrid renewable resources in an effort to provide resilient solutions to the intermittence issues that could potentially arise within the microgrid energy system. The smart agents operate the microgrids by not only integrating the use of renewable energy …

Enhanced Adaptive Image-Codebook Learning For Image Reconstruction, Yutong Ge

Computer Science and Engineering Master's Theses

In the field of image reconstruction and super-resolution, using codebooks has shown promising results despite various image degradations. Previous methods either use distinct codebooks for each image category or multiple codebooks per category, with the latter achieving better performance by capturing more nuanced image features. Our research proposes a novel method that employs enhanced sets of codebooks and weight maps tailored to each image category. These weight maps dynamically combine different codebook bases to adapt to various reconstruction tasks, resulting in improved image recognition and robustness. This approach significantly enhances the expressiveness and quality of reconstructed images, making it versatile …

E-Scooter Black Box, Soham Phadke, Suvass Ravala, Joshua Jerome, Raghav Batra, Mubashir Hussain

Computer Science and Engineering Senior Theses

The burgeoning market for shared e-scooters is significantly hampered by the short lifespan of commercial e-scooters, which currently average just three months due to rough handling by users. To address this challenge, our project aims to extend the lifespan of shared e-scooters through an innovative onboard solution that discourages detrimental riding behaviors.

Our solution integrates a portable sensor hub from STMicroelectronics to capture ride data, which is then processed and sent via a user’s iOS app to a Google Firebase backend. A machine learning model running in the cloud analyzes the data to extract valuable metrics. These metrics are displayed …

Residual Transformer Unet For Medical Image Segmentation, Ruopu He

Computer Science and Engineering Master's Theses

With the continuous development of deep learning theory in the field of medical images, information technology-assisted treatment methods represented by medical image segmentation technology can help doctors to quickly determine the shape and location of the lesions and improve the diagnosis efficiency of brain tumors. Based on deep learning technology, this thesis carries out related research work on MRI image segmentation. The main contents are as follows:

To begin with, acquire and prepare the brain tumor (MRI) image segmentation dataset from the official MICCAI Society website. This involves normalizing the images, cropping, and slicing, as well as scaling the data …