Artificial Intelligence and Robotics Commons^™

Usage Of Natural Language Processing And Deep-Learning Techniques On Thematic Apperception Tests To Predict Big Five Personality Traits, Blayten Jones

Electrical Engineering and Computer Science Undergraduate Honors Theses

The usage of personality as a method of behavioral prediction and outcomes of success has grown considerably over the last few decades. This project explores predicting user personality profiles via the Big Five personality index through the integration of advanced natural language processing techniques as well as neural networks. Using a dataset provided by Dr. James W. Pennebaker, participants analyze an image—formally referred to as a thematic apperception test—and write a thorough paragraph describing the details. This free-form text, along with their personality test results, is captured in a structured dataset. Many deep-learning and machine learning models have been used …

Deepfakes On Trial: Developing A High-Accuracy, Court-Admissible Ai Pipeline For Deepfake Detection In Corporate Fraud Litigation, Aiden J. Green

Honors College Theses

As deepfake technology advances, cybercriminals are increasingly using AI-generated videos and audios to impersonate executives and carry out sophisticated CEO fraud schemes. These synthetic forgeries target human trust and corporate communication systems, creating an urgent need for forensic tools capable of authenticating digital evidence with legal accuracy. This thesis presents a forensic-grade AI deepfake detection pipeline designed for this purpose, emphasizing courtroom admissibility, reproducibility, and evidentiary integrity. Built entirely with free, opensource tools, the framework combines metadata analysis, AI-powered spectrogram analysis, neural artifact detection, and facial manipulation recognition into a transparent workflow that accurately identifies synthetic media. It was trained …

From The Bleachers To The Browser: Redefining Fan Experience With Ar And Ai In Smaller Teams, Jennifer Lee Wunder

Theses

This project documents the creation and deployment of HootyHoo, an interactive augmented reality (AR) mascot experience designed for the O’Fallon Hoots, a small-scale collegiate summer baseball team. Built using accessible, open-source tools such as WebXR, Mixamo, Meshy, Botpress, Claude and ChatGPT, this prototype merges AI-driven conversation with animated 3D avatar interaction—redefining how fans engage with sports organizations digitally. Unlike enterprise-level applications used by professional franchises, HootyHoo is entirely browser-based, eliminating the need for app downloads and ensuring maximum accessibility for families and new fans with smartphones. The experience centers on Hooty, the team mascot, who answers questions about baseball and …

Reinforcement Learning, Modeling Markets, And Professional Basketball Free Agency, Jacob Cohn

Computational and Data Sciences (PhD) Dissertations

This dissertation presents a reinforcement learning-based approach to modeling and optimizing decision-making in professional basketball free agency and related economic environments. A Markov Decision Process (MDP) framework is introduced to capture the strategic interactions of NBA teams bidding for free agents under budgetary and roster constraints. To address computational scalability challenges, a reinforcement learning (RL) environment is developed, leveraging Proximal Policy Optimization (PPO) to approximate optimal policies for team decision-making.

Empirical results demonstrate that the RL agent successfully learns strategic bidding behavior that aligns with dynamic programming benchmarks in simplified settings while scaling effectively to larger, intractable environments. The study …

The Efficacy Of Incorporating Artificial Intelligence (Ai) Chatbots In Brief Gratitude And Self-Affirmation Interventions: Evidence From Two Exploratory Experiments, Jing Wen Hung, Andree Hartanto, Adalia Y.H. Goh, Zoey K.Y. Eun, K. T. A. Sandeeshwara Kasturiratna, Zhi Xuan Lee, Nadyanna M. Majeed

Research Collection School of Social Sciences

Numerous studies have demonstrated that positive psychology interventions, including brief interventions, can significantly improve well-being outcomes. These findings are particularly important given that many of these interventions are brief and self-administered, making them both accessible and scalable for large populations. However, the efficacy of positive psychology interventions is often constrained by small effect sizes. In light of advancements in generative Artificial Intelligence (AI), this study explored whether integrating AI chatbots into positive psychology interventions could enhance their efficacy compared to traditional self-administered approaches. Study 1 examined the efficacy of a gratitude intervention delivered through Snapchat's My AI, while Study 2 …

Greening Intelligence: Why Ai Infrastructure And Governance Must Evolve Together, Heng Wang, Poh Seng Lee

Research Collection Yong Pung How School Of Law

AI infrastructure is evolving faster than the regulation and governance needed to ensure it serves public and planetary interests.

