Graphics and Human Computer Interfaces Commons^™

Spinlock Game Engine, Shane Misley

Posters - 2026

Modern game engines prioritize developer convenience at the cost of performance and transparency. Large frameworks like Unity and Unreal Engine abstract away implementation details, which simplifies development but introduces computational overhead—often 40-50% of CPU and memory usage goes to engine infrastructure rather than the actual game. For developers targeting low-end hardware, older systems, or performance-critical applications, this overhead becomes prohibitive. The Spinlock Engine addresses this problem by adopting a "close-to-the-metal" philosophy, stripping away unnecessary abstraction layers to deliver raw speed and predictable behavior. Built in C++ with SDL3 and Raylib, Spinlock prioritizes memory efficiency, CPU optimization, and developer transparency—allowing you …

A Virtual-Reality-Based Dental Simulator For Endodontics With Automated Formative Feedback, Yousef Salah Abo El Ela

Theses and Dissertations

Advancements in virtual reality (VR) and haptic technology are transforming the landscape of medical and dental education, offering new avenues for safe, immersive, and repeatable training experiences. Within dentistry, endodontics presents unique challenges for preclinical education due to anatomical complexity, limited access to extracted teeth, ethical concerns, and the shortcomings of conventional plastic models. Despite endodontics specific plastic teeth being available, they fall short of replicating the hardness of real extracted teeth, are relatively costly compared to generic plastic teeth, and are ultimately a disposable item which makes them inadequate as a sustainable long-term solution. Extracted teeth do a much …

Swimming In Uncertainty: Filling Data Gaps And Providing An Educational Platform For Beach Water Quality At Tybee Island, Georgia, Lukas Roberson

College of Graduate Studies: Theses & Dissertations

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Swimming in beaches water contaminated with high levels of bacteria can make you sick. Current monitoring at the public beaches on Tybee Island consists of weekly monitoring and enumeration of fecal indicator bacteria that takes 24 hours for results. If the number of bacteria exceed regulatory limits, a public health advisory is issued, and affected waters are retested until …

Auxiliary Prompt Tuning Of Vision‑Language Models For Few‑Shot Out‑Of‑Distribution Detection, Wenjun Miao, Guansong Pang, Zihan Wang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Recent advancements in CLIP-based out-of-distribution (OOD) detection have shown promising results via regularization on prompt tuning, leveraging background features extracted from a few in-distribution (ID) samples as proxies for OOD features.However, these methods suffer from an inherent limitation: a lack of diversity in the extracted OOD features from the few-shot ID data.To address this issue, we propose to leverage external datasets as auxiliary outlier data (i.e., pseudo OOD samples) to extract rich, diverse OOD features, with the features from not only background regions but also foreground object regions, thereby supporting more discriminative prompt tuning for OOD detection. We further introduce …

Focus: Evaluating Pre-Trained Vision-Language Models On Underspecification Reasoning, Kankan Zhou, Yibin Lai, Kyriakos Mouratidis, Jing Jiang

Research Collection School Of Computing and Information Systems

Humans possess a remarkable ability to interpret underspecified ambiguous statements by inferring their meanings from contexts such as visual inputs. This ability, however, may not be as developed in recent pre-trained visionlanguage models (VLMs). In this paper, we introduce a novel probing dataset called FOCUS to evaluate whether state-of-the-art VLMs have this ability. FOCUS consists of underspecified sentences paired with image contexts and carefully designed probing questions. Our experiments reveal that VLMs still fall short in handling underspecification even when visual inputs that can help resolve the ambiguities are available. To further support research in underspecification, FOCUS will be released …

Dupin: A Parallel Framework For Densest Subgraph Discovery In Fraud Detection On Massive Graphs, Jiaxin Jiang, Siyuan Yao, Yuchen Li, Qiange Wang, Bingsheng He, Min Chen

