AI at UC

AI at UC
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Dr. Kelly Cohen’s Journey from Aerospace to Ethical AI Leadership
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Towards a responsible AI future
At the University of Cincinnati, we see artificial intelligence (Al) as a transformative force driving
collaboration and unlocking new opportunities across education, research, administration, and community engagement. By harnessing the collective expertise of our students, faculty, and staff. AI empowers us to solve complex problems, foster innovation, and create inclusive pathways for growth. Through collaborative efforts across all areas of our institution, we are building an environment that encourages academic exploration, technological advancement, and entrepreneurial ventures. This approach reflects our commitment to our core values of Impact, Innovation, and Inclusion, positioning UC to lead and thrive in an AI-driven world.
Use Cases
UC launched a call for AI use case submissions in early 2025, inviting students, faculty, and staff to propose ideas for pilot implementation. These proposals were reviewed by the AI Enablement Community of Practice (AIECOP) and selected based on impact, ROI, and alignment with UC’s strategic priorities.
AI for Undergraduate and Graduate Credential Certification
Proposer:
Molly McDermott-Fallon
Audience:
University Students and Faculty
Description:
AI will be used to streamline and modernize the review of student academic records, reducing manual effort and increasing accuracy. At the end of each term, the system will automatically assess degree progress using data from the Student Information System (SIS), ensuring timely validation of graduation requirements and enhancing the overall student experience.
ROI:
Streamlined credential certification processes, reduced administrative workload, and improved student satisfaction.
Implementing AI in Tutoring at UC  | Phase 1
Proposer:
20 Submissions across multiple colleges and units.
Audience:
UC Students and Faculty
Description:
Across UC, many courses—especially in regional and online programs—are delivered asynchronously, while tutoring remains largely synchronous and in-person. This creates a gap in support for students who need flexible, on-demand help. An AI-powered tutoring platform will provide asynchronous, course-aligned academic support across colleges and programs. Key features include Curriculum-specific tutoring aligned with course topics and pacing, On-demand chat and voice interaction for flexibility, Personalized tools such as study guides, quizzes, and practice exams, Coverage for hard-to-staff subjects and online-heavy programs. This solution promotes equitable academic support for all students—regardless of schedule, modality, or location—while improving learning outcomes, retention, and operational scalability.
ROI:
Enhanced student support, increased accessibility to tutoring services, and improved academic performance.
2-Sigma: AI-Driven Precision Medical Education Ecosystem  | Phase 1
Proposer:
Laurah Turner
Audience:
Medical Students and Educators
Description:
Developed at the UC College of Medicine, the 2-Sigma platform is an innovative AI-powered ecosystem advancing personalized medical education. It features dynamic clinical simulations, an adaptive Q-bank, and emerging tools like AI coaching, lesion localization games, and curriculum mapping. By analyzing student performance data to tailor learning pathways and aligning content with curricular goals, 2-Sigma enhances both instruction and outcomes—positioning UC as a leader in precision medical education.
ROI:
Improved medical education through personalized learning paths and cutting-edge technology integration.
Enhanced Student Feedback from Multiple Sources
Proposer:
Paul Gordon
Audience:
Professors and Students
Description:
This project addresses a common challenge in higher education: the timeintensive process of collecting and synthesizing student feedback from multiple sources such as peer evaluations, co-instructors, and design reviews. By leveraging AI to automate and streamline feedback compilation, the solution aims to enhance learning outcomes, reduce faculty workload, and deliver more timely, high-quality feedback to students—particularly in team-based and co-taught courses where traditional systems like Canvas fall short.
ROI:
More efficient feedback processes, improved student learning outcomes, and reduced grading time.