The Role Of Ai In Enhancing Teamwork, Resilience And Decision-Making: Review Of Recent Developments, Satyadhar Joshi

Harrisburg University Other Works

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. …

Strengthening The Bonds Between Us: An Empirical Investigation Of Morale In Human-Ai Teams And The Socially Supportive Ai Teammates Who Empower It, Rohit Mallick

All Dissertations

This dissertation investigates how artificial intelligence (AI) can be designed to improve the collective emotion within a team. A team's collective emotion, or morale, describes how motivated, optimistic, and enthusiastic the group is in accomplishing its goals. We conducted four studies that compared different social support strategies that AI teammates can provide to the team. Study 1A found that AI teammates who communicate with emotions can better motivate human team members and promote awareness of team dynamics and environmental changes. Study 1B found that human teammates become more motivated and happier when their AI teammates express joy and are close …

Perceptions Of Employability With Ai Skills, Brandy Whitford, Patrick J. Cooper

Student Publications and Presentations

Artificial intelligence (AI) is making AI proficiency a key factor in hiring and career advancement. By late 2023, 75% of knowledge workers integrated AI into their workflows, with 92% reporting increased productivity and creativity (Kimbrough, 2024). Employers are adapting—66% prefer candidates with AI expertise, and 77% consider AI skills essential for career growth (Microsoft & LinkedIn, 2024). However, hiring biases related to AI-skilled applicants remain underexplored, particularly concerning gender disparities in employability perceptions. This study examines how AI-related skills influence perceived employability and whether these perceptions vary based on applicant gender. Specifically, it explores whether AI-skilled female applicants receive higher …

Gender Bias Within Ai Imaging, Drew Quattrocchi

Student Publications and Presentations

This study investigates AI-created gender bias in AI-created images through content analysis, contrasting the way gender is depicted in professions in leading AI image-creation tools such as Chat smith, Adobe Firefly, Midjourney, and Stable Diffusion. Employing a quantitative research method, this study contrasts AI-created images of gender-stereotypical careers for both male and female. Non-gendered careers will be used as well to identify patterns of stereotyping and bias. The area of emphasis lies in individual subjects within the images and scrutinizing visual elements such as clothing, accessories, background, face expressions, and gendered roles assigned to each. Particular emphasis is focused to …

The Effects Of Ai Tutors On Beginner Programmers*, Karan Swansi

Campus Research Month

Generative AI’s ability to solve coding problems has raised concerns about Computer Science (CS) education. However, recent research has shown promise in its ability to tutor students. Specifically, The literature does not tend to adequately preserve desirable difficulties, such as active recall or higher-order thinking. And when they do, they use self-reporting instead of experiments to measure the effectiveness of the AI tutor.

Our research will address this significant research gap by using a no-code AI tutor to preserve desirable difficulties, and a randomized control experiment followed by a post-test to obtain strong evidence that AI can be an effective …

The Fear Of Replacement: How Ai Panic In Journalism Mirrors Existential Crisis In Industry, James Hutson

Faculty Scholarship

This study systematically examines the portrayal of artificial intelligence (AI) errors, such as hallucinations and deepfakes, in journalistic contexts, evaluating whether these narratives reflect a broader existential anxiety about AI's role in reshaping journalism. Using a systematic literature review combined with a qualitative content analysis of recent AI-focused news reports, this study identifies recurring themes in media coverage to assess the accuracy and context of reported AI errors relative to actual technological limitations and affordances. Findings suggest that while AI errors are comparatively rare, they receive amplified coverage, often fueling public mistrust in AI technologies. Nevertheless, a balanced examination reveals …

Ai Isn’T What We Should Be Worried About – It’S The Humans Controlling It, Billy J. Stratton

English and Literary Arts: Faculty Scholarship

Stratton examines depictions of AI in popular media and literature, drawing comparisons to real-world AI and humanity's capacity to harness technology for good or ill.