Research Collection School Of Computing and Information Systems

Detecting fraudulent activities in financial and e-commerce transaction networks is crucial. One effective method for this is Densest Subgraph Discovery (DSD). However, deploying DSD methods in production systems faces substantial scalability challenges due to the predominantly sequential nature of existing methods, which impedes their ability to handle large-scale transaction networks and results in significant detection delays. To address these challenges, we introduce Dupin, a novel parallel processing framework designed for efficient DSD processing in billion-scale graphs. Dupin is powered by a processing engine that exploits the unique properties of the peeling process, with theoretical guarantees on detection quality and efficiency. …

Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton

Shelby Hall Graduate Research Forum Posters

Stream of consciousness writing has a long history, including novelists James Joyce and Virginia Woolf. However, there has been little work done in automated and semi-automated analysis of such writing, which is the focus of this work. We plan to divide real streams of consciousness writing into distinct topical units and then capture different momentary meaningful topics from these units. By doing this, researchers and readers could gain a more nuanced understanding of the narrative structure and thematic elements. In addition, it would also support applications in fields like psychology and linguistics, where understanding thought processes and narrative structures is …

Ultrasonic Sensor-Based Sound Synthesis Using Raspberry Pi Pico W, Niraj Jaishwal

Williams Honors College, Honors Research Projects

At the intersection of Human Computer Interaction and digital art, this project transforms simple motion into musical expression. It explores an interactive real-time sound synthesis system using ultrasonic sensors to generate continuous audio. The objective is to design a system that maps physical distances into musical parameters such as pitch and amplitude, which will create a responsive audio environment. Two ultrasonic sensors are used in combination with the Raspberry Pi Pico W microcontroller running CircuitPython and Adafruit Audio Hat for real-time sound output. One sensor controls the pitch of the generated tone, while the other controls volume. This enables expressive …

Let’S Think Outside The Box: Exploring Leap-Of-Thought In Large Language Models With Multimodal Humor Generation, Shanshan Zhong, Zhongzhan Huang, Shanghua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, Pan Zhou

Research Collection School Of Computing and Information Systems

Chain-of-Thought (CoT) [2, 3] guides large language models (LLMs) to reason step-by-step, and can motivate their logical reasoning ability. While effective for logical tasks, CoT is not conducive to creative problem-solving which often requires out-of-box thoughts and is crucial for innovation advancements. In this paper, we explore the Leap-of-Thought (LoT) abilities within LLMs — a nonsequential, creative paradigm involving strong associations and knowledge leaps. To this end, we study LLMs on the popular Oogiri game which needs participants to have good creativity and strong associative thinking for responding unexpectedly and humorously to the given image, text, or both, and thus …

Exploring Neural Networks For Developing A Chess Learning Platform With Integrated Ai Agent, Lauren Escobedo

Posters - 2024

Chess is a highly strategic, complex, and long-form game that has been popular for many centuries. Due to the aforementioned complexities of this game, new players often have a hard time learning how to effectively and successfully play. With the recent developments in machine learning algorithms, new opportunities arise to create artificially intelligent tutors - not only for chess, but for all subjects. This project aims to develop a product which investigates the integration of an artificially intelligent “coach”, named Chesster, to train the player, which is trained on a neural network machine learning algorithm.

What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman

Dissertations, Theses, and Capstone Projects

The word “billion” is a mathematical abstraction related to “big,” but it is difficult to understand the vast difference in value between one million and one billion; even harder to understand the vast difference in purchasing power between one billion dollars, and the average U.S. yearly income. Perhaps most difficult to conceive of is what that purchasing power and huge mass of capital translates to in terms of power. This project blends design, text, facts, and figures into an interactive narrative website that helps the user better understand their position in relation to extreme wealth: https://whatdoesonebilliondollarslooklike.website/

The site incorporates …

Cgt-Gan: Clip-Guided Text Gan For Image Captioning, Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He

