Artificial Intelligence and Robotics Commons^™

Looking Good: The Math Behind Computer Vision*, Corbin Weiss

Campus Research Month

Exploring the mathematical foundations of a Multilayer Perceptron (MLP), a foundational approach to computer vision. Then expanding this understanding to create a visualization of the representation of reality in the MLP.

Dictating The Divine: Revisiting Authorship, Intention, And Authority From Sacred Texts To Generative Ai, James Hutson, W. Travis Mcmaken

Faculty Scholarship

This article interrogates the historical practice of mediated authorship in religious texts to draw critical parallels with contemporary debates surrounding generative artificial intelligence (AI), specifically large language models (LLMs). By juxtaposing the mediated authorship of sacred texts, such as the Hebrew Bible and New Testament—where figures like the Apostle Paul dictated theological concepts to scribes who infused these directives with their interpretive insights—with the generative processes of LLMs, this research underscores the shared dynamics of co-constructed authorship across historical and technological contexts. Employing interdisciplinary methodologies from art history, textual studies, and reception theory, as well as theological and biblical studies, …

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 Foundations And Applications: Summary Of A Panel Discussion At Loyola University Chicago, George K. Thiruvathukal, Dmitry Dligach, Shilpika, Michael B. Burns, Joseph Vukov, Fraser Turner, Mary Usher

Computer Science: Faculty Publications and Other Works

This document summarizes the panel discussion titled "AI Foundations and Applications," held at Loyola University Chicago as part of the "Forum on Global Affairs: Artificial Intelligence in a Globalized World" series. The panel brought together interdisciplinary experts to discuss the foundational aspects of artificial intelligence (AI), its applications, ethical considerations, and implications for education and society.

Ai In Academia: Supportive Ally Or Cheating Accomplice?, Ian Offner

INSPIRE Student Research and Engagement Conference

• The purpose of this study was to investigate student attitudes toward the use of AI for college class work in a variety of domains.
• For some situations, the use of the AI was collaborative. The students would have to utilize their own abilities in conjunction with the AI as a co-intelligence. For some situations, the AI was a dominant agent, requiring little input from the students.

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.

Evaluating Wrist Placement And Signal Processing Techniques For Real-World Hrv Monitoring Using Ppg, Andrew Murphy

College of Computing and Digital Media Dissertations

This thesis investigates trade-offs between signal quality and data coverage in photoplethysmographic (PPG) heart rate variability (HRV) monitoring using wrist-worn devices. The goal was to evaluate whether wrist placement and signal processing techniques can improve measurement reliability in real-world conditions. Data was collected from healthy participants wearing smartwatches on both wrists during rest and a structured math task introducing natural wrist movement. Three distinct processing methodologies were compared, including a proposed Rolling-Standardized Derivative (RSD) approach. Results showed that while HRV signals from both wrists were highly correlated at rest, motion caused a measurable drop in signal quality and inter-wrist agreement, …

Closing Remarks, Jay Yang

Value and Responsibility in AI Technologies

Closing remarks from director of Gonzaga's Institute for Informatics and Applied Technology, Dr. Jay Yang, with a reception to follow.

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% …

Ceker: A Generalizable Llm Framework For Literature Analysis With A Case Study In Unikernel Security, Alex Wollman, John Hastings

Research & Publications

Literature reviews are a critical component of formulating and justifying new research, but are a manual and often time-consuming process. This research introduces a novel, generalizable approach to literature analysis called CEKER which uses a three-step process to streamline the collection of literature, the extraction of key insights, and the summarized analysis of key trends and gaps. Leveraging Large Language Models (LLMs), this methodology represents a significant shift from traditional manual literature reviews, offering a scalable, flexible, and repeatable approach that can be applied across diverse research domains. A case study on unikernel security illustrates CEKER's ability to generate novel …

Grounding Ai Use In Learning Science: A Conversation With Steven Miller, Steven Miller, Lieven Demeester