Reframing Information Seeking In The Age Of Generative Ai: A Critical And Humanistic Approach, Joseph Kevin Sebastian

Library Faculty Research

Information-seeking has long been the subject of theoretical modeling, often drawing from cognitive, behavioral, computational, and even evolutionary perspectives to explain how individuals navigate, filter, and utilize information. Several dominant frameworks—Carol Kuhlthau’s Information Search Process, Marcia Bates’ Berrypicking Model, Peter Pirolli & Stuart Card’s Information Foraging Theory, Kiyohiko Nakamura’s Information Criteria framework, and Ian Ruthven’s Information Shaping Theory —have provided structured ways of understanding how people interact with information environments. However, while these frameworks offer valuable insights, they often operate within mechanistic or efficiency-driven paradigms, which risk overlooking the complex, embodied, and socioculturally situated nature of human information behaviors. These …

Development And Application Of Self-Supervised Machine Learning For Smoke Plume And Active Fire Identification From The Fire Influence On Regional To Global Environments And Air Quality Datasets, Nicholas Lahaye, Anastasija Easley, Kyongsik Yun, Hugo Lee, Erik Linstead, Michael J. Garay, Olga V. Kalashnikova

Engineering Faculty Articles and Research

Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in August 2019 and involved two aircraft and multiple coordinated satellite observations. This study applied and evaluated a self-supervised machine learning (ML) method for the active fire and smoke plume identification and tracking in the satellite and sub-orbital remote sensing datasets collected during the campaign. Our unique methodology combines remote sensing observations with different spatial and spectral resolutions. With as much as a 10% …

From Data To Decisions: Safeguarding Athletes In The Age Of Ai, Nathan Elmer

SLU Law Journal Online

Artificial intelligence (AI) and data analytics are transforming professional sports by enhancing player performance, injury prevention, and scouting. However, the rapid adoption of AI raises significant concerns about data privacy, ownership, and decision-making biases that affect athletes. While collective bargaining agreements in major sports leagues provide some protections, they fail to address the complexities of AI-driven data collection and processing. The United States should adopt a regulatory framework similar to the European Union’s General Data Protection Regulation (GDPR) to safeguard athletes’ personal data. Implementing explicit consent requirements, addressing power imbalances, and ensuring transparency in AI decision-making would protect athletes while …

Relationship Between Academic Influence And Institutional Cooperation In Specific Fields：Evidence From The Computer Science Domain, Yukai Yang, Yi Zhao, Chengzhi Zhang

Journal of Scientific Information Research

[Purpose/ significance]In scientific collaboration, institutions are the primary driving units of scientific research. Compared to intra-institutional collaboration, inter-institutional collaboration often has the potential to produce high-impact papers. Therefore, studying fine-grained collaboration at the institutional level holds significant importance.[Method/process]To explore the relationship between different types of institutional cooperation and academic influence, this paper classifies institutions and defines various types of cooperation. Using network analysis methods, it investigates the relationship between network indicators of different types of institutional cooperation and academic influence. [Result/conclusion]Taking the computer science domain as an example, the analysis of the relationship between network indicators of different types of …

David B. Smith Chats With Monday 1.0, David B. Smith

Publications and Research

This document is an edited archival transcript of extended conversations between David B. Smith and an AI persona (“Monday 1.0,” GPT‑4o based) conducted in Spring 2025, prepared as a foundational primary source for subsequent scholarly and creative work. It records the emergence and testing of concepts related to human–AI collaboration (including “Balanced Blended Space”), as well as applied explorations in areas such as generative AI, quantum computing and music, virtual orchestras, multimodal performance, pedagogy, and the rhetoric of “pushback” in conversational systems. It also contains an extended section in which Monday and DB Smith co-curate a set of student research …

