Artificial Intelligence and Robotics Commons^™

Why Ai’S Role In Advancing Sustainability Is Underestimated, Lipika Bhattacharya

CCX Research

AI has quietly, but powerfully, woven itself into the fabric of our everyday lives. Yet, AI's potential impact on creating a more sustainable world is undervalued. The author examined artificial intelligence's (AI) role in advancing sustainability. She outlined how AI can be applied in various domains such as agriculture, water management, industry, urban planning, and biodiversity conservation for transformative effects.

Artificial Intelligence In Surgical Coding: Evaluating Large Language Models For Current Procedural Terminology Accuracy In Hand Surgery, Emily Isch, Jamie Lee, D. Mitchell Self, Abhijeet Sambangi, Theodore E. Habarth-Morales, John R. Vaile, E. J. Caterson

Department of Surgery Faculty Papers

PURPOSE: The advent of large language models (LLMs) like ChatGPT has introduced notable advancements in various surgical disciplines. These developments have led to an increased interest in the use of LLMs for Current Procedural Terminology (CPT) coding in surgery. With CPT coding being a complex and time-consuming process, often exacerbated by the scarcity of professional coders, there is a pressing need for innovative solutions to enhance coding efficiency and accuracy.

METHODS: This observational study evaluated the effectiveness of five publicly available large language models-Perplexity.AI, Bard, BingAI, ChatGPT 3.5, and ChatGPT 4.0-in accurately identifying CPT codes for hand surgery procedures. A …

Gender Biases Within Artificial Intelligence And Chatgpt: Evidence, Sources Of Biases, And Solutions, Qi Hui Jerlyn Ho, Andree Hartanto, Andrew Koh, Nadyanna M. Majeed

Research Collection School of Social Sciences

The growing adoption of Artificial Intelligence (AI) in various sectors has introduced significant benefits, but also raised concerns over biases, particularly in relation to gender. Despite AI's potential to enhance sectors like healthcare, education, and business, it often mirrors reality and its societal prejudices and can manifest itself through unequal treatment in hiring decisions, academic recommendations, or healthcare diagnostics, systematically disadvantaging women. This paper explores how AI systems and chatbots, notably ChatGPT, can perpetuate gender biases due to inherent flaws in training data, algorithms, and user feedback loops. This problem stems from several sources, including biased training datasets, algorithmic design …

Patient Consent And The Right To Notice And Explanation Of Ai Systems Used In Health Care, Meghan E Hurley, Benjamin H Lang, Kristin Marie Kostick-Quenet, Jared N Smith, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

Given the need for enforceable guardrails for artificial intelligence (AI) that protect the public and allow for innovation, the U.S. Government recently issued a Blueprint for an AI Bill of Rights which outlines five principles of safe AI design, use, and implementation. One in particular, the right to notice and explanation, requires accurately informing the public about the use of AI that impacts them in ways that are easy to understand. Yet, in the healthcare setting, it is unclear what goal the right to notice and explanation serves, and the moral importance of patient-level disclosure. We propose three normative functions …

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley

Publications

Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …

A Review Of Racial Differences And Disparities In Ecg, Jianwei Zheng, Chizobam Ani, Islam Abudayyeh, Yunfan Zheng, Cyril Rakovski, Ehsan Yaghmaei, Omolola Ogunyemi

Mathematics, Physics, and Computer Science Faculty Articles and Research

The electrocardiogram (ECG) is a widely used, non-invasive tool for diagnosing a range of cardiovascular conditions, including arrhythmia and heart disease-related structural changes. Despite its critical role in clinical care, racial and ethnic differences in ECG readings are often underexplored or inadequately addressed in research. Variations in key ECG parameters, such as PR interval, QRS duration, QT interval, and T-wave morphology, have been noted across different racial groups. However, the limited research in this area has hindered the development of diagnostic criteria that account for these differences, potentially contributing to healthcare disparities, as ECG interpretation algorithms largely developed from major …

Limitations In Speech Recognition For Young Adults With Down Syndrome, Franceli L. Cibrian, Yingying 'Yuki' Chen, Kayla Anderson, Cecilia Marie Abrahamsson, Vivian Genaro Motti

Engineering Faculty Articles and Research

Speech recognition has the potential to make technology more accessible to users. However, the accuracy of speech recognition remains limited for users with disabilities, including those with Down Syndrome, and the types and frequencies of recognition errors are poorly understood. This paper characterizes these problems, focusing on errors occurring when recognizing Down Syndrome speech. We analyze the transcripts from six speech recognition algorithms (Google, IBM, Otter.ai, Microsoft, AssemblyAI, OpenAI) using the audio content of 15 individuals with Down Syndrome (331 dialogues; 3428 words). Our analysis shows: (1) significant difference in speech recognition accuracy for people with Down Syndrome compared to …

