AI Exchange Poster Presentations

Aditi Saha, Tuskegee University

This study evaluates the performance of Quantum long short term memory (QLSTM) and classical LSTM models in time series forecasting. Through controlled parametric numerical experiments, the study examines the performance of both models using CPUs and GPUs in cloud environments. Our findings reveal significant improvements in the QLSTM model, with enhanced training accuracy and reduced test loss.

Allie Brandriet, Auburn University
Tanner Morrison, Auburn University
Shuqi Du, Auburn University

Ever wondered how AI could make your course design more engaging? Join us as we share how we designed a Workforce Management course using AI to create a semester-long student role-play. Students stepped into an HR Generalist's shoes, tackling real-world HR challenges. We'll discuss our successes, challenges, and practical tips for using AI to enhance your course design.

Amy Conway, Auburn University
Asim Ali, Auburn University

Auburn University is developing a new Undergraduate Certificate in Artificial Intelligence. This initiative aims to equip students from diverse disciplines with AI knowledge and skills. The poster will discuss the goals, process, and anticipated timeline for the initiative.

Betsy Gilbertson, Auburn University

In the evolving landscape of online education, leveraging data-driven insights is crucial for continuous improvement. This study explores the comparative efficacy of various AI engines in analyzing multifaceted data sources‚ namely Learning Management System (LMS) analytics, Panopto video engagement metrics, assignment performance data, and student feedback surveys. 

Chelsy Hooper, Auburn University

Learn about various ways AI literacy is addressed on our campus through in-house library workshops, collaborations across campus and with professional entities, online resources, and within credit courses. Integration strategies and examples of workshops and collaborative events will be shared, mainly focusing on integrating generative AI art within the Adobe Creative Cloud applications.

Courtney P. Heaton, Auburn University

Artificial intelligence (AI) can be utilized in disciplines such as animal sciences as a tool for undergraduate learning. Undergraduates are often not exposed to or comfortable with the creation of lesson plans or research proposals and experimental design. By utilizing AI, students can generate examples, ask questions, and feel more confident in their delivery of quality projects.

Danielle Hassan, The University of Alabama at Birmingham
Brooke Becker, The University of Alabama at Birmingham

This poster explores the transformative impact of artificial intelligence (AI) on academic libraries and the shifting landscape of librarianship.

Laura McNeill, University of Alabama
Tyler Roberts, University of Alabama
Lee Laska, University of Alabama

The integration of AI in teaching is now a crucial component of modern pedagogy. We have developed a microlearning video initiative aimed at equipping faculty with the knowledge and tools necessary to effectively incorporate AI into their teaching practices. A library of 100 on-demand 2-minute video resources means educators have the flexibility to learn and apply AI techniques at their own pace.

Heather S. Cole, The University of Alabama Capstone College of Nursing

This pilot study explores the integration of a conversational AI speaker in a simulation-based learning environment for entry-level nursing students. A quasi-experimental design assessed the acceptance of AI in healthcare simulation. Results show a significant increase in Technology Acceptance Model (TAM) scores post-simulation, indicating AI's potential to enhance nursing education and practice.

Israel Ncube, Alabama A&M University

We characterise the local stability of a certain class of static artificial neural networks endowed with multiple unbounded S-type distributed signal transmission time delays. The approach adopted exploits the notion of bounded linear functionals and the Riesz representation theorem in C[a,b].

Jessie Lynn, Dirt to Diva Productions, LLC.

IP Patrol is an algorithm and software that enables the comprehensive tracking and monitoring of digital content usage, ensuring artists and rights holders can assert control over their intellectual property effectively. Key Features include - comprehensive tracking royalty collection, and user-friendly dashboard tools that will provide an intuitive online interface for users. Patent pending.

Jonan Phillip Donaldson, University of Alabama at Birmingham

AI is not a threat, but an opportunity. We are training learning designers to leverage AI for augmented intelligence. These learning designers focus on developing learning experiences that enable learners to adapt, innovate, and flourish through the use of AI tools. This poster explores how AI tools can enhance learning experiences that foster creativity, productivity, and problem-solving.

Katelyn Nelson, Auburn University
Kailea Manning, Auburn University
David Marshall, Auburn University

This study examines higher education instructors' views on AI in teaching through qualitative interviews. Findings reveal cautious optimism about AI's benefits, alongside concerns about student dishonesty and over-reliance. The research aims to guide policy and strategies for effective AI integration, addressing both opportunities and challenges to enhance teaching practices.

Katelyn Nelson, Auburn University
Kailea Manning, Auburn University
Vanessa Harrison, Auburn University
Asim Ali, Auburn University 
Moriah Kent, Auburn University 
Chelsy Hooper, Auburn University 
Rachel Odomes, Auburn University

This study examinesdthe perceptions of student affairs professionals on the integration of artificial intelligence (AI) in higher education. Preliminary findings will be shared, offering key insights into the evolving role of AI within student affairs, while addressing essential topics such as ethical considerations and the broader impact of AI on the higher education landscape.