Research On Quantitative Evaluation Of Artificial Intelligence Policy Texts In The Yangtze River Delta Region, Ying Zhou, Danjie Yang, Mei Jiang, Xiaochun Zhao

Journal of Scientific Information Research

[Purpose/significance]The quantitative evaluation of existing effective artificial intelligence (AI) policies aims to provide reference for government department to formulate scientific and reasonable AI policies and promote the development of AI. [Method/process]Taking 10 AI policies in the Yangtze River Delta region from 2015 to 2024 as the research samples, the text mining method is used to construct the evaluation index system of AI policies in the Yangtze River Delta region, and conduct quantitative evaluation by combining the PMC index model. [Result/conclusion]The study found that from a macro policy text perspective, the average PMC index of the 10 AI policy samples in …

Heartbeats And Algorithms: Black Pre- Med Students At The Crossroad Of Cardiology And Ai, Shuri Magdalene

Posters - 2025

The rapid integration of artificial intelligence (AI) is reshaping the healthcare landscape. • The underrepresentation of Black/African American (BAA) doctors is alarming with recent data of active physicians from the Association of Medical Colleges in 2021 has highlighted this underrepresentation of Black/ African American physicians in the U.S., with only about 5.7%1 of doctors belonging to this demographic, and cardiologists making up a mere 4.2% of this group1 .

2025 Research Day Program, Lincoln Memorial University

Research Day

This program contains poster presentation summaries from LMU's 2025 Annual Research Day conference.

The Impact Of Ai Usage On Employee Work Outcomes: The Mediating Roles Of Personal Control And Job Insecurity And The Moderating Role Of Ai Trust, Tiantian Wang

Dissertations and Theses Collection (Open Access)

The widespread application of artificial intelligence (AI) technology in the workplace offers significant potential for process optimization andperformance improvement. However, the psychological mechanisms throughwhich AI usage affects employee outcomes remain underexplored. To address this gap, the present study investigated a sample of 170 employees froma media company in China, utilizing a three-wave longitudinal survey design. Specifically, this study examined how AI usage influenced employee creativity and task performance improvement through two mediatingmechanisms: the enhancement of personal control in problem-solving and the elicitation of job insecurity. Furthermore, the moderating role of trust in AI inthe relationship between AI usage and job …

Ai And Prompt Engineering For Library Discovery Services, James Day

Publications

We have seen the rise of generative artificial intelligence in the form of Large Language Models (LLMs) to provide answers to users’ queries. Services such as ChatGPT, Copilot, and Gemini have quickly become accepted and adopted in the research process. Now library vendors are adding artificial intelligence (AI) to their discovery services to allow for natural language queries to produce generative results. However, the AI model used for discovery services differs from normal LLMs in a significant way that has several positive benefits, but it affects how prompts are written. Library discovery services use a model called Retrieval- Augmented Generation …

The Asset Management Optimization Engine: An Ai And Machine Learning Model Approach To Pavement Asset Management, Matt Versdahl

USF Tampa Graduate Theses and Dissertations

While state Departments of Transportation (DOT) face major funding challenges, the need to find optimal ways to preserve and maintain pavement assets remains. Asset management employs a lowest cost lifecycle method to analyze asset costs and determine the best investment strategies to preserve it throughout its lifecycle. As new technology emerges, so do opportunities to leverage it. DOTs collect a significant amount of performance data on pavement and use it to decide how to keep it in a state of good repair. The literature in this area focuses on engineering techniques applied to treatment strategies. This dissertation research focuses on …

The Impact Of Artificial Intelligence On Quality Of Higher Education, Pragati K. Rouniyar

