AI Research and Innovation

FSU faculty and staff have been very active in research and teaching innovation related to AI. The Chesnutt Library maintains a special topics page of faculty publications on artificial intelligence which can be found by clicking here. The following is a partial list of individuals and, in some cases, a partial list of their contributions to AI research and innovation. Click on names for more information.

Dr. Sambit Bhattacharya, Professor of Computer Science, Department of Mathematics and Computer Science, Lloyd College of Health, Science, and Technology

  • Panelist, Getting Started with AI in the Classroom, Office of Faculty Development, February 2025.
  • Wilkerson, M., Vincent, G., Hasnain, Z., Bhattacharya, S., & Dunkel, E. (2024). Benchmarking ResNet50 for Image Classification on Diverse Hardware Platforms. The ITEA Journal of Test and Evaluation, 45(3).
  • Bhattacharya, S., Brown, T., Wilkerson, M., Blanton, B. (2024). Pragmatic and ML Approaches to Backfilling Missing Data within Time Series Datasets. Accepted for publication in IEEE Explore under the 2024 IEEE International Conference on Machine Learning Applications (ICMLA).
  • Bhattacharya, S., Czejdo, B., Zulli, R. A., & Smith, A. A. (2024, May). Enhancing AI Education at an MSI: A Design-Based Research Approach. In Proceedings of the AAAI Symposium Series (Vol. 3, No. 1, pp. 467-472).
  • Bhattacharya, S., Czejdo, B. (2023). Trustworthiness of Artificial Intelligence: Teaching Factors that Influence AI-supported Decision Making. Journal of Computing Sciences in Colleges, 38.6 (2023): 85-94.
  • Greis, N. P., Nogueira, M. L., Bhattacharya, S., Spooner, C., & Schmitz, T. (2022). Stability modeling for chatter avoidance in self-aware machining: an application of physics-guided machine learning. Journal of Intelligent Manufacturing, 1-27.
  • Czejdo, C., & Bhattacharya, S. (2022). Increasing Accessibility of Language Models with Multi-stage Information Extraction. Journal of Advances in Information Technology Vol, 13(2).
  • Bhattacharya, S., Czejdo, B., & Milanov, V. (2021). Infusion of machine learning concepts and skills: a workshop review. Journal of Computing Sciences in Colleges, 36(6), 55-65.
  • Claiborne, J., Brown, T., Rodriguez, P., & Bhattacharya, S. (2024, March). Enhancing Rare Object Detection in AI: Leveraging Synthetic Data for Improved Model Training. In SoutheastCon 2024(pp. 56-60). IEEE.
  • PI, “A data analytics certificate for non-computing majors”, National Science Foundation (NSF), $403,198. Funded from July 1st, 2023, to June 30th, 2027. Award Number: 2245960.
  • PI, “Data and AI Literacy for National Security”, US Department of Defense, Office of Naval Research (ONR), $598,707. Funded from 2023 to 2026. Award Number: N00014-23-1-2246.
  • PI, “Building an FSU-JPL Partnership to Advance Science Productivity through Applications of Deep Learning”, National Aeronautics and Space Administration (NASA), Science Mission Directorate (SMD), $299,702. Funded from August 1st, 2024, to July 31st, 2026. Award Number: 80NSSC24K1618.
  • PI, “Planning: Research in Generative Artificial Intelligence for Enhanced Analysis in the US Intelligence Community”, National Science Foundation (NSF), $99,955. Funded from September 1st, 2023 to August 31st, 2024. Award Number: 2332095.
  • Co-PI,  "AI and ML Consortium to Advance Health Equality and Researcher Diversity," $100,000 grant from the Artificial Intelligence (AI) and Machine Learning (ML) Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) to increase research capacity in AI applied to Health Equity. 2023.

Dr. John Brooks, Associate Professor of History, Department of Intelligence Studies, Geospatial Science, Political Science, and History

  • Panelist, Getting Started with AI in the Classroom, Office of Faculty Development, February 2025

Dr. Jennifer Bushelle-Edghill, Associate Professor and Chair, Department of Accounting, Finance, Healthcare Administration, Information Systems and Business Analytics, Broadwell College of Business and Economics

  • Zhou, Jiahua & Bushelle-Edghill, Jennifer (2023). A Proposal to Develop a Risk Analytics Course and a Computer-Supported Collaborative Learning Platform to Scaffold Data-driven Risk Management. Spencer Education Foundation: Spencer_202311. Funding Source: Private, Spencer Foundation. Fund Amount: $19,000.
  • Zhou, Jiahua, Bushelle-Edghill, Jennifer & McGee, Robert (2022). Collaboratory Project ID: collab_377. Funding Source: State, non-reverting funds. Project title: Dancing Around Emerging Data and Analytics: Using a Novel Decision Intelligence Platform to Integrate Teaching Data Analytics and Offering Data-driven Solution Consultancy for Small Businesses. Fund Amount: $50,000.