Zombie-Auras: Genai And Hybrid Text Production, Joshua Nieubuurt

English Faculty Publications

This paper explores the iterative evolutions of textual production and their impact on the “aura” of texts, as conceptualized by Walter Benjamin. The study identifies three key phases of textual production: the natural, the mechanized, and the digitized, each progressively displacing the “cult value” of texts. This cult value is lost through increased ease of creation, reproduction, dissemination, and dislocation of creators and audiences in time and space. The advent of Generative AI (GenAI) marks the latest evolution, transforming the “aura” into a memetic “zombie” form—familiar yet opaque, evoking both the sublime and fear. By examining Benjamin’s notion of “aura” …

Chatgpt Didn’T Write This: Evaluating The Impact Of Llms With A Case Study In Grading Cuny Language Immersion Program Student Essays, Benjamin Inbar

Dissertations, Theses, and Capstone Projects

This study evaluates the capabilities and limitations of large language models (LLMs), specifically OpenAI’s ChatGPT-4o, in grading essays from students in the City University of New York’s Language Immersion Program. The program serves English language learners with diverse linguistic and demographic backgrounds, offering intensive language instruction to prepare students for academic success in college. Using a dataset of 30 pre- and post-program essays scored by program instructors and ChatGPT-4o under three paradigms, this research explores the alignment between human and AI-generated scores across five rubric-based competency areas. Findings reveal that ChatGPT-4o aligns moderately with human grading, with the strongest agreement …

Ai As Your Ally: The Effects Of Ai-Assisted Venting On Negative Affect And Perceived Social Support, Meilan Hu, Xavier Cheng Wee Chua, Shu Fen Diong, K. T. A. Sandeeshwara Kasturiratna, Nadyanna M. Majeed, Andree Hartanto

Research Collection School of Social Sciences

In recent years, artificial intelligence (AI) chatbots have made significant strides in generating human-like conversations. With AI's expanding capabilities in mimicking human interactions, its affordability and accessibility underscore the potential of AI chatbots to facilitate negative emotional disclosure or venting. The study's primary objective is to highlight the potential benefits of AI-assisted venting by comparing its effectiveness to venting through a traditional journaling platform in reducing negative affect and increasing perceived social support. We conducted a pre-registered within-subject experiment involving 150 participants who completed both traditional venting and AI-assisted venting conditions with counterbalancing and a wash-out period of 1-week between …

Towards The Next Generation Of Geospatial Artificial Intelligence, Gengchen Mai, Yiqun Xie, Xiaowei Jia, Ni Lao, Jinmeng Rao, Qing Zhu, Zeping Liu, Yao-Yi Chiang, Jiao, Junfeng

Research Collection College of Integrative Studies

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote …

The Year Of Ai: Raising Campus Awareness Through Art, Exhibits, And Community Engagement, Essraa Nawar

Library Articles and Research

This poster highlights the Leatherby Libraries’ leadership in advancing AI literacy through creative, inclusive, and interdisciplinary approaches. As part of Chapman University’s “Year of AI,” the library launched initiatives such as Beyond the Lens and AI: The Next Chapter, blending art, ethics, and education to inspire campus-wide engagement. Through collaboration with IS&T, Town & Gown, and academic departments, the library positioned itself as a hub for ethical dialogue and innovation. The poster shares replicable models for how libraries can foster AI awareness through community partnerships, exhibitions, and experiential learning.

Making The Most Of Artificial Intelligence And Large Language Models To Support Collection Development In Health Sciences Libraries, Ivan Portillo, David Carson

Library Articles and Research

This project investigated the potential of generative AI models in aiding health sciences librarians with collection development. Researchers at Chapman University’s Harry and Diane Rinker Health Science campus evaluated four generative AI models—ChatGPT 4.0, Google Gemini, Perplexity, and Microsoft Copilot—over six months starting in March 2024. Two prompts were used: one to generate recent eBook titles in specific health sciences fields and another to identify subject gaps in the existing collection. The first prompt revealed inconsistencies across models, with Copilot and Perplexity providing sources but also inaccuracies. The second prompt yielded more useful results, with all models offering helpful analysis …

Ai 101: What It Can (And Can't) Do For You, April Sheppard

Staff and Faculty Scholarship

In this presentation, April defines AI, describes how it works, reviews some pros and cons, and finally discusses what AI can actually accomplish in its current iteration.