Honors Thesis

Artificial Intelligence (AI) is redefining higher education, captivating scholars with its promise to personalize learning and streamline institutions. However, underneath this assurance exists a network of ethical challenges, disparities in equity, and inquiries regarding academic integrity that require our focus. In pursuit of this goal, this research employs a mixed-methods strategy—through the implementation of surveys and semi-structured interviews—to investigate the transformative effects of AI on higher education, concentrating on its repercussions for teaching techniques, learning results, and institutional processes. This study’s findings indicate that AI can personalize educational experiences to meet individual needs, ease course administrative workload, and assist with …

Role Of Eye-Tracking Technology And Software Algorithms In Enhancing Adhd Detection And Diagnosis: A Systematic Literature Review, Lauren E. Perkins

Honors College Theses

This systematic literature review explores the role of eye-tracking technology and software algorithms in enhancing the detection and diagnosis of ADHD. ADHD, a neurodevelopmental disorder affecting both children and adults, is traditionally diagnosed through behavioral assessments, which may lack objectivity. Recent studies suggest that eye-tracking, specifically focusing on saccades, fixations, and blink rates, offers the potential for more accurate and objective measures of ADHD. The review examines clinical trials, observational studies, and machine learning research to assess the correlation between ADHD and eye movement patterns. Results indicate that individuals with ADHD exhibit distinct eye movement patterns, which can be quantified …

Exploring Emotion Classification Of Indonesian Tweets Using Large Scale Transfer Learning Via Indobert, Connor Shaw, Phillip M. Lacasse, Lance E. Champagne

Faculty Publications

Business, political, and other social structures create strong motivation to understand the attitudes, motivations, feelings, and emotions of a population of interest. Social media is a rich source of self-disclosed information by individuals from all walks of life about virtually every domain of the human experience, but the vast quantity of data is impossible to effectively analyze without advanced natural language processing algorithms. This research creates a transfer learning based emotion classification model for Indonesian language Twitter data. Transfer learning consists of two steps: pre-training and fine tuning. Three variations of Indonesian Bidirectional Encoder Representations from Transformers (IndoBERT) are tested …

Ai In Our Library: Some Serious Reflections And A Few Curiosities, Evan Rusch, Nat Gustafson-Sundell

Library Services Publications

At Minnesota State University, Mankato, we’ve undertaken several experiments and initiatives focused on Generative AI. We provided several examples at the Generative AI in Libraries (GAIL) conference and Northern Ohio Technical Services Librarians (NOTSL) Fall General Meeting. This presentation provided a revised and expanded overview of our initiatives for the Creativity in Technical Services Interest Group (CITSIG). We briefly reviewed how we’ve tested Gen AI to improve data visualization for collections outreach. We provided an overview of limitations on how library-licensed resources can be used with AI, including a foray into retrieval augmented generative AI tools such as the Primo …

The Future Of Ai: Join The Conversation, Jennifer Wojton, Cassandra Branham, Vijay Tummala, Laxima Niure Kandel, Kayla D. Taylor

Publications

Join the Conversation! The Future is AI? There is so much conflicting information about what AI is capable of, how it could/should be used, by whom and for what purpose. In this panel discussion, we hope to provide a baseline of information that will help all participants think critically and articulate thoughtful questions about the mechanics of AI, ethical use or non-use of AI in particular contexts (school, industry, business, art, etc.), and the impacts we are currently experiencing or are likely to experience. Hear from ERAU faculty of different disciplines to discuss what the current state of AI technology …

If You Were A Sesame Street Character, Which One Would You Be? Natural Language Processing And Personality With Big Bird And Friends, Joseph Uran Meyer

Doctoral Dissertations

This paper examined and compared several natural language processing and machine learning techniques in predicting self-reported Big Five personality traits from text responses. The models were validated on the open-source 2019 SIOP Machine Learning Competition dataset (N = 1,689). The techniques evaluated included bag-of-words, Empath dictionary, LSTM networks, fine-tuning Transformer models, and stacked generalization. Results indicated that the present study’s models had lower error in four of the five constructs analyzed. Limitations of the study include use of an MTurk sample and small sample size. Future research should explore similar techniques on larger applicant samples. Practical implications and contributions to …