CASTLe: Collection of Articles on Scholarship for Teaching and Learning

In this insightful interview, SMU Associate Provost (Teaching and Learning Innovation) Lieven Demeester and Professor Emeritus of Information Systems Steven Miller discuss the integration of artificial intelligence (AI) in teaching and learning, emphasising the importance of grounding AI use in the fundamentals of learning science. They explore the evolving role of education in the context of AI advancements, highlighting the need for educators to focus on the cognitive aspects of learning, such as goal-directed practice and feedback. They also address the potential of AI as a collaborative agent in group projects and the importance of maintaining accountability and quality control …

Impact Of Data Snooping On Deep Learning Models For Locating Vulnerabilities In Lifted Code, Gary Mccully, John Hastings, Shengjie Xu

Research & Publications

This study examines the impact of data snooping on neural networks used to detect vulnerabilities in lifted code, and builds on previous research that used word2vec and unidirectional and bidirectional transformer-based embeddings. The research specifically focuses on how model performance is affected when embedding models are trained with datasets, which include samples used for neural network training and validation. The results show that introducing data snooping did not significantly alter model performance, suggesting that data snooping had a minimal impact or that samples randomly dropped as part of the methodology contained hidden features critical to achieving optimal performance. In addition, …

Coding An Assignment Calculator Exclusively With Chatgpt, Andy Tincknell, Heather P. Vandyne, Lisa K. Bell

SACAD: Scholarly Activities

Large Language Models like ChatGPT are influencing higher education and society in broader ways, including the coding and programming of applications and websites (Silva et al., 2024). This poster will profile how Forsyth Library, with no coders on staff, used ChatGPT to program an Assignment Calculator LibGuide without human coding. It details the process, challenges, and outcomes while highlighting AI’s potential to enhance resources for academic success and considers its efficacy and ethical implications.

Ethical Work Cultures & Ai, Andrew Brei

Presentations - 2025

With the help of moral theories, several case studies, and insights from the world of behavioral ethics, my project aims to provide engineering professionals with the means to deal properly with moral issues that commonly arise in their chosen fields.

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 …

Development And Evaluation Of The Da Vinci Ai Tutor: Enhancing Accessibility And Personalized Learning In Art History Education, James Hutson, Tiffani Barner

Faculty Scholarship

This study examines the implementation of the Da Vinci AI Tutor, an innovative artificial intelligence (AI)-based tutoring platform designed specifically for enhancing personalized and accessible learning in art history within higher education. Launched in Fall 2024 at a private liberal arts institution in the Midwest, the system integrates a conversational AI avatar modeled after Leonardo da Vinci, incorporating immersive virtual reality environments and multimodal interaction capabilities to engage students across undergraduate survey courses, advanced Renaissance classes, and graduate comprehensive exam preparations. Addressing significant gaps in existing humanities education research, the current study explores two primary research questions: (i) How AI-driven …

Emerging Technologies In Beluga Research: Potential And Possibilities, Alejandro Zuniga-Schettino

Posters - 2025

Beluga whale face increasing threats in the Arctic, demanding effective research for conservation. Transitional methods going on field trips to collect short videos in excel, going on field trips to collect short videos, and having to rewatch the video are often time- consuming labor intensive, and limited in scope. This poster explores how engineering and AI can improve research. Engineering can provide robust tools like autonous underwater vehicles with advanced sensors for data collection in challenging environments. These technology offer an enhanced understanding of belugas behavior and ecology

Association Of Ai Derived Biomechanics And Hand Grip Strength, Theophile Nsabimana

Posters - 2025

Biomechanical analysis offers a way of better understanding the mechanism of a person's movement pattern or functional decline. Usually, motion analysis is costly and requires the purchase of a lot of equipment and software. This makes the technology out of reach of students, educators and researchers in austere settings.

Fortunately, artificial intelligence has brought affordability to motion analysis and created a whole new method of analyzing functional performance. OpenCap is an application which was produced by Stanford University and is hailed as being a future replacement to higher costing systems. Gait analysis provides an indication of a person's walking symmetry …