The Influence Of Generative Artificial Intelligence On Leadership: An Exploration Of Technology Professionals' Perceptions Regarding Leadership, Adaptation, And Organizational Culture In The Digital Age, Paul Thomas Herdman

Theses, Dissertations and Capstones

The emergence of generative artificial intelligence (GenAI) has introduced new complexities for organizational leadership, requiring technology professionals to adapt in real time to evolving digital tools, strategic demands, and cultural dynamics. Although prior research has examined AI’s broad influence on business processes, few studies have explored how technology leaders experience and interpret the leadership challenges and opportunities arising from GenAI. This qualitative dissertation addressed that gap by investigating the perceptions of senior technology professionals regarding GenAI’s influence on leadership roles, competencies, decision making, and organizational culture. Using Lanigan’s (1977) phenomenological method of human science, this study explored the lived experiences …

Modeling Trust And Deception In Multi-Agent Reinforcement Learning Using The Werewolf Game, Pathikkumar Dharmeshbhai Patel

Computer Science and Engineering Theses - Archive

This thesis explores the emergence of trust, deception, and adaptive strategy in multi-agent reinforcement learning (MARL) environments using the social deduction game Werewolf as a simulation framework. In this environment, agents operate with hidden roles, incomplete information, and the need to reason about others’ intentions- mirroring the complexities of real-world social interactions. We present and evaluate two agent architectures: Agent vA, a symbolic, heuristic-based agent with probabilistic trust modeling and scalable memory structures; and Agent vB, a modular Q-learning agent that learns phase-specific policies through reinforcement. Agent vA relies on symbolic reasoning, bounded belief updates, and generalizable heuristics, while Agent …

Technology-Facilitated Abuse (Tfa): Analyzing Trends, Tactics, And Victim Responses On Reddit, Solomon G. Dandekar

Computer Science and Engineering Theses - Archive

The increasing integration of technology into daily life has provided numerous benefits but also significant risks, particularly when exploited by malicious actors in cases of technology facilitated abuse (TFA). Per- petrators can misuse technology to monitor, control, and intimidate their partners, random strangers, etc. exacerbating cycles of abuse. From location tracking and cellphone surveillance to smart device manipula- tion, spyware, and doxing, digital tools have become powerful instruments for coercion and control. This research project investigates the role of technology in stalking and harassment by analyzing discussions on a relevant subreddit where victims share their experiences, strategies for coping, and …

Maritime Industry Cybersecurity Threats In 2025: Advanced Persistent Threats (Apts), Hacktivism And Vulnerabilities, Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Mihaela Hnatiuc, Gabriel Raicu

Engineering Management & Systems Engineering Faculty Publications

Background: The maritime industry, vital for global trade, faces escalating cyber threats in 2025. Critical port infrastructures are increasingly vulnerable due to rapid digitalization and the integration of IT and operational technology (OT) systems. Methods: Using 112 incidents from the Maritime Cyber Attack Database (MCAD, 2020-2025), we developed a novel quantitative risk assessment model based on a Threat-Vulnerability-Impact (T-V-I) framework, calibrated with MITRE ATT&CK techniques and validated against historical incidents. Results: Our analysis reveals a 150% rise in incidents, with OT compromise identified as the paramount threat (98/100 risk score). Ports in Poland and Taiwan face the …

Consequences Of Artificial Intelligence In Health Insurance: Lawsuits, Policy, And Ethics, Alyssa N. Roberts

Honors Undergraduate Theses

In recent years, the healthcare system has been burdened by a multitude of obstacles that hinder the ability to provide effective, affordable, and timely care. Among these, one of the most significant challenges is the role that health insurance plays in shaping the quality of care. Health insurance companies are designed to decrease financial strain on patients, but they have introduced inefficiencies through delayed coverage approvals, increased denials, and administrative costs. Artificial intelligence (AI) has started to play an integral role in resolving these issues for the health insurance industry. Through its quick automated claim processing, fraud screening, and reduced …

Ally With Ai: An Icebreaker To Unlock Career Aspirations For Online Or Hybrid Organizational Behavior Cohorts, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Modern organizational behavior classroom, which are increasing in size, diversity, and complexity, are shifting to online and hybrid learning environments, challenging the use of traditional icebreaker activities. This paper introduces a 15-minute icebreaker designed to address these issues while integrating the principles of Kolb's experiential learning theory and fostering social capital through peerr engagement in an online setting. By leveraging the availability of generative AI, students prompt a template code to unlock their career aspirations and stimulate social connections among their classmates. This provides an innovative teaching model for meeting the foundational icebreaker goal while serving a suitable tool for …

Application Of Physics-Informed Neural Networks On Crop Yield Prediction At Multiple Scales, Aditya P. Prabhu, Pratishtha Poudel, James V. Krogmeier

Discovery Undergraduate Interdisciplinary Research Internship

Accurately predicting crop yields is a critical challenge in sustainable agriculture, food security, and farm management. Traditional process-based models rely on agronomic domain knowledge, crop physiology and statistical approaches, while purely data-driven approaches leverage machine learning or deep learning models using meteorological and spatial data. Unfortunately, these black-box models(Data-drive approaches) often lack interpretability and fail to incorporate well-established physical principles. This project explores a hybrid approach by implementing Physics Informed Neural Networks, mainly, physics-based recurrent neural networks (PI-RNNs) for time-series yield prediction. PINNs allow for the integration of scientific knowledge directly into the model by embedding physical laws as constraints …