Research Collection School Of Computing and Information Systems

The large-scale visual-language pre-trained model, Contrastive Language-Image Pre-training (CLIP), has significantly improved image captioning for scenarios without human-annotated image-caption pairs. Recent advanced CLIP-based image captioning without human annotations follows a text-only training paradigm, i.e., reconstructing text from shared embedding space. Nevertheless, these approaches are limited by the training/inference gap or huge storage requirements for text embeddings. Given that it is trivial to obtain images in the real world, we propose CLIP-guided text GAN (CgT-GAN), which incorporates images into the training process to enable the model to "see" real visual modality. Particularly, we use adversarial training to teach CgT-GAN to mimic …

Position-Guided Text Prompt For Vision-Language Pre-Training, Alex Jinpeng Wang, Pan Zhou, Mike Zheng Shou, Yan Shuicheng

Research Collection School Of Computing and Information Systems

Vision-Language Pre-Training (VLP) has shown promising capabilities to align image and text pairs, facilitating a broad variety of cross-modal learning tasks. However, we observe that VLP models often lack the visual grounding/localization capability which is critical for many downstream tasks such as visual reasoning. In this work, we propose a novel Position-guided Text Prompt (PTP) paradigm to enhance the visual grounding ability of cross-modal models trained with VLP. Specifically, in the VLP phase, PTP divides the image into N x N blocks, and identifies the objects in each block through the widely used object detector in VLP. It then reformulates …

Visualized Algorithm Engineering On Two Graph Partitioning Problems, Zizhen Chen

Computer Science and Engineering Theses and Dissertations

Concepts of graph theory are frequently used by computer scientists as abstractions when modeling a problem. Partitioning a graph (or a network) into smaller parts is one of the fundamental algorithmic operations that plays a key role in classifying and clustering. Since the early 1970s, graph partitioning rapidly expanded for applications in wide areas. It applies in both engineering applications, as well as research. Current technology generates massive data (“Big Data”) from business interactions and social exchanges, so high-performance algorithms of partitioning graphs are a critical need.

This dissertation presents engineering models for two graph partitioning problems arising from completely …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James

Computer Science and Computer Engineering Undergraduate Honors Theses

The state-of-the-art for pruning neural networks is ambiguous due to poor experimental practices in the field. Newly developed approaches rarely compare to each other, and when they do, their comparisons are lackluster or contain errors. In the interest of stabilizing the field of pruning, this paper initiates a dive into reproducing prominent pruning algorithms across several architectures and datasets. As a first step towards this goal, this paper shows results for foresight weight pruning across 6 baseline pruning strategies, 5 modern pruning strategies, random pruning, and one legacy method (Optimal Brain Damage). All strategies are evaluated on 3 different architectures …

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …

A Study Of Software Development Methodologies, Kendra Risener

Computer Science and Computer Engineering Undergraduate Honors Theses

Software development methodologies are often overlooked by software engineers as aspects of development that are handled by project managers alone. However, if every member of the team better understood the development methodology being used, it increases the likelihood that the method is properly implemented and ultimately used to complete the project more efficiently. Thus, this paper seeks to explore six common methodologies: the Waterfall Model, the Spiral Model, Agile, Scrum, Kanban, and Extreme Programming. These are discussed in two main sections in the paper. In the first section, the frameworks are isolated and viewed by themselves. The histories, unique features, …

Taming The Data In The Internet Of Vehicles, Shahab Tayeb

Mineta Transportation Institute

As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …

Markdown To Question & Test Interoperability, Su Kim

Master's Projects

As the classroom setting shifted to a virtual one as a result of Covid-19, numerous software are readily available to accommodate for the change, including Canvas, the online course management system. Canvas has a core feature that allows teachers to generate and administer quizzes for students through their interface, but it does not fully utilize the potential with online exams. The first step to exploring this potential is this project, known as Markdown to Question & Test Interoperability (M2QTI). Based on the QTI specifications, this tool lets users to plan and write quizzes in Markdown format. Combined with Canvas’s ability …