From RAG to Information Riches: Leveraging Generative AI
Proposer:
May Chang
Audience:
UC Libraries Users
Description:
UC Libraries seeks to enhance access to its extensive, multi-format digital collections by leveraging generative AI and retrieval-augmented generation (RAG). This initiative will allow users to interact with scholarly and historical content through natural, conversational interfaces—improving discoverability, user experience, and engagement across disciplines. Early R&D using BearcatGPT has demonstrated accurate responses and source citation, laying the groundwork for broader implementation across expanding digital collections.
ROI:
Expanded access to high-quality academic content through generative AI, enhancing research discovery, improving search precision, and delivering a modern user experience in digital scholarship
Increasing Student Engagement through AI
Proposer:
Stacy Jenkins
Audience:
University Students
Description:
Students have voiced a clear need for more responsive support in their learning journey. This initiative proposes the use of AI-powered tools—such as intelligent course chatbots, automated discussion board monitoring, and personalized nudges—to enhance engagement and well-being. Applications include identifying disengaged students, offering timely encouragement, supporting accessibility, and providing study assistance and deadline reminders. Together, these tools create a proactive, student-centered classroom environment that promotes success and retention.
ROI:
Higher student engagement, better learning outcomes, and increased retention rates
AI-Powered Accounts Payable Invoice Processing
Proposer:
Erik Sager
Audience:
University Finance Department
Description:
This use case applies AI technologies—including Natural Language Processing and Computer Vision to automate Accounts Payable invoice processing. By eliminating manual data entry, the solution significantly reduces processing time, improves accuracy, and lowers the risk of human error—enhancing efficiency across financial operations.
ROI:
Reduced processing time, increased accuracy, and cost savings in invoice management
Adaptive Phishing Detection and Robustness Testing
Proposer:
Lohith Srikanth Pentapalli
Audience:
Cybersecurity Teams
Description:
Phishing remains one of the most persistent cybersecurity threats. This project proposes an innovative AI-driven approach that strengthens phishing detection systems by combining an explainable genetic fuzzy logic model with an adversarial reinforcement learning agent. Operating within a secure, sandboxed environment, the system simulates sophisticated phishing attacks to expose vulnerabilities and retrain the model in real time. This adaptive strategy enhances detection accuracy, resilience to emerging threats, and overall cybersecurity posture.
ROI:
Enhanced cybersecurity posture through adaptive AI models, reducing institutional risk, improving phishing detection rates, and strengthening resilience against evolving threats.
Using AI Tools to Identify and Address Bias in University Curricula
Proposer:
Palak Shah
Audience:
University Curriculum Designers
Description:
This project aims to identify and mitigate implicit biases in teaching materials hosted within UC’s Learning Management System (Canvas). Using AI-powered tools and natural language processing, the initiative will analyze syllabi, lecture notes, and assignments for biased representations related to race, gender, socioeconomic status, ability, and culture. The resulting insights will generate actionable recommendations to enhance curricular inclusivity, reduce stereotype reinforcement, and support a more equitable learning environment across the university.
ROI:
More inclusive curricula; reduced algorithmic bias; and improved educational opportunity
The Use of AI to Enhance Communication and Operational Efficiency
Proposer:
Rajh Mehta
Audience:
UC International and University Honors Program
Description:
This use case explores the use of AI tools to enhance communication, streamline operations, and strengthen engagement with students, faculty, staff, and external partners. Early experimentation with platforms such as DeepSeek, Claude, and Suno.ai has demonstrated potential for generating high-quality content, automating routine tasks, and improving multilingual communication. The initiative aims to pilot these tools to support student recruitment and retention, increase operational efficiency, and deepen relationships with global and community stakeholders.
ROI:
Streamlined operations, improved communication, and strengthened stakeholder relationships.