Lindsey Adams, MPA, MCP, Auburn University
R. Reid Hanson, DVM, DACVS, DACVECC, Auburn University

Maximize your course content potential with AI tools to automate content creation. This project shows how AI transforms course materials into valuable resources like practice exams and diverse exam versions. AI saves time, enhances student learning, and helps you achieve what you have always wanted but never had time for.

Luyu Liu, Auburn University, Department of Geosciences
Yilong Dai, Department of Computer & Information Science & Engineering, University of Florida
Kaiyue Wang, Department of Computer & Information Science & Engineering,  University of Florida
Meiqing Li, School of Public Administration, University of Central Florida
Xiang Yan, Department of Civil and Coastal Engineering, University of Florida

Assessing bus stop amenities is crucial for public transit research, planning, and infrastructure improvements. We present an automated, low-cost approach using Google Street View images and deep learning to evaluate bus stop amenities. By leveraging the YOLOv8 model, our method efficiently detects shelters and benches with high accuracy in major Florida cities.

Lydia Wilkes, Auburn University

This poster presents an approach to teaching critical AI literacy within a multiliteracies framework. The moves in the assignment can be used in any class: student as expert, as evaluator of AI output, and as critic of AI's effects on writing, the environment, labor, privacy, and more. Students' choice of topic and position as expert make it highly engaging for students.

Lynn W. Strong, Auburn University English Department

This poster explores integrating AI tools into course compositions and promoting multimodal communication, emphasizing the need for students to go beyond traditional writing. By adopting diverse methods‚ visual, auditory, and interactive‚ we prepare students for the competitive market, ensuring they are adaptable and proficient in multiple forms of expression for professional success.

Macaleigh Mancuso, Auburn University Harrison College of Pharmacy
Elizabeth W. Covington, Pharm.D., BCIDP; Auburn University, Harrison College of Pharmacy, Department of Pharmacy Practice 
Lindsey E. Moseley, Pharm.D., Ph.D, M.Ed.; Auburn University, Harrison College of Pharmacy, Department of Pharmacy Practice 
Courtney S. Watts Alexander, Pharm.D., M.S., BCPS, BCOP.; Auburn University, Harrison College of Pharmacy, Department of Pharmacy Practice

Custom GPTs can be trained to enhance efficiency in assignment creation and completion. By providing interactive tools for pre-class assignments, educators can set the stage for deeper learning and more meaningful classroom discussions. This project aims to showcase how the development, implementation, and evaluation of a custom GPT can complement and elevate pharmacy education. 

S. Raj Chaudhury, University of South Alabama
Lisa LaCross, University of South Alabama
Robin Lasey, University of South Alabama
Shelley Mayo, University of South Alabama 

Faculty at South Alabama have been supported in a variety of ways as they grapple with the opportunities and challenges of generative AI. Our faculty development and online learning Center has explored a multi-faceted approach of professional engagement through convenings, mini-courses, policy discussions and a book club. Program descriptions, findings and future plans will be shared. 

Shadi Alathamneh, Auburn University

Leveraging AI for Efficiency: A framework to develop, deploy, and assess custom generative chatbots in STEM courses. A custom chatbot, serving as a virtual teaching assistant, has been created using Microsoft Copilot and Teams to assist construction management students with coursework-related tasks.

Taieba Tasnim, Tuskegee University

Breast cancer is a major cause of death in women, making early detection essential. This study compares Quantum Convolutional Neural Networks (QCNNs) with classical CNNs for classifying benign and malignant tumors using the BreakHis dataset. QCNNs outperform CNNs in accuracy, particularly with smaller batch sizes, and demonstrate faster convergence and better computational efficiency.

Samiha Nazrul, Mohammad Rahman, Tuskegee University

Cloud-Based Cyber-Physical Systems (CBCPS) offer considerable benefits by harnessing computational and storage capacities in the cloud. However, disruptions in obtaining realtime access to cloud computational and network resources can impede the control of CBCPS. Hence, minimizing resource demands by adapting the controller’s sampling rate can enhance performance. Due to the dynamic nature of the system model, we employ reinforcement learning techniques. We demonstrate our approach through simulation to remotely control a car’s speed using cloud-based controllers, dynamically adjusting the sampling frequency to reduce network load and optimize cloud resource utilization. Our proposed method utilizes an actor-critic reinforcement learning framework, specifically the Deterministic Policy Gradient (DDPG) algorithm, to learn optimal policies that strike a balance between resource usage, response time, real-time performance, and system stability.