Wav-Bert: Cooperative Acoustic And Linguistic Representation Learning For Low-Resource Speech Recognition, Guolin Zheng, Yubei Xiao, Ke Gong, Pan Zhou, Xiaodan Liang, Liang Lin

Research Collection School Of Computing and Information Systems

Unifying acoustic and linguistic representation learning has become increasingly crucial to transfer the knowledge learned on the abundance of high-resource language data for low-resource speech recognition. Existing approaches simply cascade pre-trained acoustic and language models to learn the transfer from speech to text. However, how to solve the representation discrepancy of speech and text is unexplored, which hinders the utilization of acoustic and linguistic information. Moreover, previous works simply replace the embedding layer of the pre-trained language model with the acoustic features, which may cause the catastrophic forgetting problem. In this work, we introduce Wav-BERT, a cooperative acoustic and linguistic …

Towards A Large-Scale Intelligent Mobile-Argumentation And Discovering Arguments, Controversial Topics And Topic-Oriented Focal Sets In Cyber-Argumentation, Najla Althuniyan

Graduate Theses and Dissertations

User-generated content (UGC) platforms host different forms of information, such as audio, video, pictures, and text. They have many online applications, such as social media, blogs, photo and video sharing, customer reviews, debate, and deliberation platforms. Usually, the content of these platforms is provided and consumed by users. Most of these platforms, mainly social media and blogs, are often used for online discussion. These platforms offer tools for users to share and express opinions. Commonly, people from different backgrounds and origins discuss opinions about various issues over the Internet. Furthermore, discussions among users contain substantial information from which knowledge about …

City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial Intelligence systems have come a long way over the years. One particular application of A.I. is its incorporation in video games. A key goal of creating an A.I. system in a video game is to convey a level of intellect to the player. During playtests for Halo: Combat Evolved, the developers at Bungie noticed that players deemed tougher enemies as more intelligent than weaker ones, despite the fact that there were no differences in behavior in the enemies. The tougher enemies provided a greater illusion of intelligence to the players. Inspired by this, I set out to create a …

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

Argumentation Stance Polarity And Intensity Prediction And Its Application For Argumentation Polarization Modeling And Diverse Social Connection Recommendation, Joseph Winstead Sirrianni

Graduate Theses and Dissertations

Cyber argumentation platforms implement theoretical argumentation structures that promote higher quality argumentation and allow for informative analysis of the discussions. Dr. Liu’s research group has designed and implemented a unique platform called the Intelligent Cyber Argumentation System (ICAS). ICAS structures its discussions into a weighted cyber argumentation graph, which describes the relationships between the different users, their posts in a discussion, the discussion topic, and the various subtopics in a discussion. This platform is unique as it encodes online discussions into weighted cyber argumentation graphs based on the user’s stances toward one another’s arguments and ideas. The resulting weighted cyber …

Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari

Department of Computer Science Faculty Scholarship and Creative Works

With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …

Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess

MS in Computer Science Project Reports

OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms. A user can see how data is processed at each step in their algorithm, and the results of any changes to the algorithm will be displayed to the user immediately. This can allow the user to easily experiment with various computer vision methods and their parameters. EyeCalc 1.0 uses the Microsoft Foundation Class Library, an old GUI framework by Microsoft, and contains various …

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

Helion’S Snapshot Module, Nii-Kwartei Quartey

Cybersecurity Undergraduate Research Showcase

During my undergraduate research, I spent my time working with a home automation program known as Helion, specifically, its Snapshot module. I was tasked with learning new material and completing part of the webpage that were unfinished. I also had to get a little creative when working on a design that users could find appealing. There were times I found working on Helion difficult but overall, working with Helion’s Snapshot Module is something that will help me improve with my undergraduate studies.

Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng

Department of Computer Science Faculty Scholarship and Creative Works

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to …