Bearcat Achieve
Proposer:
DTS
Audience:
STEM Students at the University of Cincinnati
Description:
Bearcat AIchieve is an initiative designed to boost student success and retention in high-challenge STEM courses at the University of Cincinnati. By integrating adaptive tutoring, gamification, and real-time engagement tools, the program delivers personalized academic support tailored to individual student needs. Piloted in foundational courses like Business and Engineering calculus, it aims to reduce failure rates, improve engagement, and enable early interventions. Developed in partnership with Digital Technology Solutions (DTS), faculty, and student success teams, Bearcat AIchieve also offers experiential learning through AI-focused student internships. Aligned with UC’s Next Lives Here vision, this initiative advances innovation, digital transformation, and scalable, student-centered education.
ROI:
Personalized academic support, reduced failure rates, and increased student success.
Bearcat Twin: A Dynamic Digital Twin for Student Success and Campus Optimization
Proposer:
DTS
Audience:
University Administration and Students, Faculty and Staff
Description:
Bearcat Twin is an AI-powered initiative to create a real-time digital twin environment at the University of Cincinnati, integrating academic, engagement, and environmental data to drive both student success and institutional efficiency. The initial focus targets first-year STEM retention by modeling academic progress, campus engagement, and residential experiences to deliver timely, personalized interventions. Beyond student support, Bearcat Twin addresses strategic needs identified by Administration & Finance—using real-time insights to inform space utilization, course planning, and infrastructure decisions. Bearcat Twin positions the university as a national leader in applying digital twin technologies to reimagine the future of education and campus operations.
ROI:
The Bearcat Twin initiative represents a transformative leap in how universities understand, support, and optimize the student experience and campus operations. By leveraging a dynamic digital twin model, this initiative integrates academic, financial, social, and environmental data into a unified simulation environment, enabling predictive insights and real-time decision support.
UC Course Assistant – AI Support for Canvas Integration
Proposer:
Jeff Shaffer
Audience:
UC Students
Description:
Developed by the Lindner Applied AI Lab, this prototype connects to Canvas via API to provide students with an interactive AI assistant that retrieves course-specific information—such as syllabi, assignments, and modules—for the current semester. Students can chat with the assistant about any course and download a consolidated Outlook calendar file of all assignment deadlines.
ROI:
Enhances student organization, engagement, and course readiness through a unified interface. With further development—such as deployment on a dedicated server, integration with BearcatGPT or an internal LLM, and data storage via a vector database—this tool can scale to support all students at UC, offering real-time academic assistance and streamlining access to key course materials.
UC Power Plant Optimization and Energy Management using Artificial Intelligence
Proposer:
Sid Thatham (sampatsm)
Audience:
UC Utilities and Operational Leadership
Description:
This initiative applies AI, machine learning, and predictive analytics to optimize UC’s energy infrastructure by analyzing performance data, market trends, and campus energy demands. Current prototypes have already improved SQL-based data access and automated utility billing processes—reducing a monthly manual task from 8 hours to 5 minutes. These efforts demonstrate the potential of AI to increase efficiency, reduce costs, and support sustainable campus operations.
ROI:
The project offers immediate cost and labor savings and lays the groundwork for long-term gains in operational efficiency, sustainability, and data-driven energy management. With strategic investments in technical expertise, high-performance infrastructure, and research partnerships, UC Utilities can scale this model to serve as a national exemplar in AI-powered facilities optimization.
Tools
Bearcat
GPT
Helps you get answers, find inspiration, and be more productive.
Copilot Chat
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Copilot M365
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Adobe Firefly
Helping people expand upon their natural creativity.
LinkedIn Learning AI
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Zoom AI Companion
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Resources
Whether you're a seasoned developer, a curious beginner, or a business leader looking to integrate AI into your operations, you'll find valuable information here. This collection is designed to help you navigate the exciting and rapidly evolving landscape of artificial intelligence. Explore the links and resources below to discover tools, learn new skills, and stay updated on the latest advancements in AI.
Students
Faculty
Staff
AI Tools
Policies
Prompt Library
Generative AI Videos
Generative Al is a rapidly evolving field with the potential to revolutionize many industries. In this
video, we will provide an overview of generative Al, including its history, key concepts, and potential
applications..
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