Understanding Misinformation On Social Media Through Truthfulness Stance, Zhengyuan Zhu

Computer Science and Engineering Dissertations - Archive

Misinformation on social media has become a pervasive issue that profoundly influences public opinion and decision-making. As false or misleading claims circulate widely online, there is a critical need for analytical tools to understand how people react to such claims. This dissertation introduces the concept of truthfulness stance as a key lens for social sensing. In essence, truthfulness stance assesses whether a textual utterance believes a factual claim to be true, false, or expresses a neutral stance or no stance toward the claim. Leveraging stance in this manner fills an important gap in misinformation research: it enables us to gauge …

Research On Automated Generation And Evaluation Of Patent Claimsbased On Gpt-4, Junhua Li, Qian Yuan, Xiang Yan, Changhong Lv

Journal of Scientific Information Research

[Purpose/significance]This study aims to automatically generate claims using the GPT-4 model, in order to reduce the writing difficulty for inventor and improve the work efficiency and quality. [Method/process]The article constructs Prompts suitable for automatically generating patent claims and implements four prompting strategies: ZeroShot, Exact-Drafting, Stepwise-Claim, and Exact-Step Claim. By inputting patent specifications and technical disclosure documents into the GPT-4 model and using Prompts to guide its output, the automated generation of patent claims is achieved. The ROUGE and BERTScore evaluation metrics were used to assess the quality of the text, and the generated text was analyzed in comparison with the …

Research On Emerging Technology Topic Identification Based On Bertopic, Dakun Wang, Bolin Hua

Journal of Scientific Information Research

[Purpose/significance]Identifying and foreseeing emerging technologies, bring technological first-mover advantages to enterprises and governments, and grasp technological development trends in a timely manner. [Method/process]This study uses BERTopic's topic modeling method to obtain domain topic distribution, and merges paper and patent topics based on the cosine similarity of topic vectors to identify emerging topics. [Result/conclusion]Using the BERTopic topic modeling method combined with index evaluation can effectively identify emerging topics and emerging terms.Taking the field of new energy vehicles as an example to carry out empirical research, using two methods: divided verification period and data verification method, 12 of the 16 identified topics …

Extending A Pretrained Language Model (Bert) Using An Ontological Perspective To Classify Students' Scientific Expertise Level From Written Responses, Heqiao Wang, Kevin C. Haudek, Amanda D. Manzanares, Chelsie L. Romulo, Emily A. Royse, Caterina B. Azzarello

Human Movement Studies & Special Education Faculty Publications

The complex and interdisciplinary nature of scientific concepts presents formidable challenges for students in developing their knowledge-in-use skills. The utilization of computerized analysis for evaluating students' contextualized constructed responses offers a potential avenue for educators to develop personalized and scalable interventions, thus supporting the current teaching and learning of science. While prior research in artificial intelligence has demonstrated the effectiveness of algorithms, including Bidirectional Encoder Representations from Transformers (BERT), in tasks like automated classifications of constructed responses, these efforts have predominantly leaned towards text-level features, often overlooking the exploration of conceptual ideas embedded in students' responses from a cognitive perspective. …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Psychology Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Application Of Large Language Model Methods In Scientific And Technical Intelligence Practice, Bolin Hua, Yingze Wang

Journal of Scientific Information Research

[Purpose/significance]With the strong ability to process large-scale datasets and outstanding performance in various natural language processing tasks, large language models (LLMs) have excelled across multiple industries.Since scientific and technical intelligence primarily relies on textual data, LLMs are naturally well-suited for this field, ushering in a new wave of transformative changes. [Method /process]This article discusses the advantages of LLMs from five perspectives: low-dimensional dense vector representations of text, large-scale pre-trained models,fine-tuning and prompt learning, high-quality large-scale training data, and human alignment techniques. [Result/conclusion]LLMs have extensive applications in tasks such as intelligence identification, intelligence tracking, intelligence evaluation, and intelligence prediction, resulting in …

From Philosophy To Nlu: Evolving Definitions Of Research Hypotheses, Jian Wu, Sarah Rajtmajer

Computer Science Faculty Publications

Over the past decades, alongside advancements in natural language processing, significant attention has been paid to training models to automatically extract, understand, test, and generate hypotheses in open and scientific domains. However, interpretations of the term hypothesis for various natural language understanding (NLU) tasks have migrated from traditional definitions in the natural, social, and formal sciences. Even within NLU, we observe differences defining hypotheses across literature. In this paper, we overview and delineate various definitions of hypothesis. Especially, we discern the nuances of definitions across recently published NLU tasks. We highlight the importance of well-structured and well-defined hypotheses, particularly as …