Dr. Bogdan Czedo, Professor of Science, Department of Mathematics and Computer Science

  • Bhattacharya, S., Czejdo, B., Zulli, R. A., & Smith, A. A. (2024, May). Enhancing AI Education at an MSI: A Design-Based Research Approach. In Proceedings of the AAAI Symposium Series(Vol. 3, No. 1, pp. 467-472).
  • Bhattacharya, S., Czejdo, B. (2023). Trustworthiness of Artificial Intelligence: Teaching Factors that Influence AI-supported Decision Making. Journal of Computing Sciences in Colleges, 38.6 (2023): 85-94.
  • Czejdo, C., & Bhattacharya, S. (2022). Increasing Accessibility of Language Models with Multi-stage Information Extraction. Journal of Advances in Information Technology Vol, 13(2).
  • Bhattacharya, S., Czejdo, B., & Milanov, V. (2021). Infusion of machine learning concepts and skills: a workshop review. Journal of Computing Sciences in Colleges, 36(6), 55-65.
  • Czejdo, C., & Bhattacharya, S. (2021, August). Support for Interview Preparation with Deep Learning Based Language Model. In 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI) (pp. 16-20). IEEE.
  • Czejdo, C., & Bhattacharya, S. (2021, March). Augmenting Case Based Learning with Dynamic Language Models. In SoutheastCon 2021 (pp. 1-4). IEEE.

Mr. Tristan Daniels, Online Navigator, Office of Faculty Development 

  • Developer, AI in Academia: Drafting Policies, 2024
  • Developer, AI in Academia: Designing Assignments, 2024
  • Developer, AI in Academia: Using Chatbots, 2024

Dr. Heather Griffiths, Associate Professor of Sociology, Department of Sociology and Interdisciplinary Studies

  • Member, UNC System AI Task Force
  • Presenter, "Ensuring Academic Integrity in the Age of Artificial Intelligence: A Data-Driven Approach," NC Sociological Association, February 2025

Dr. Lenora Hayes Associate Professor of Spanish, Department of Communication and World Languages.

  • Member, UNC System AI Task Force
  • Panelist, Getting Started with AI in the Classroom, Office of Faculty Development, February 2025

Prof. Soni Martin, Professor of Art, Department of Performing and Fine Arts

  • Panelist, Getting Started with AI in the Classroom, Office of Faculty Development, February 2025

Dr. Robert McGee, Professor of Accounting, Graduate and Professional Studies, Broadwell College of Business and Economics

Dr. Valentin Milanov, Associate Professor of Mathematics, Department of Mathematics and Computer Science

  • Bhattacharya, S., Czejdo, B., & Milanov, V. (2021). Infusion of machine learning concepts and skills: a workshop review. Journal of Computing Sciences in Colleges, 36(6), 55-65.
  • PI, “Data and AI Literacy for National Security”, US Department of Defense, Office of Naval Research (ONR) for the Department of Navy (DON) STEM Education and Workforce Program, $598,707 with Valentin Milanov as Co-PI. Funded from 2023 to 2026. Award Number: N00014-23-1-2246.

Dr. Chekad Sarami, Professor of Mathematics and Computer Science, Department of Mathematics and Computer Science, Lloyd College of Health, Science, and Technology

  • "Retrieval-Augmented Generation (RAG): The Future of AI-Powered Knoweldge," Henry Eldridge Department of Mathematics and Computer Science Seminar Series, February 2025.

Dr. Zahra Shekarkhar, Associate Professor of Criminal Justice, Department of Criminal Justice

  • Panelist, Getting Started with AI in the Classroom, Office of Faculty Development, February 2025.

Dr. Alexander Umantsev, Professor of Physics, Department of Chemistry, Physics, and Materials Science

  • Umantsev, Alexander, "Dr. Alexander Umantsev - Design on Novel Materials Human Intelligence vs Artificial One October 16 2024" (2024). Faculty Authors Series at Chesnutt Library.

Dr. Longfei Wu, Associate Professor of Computer Science, Department of Mathematics and Computer Science

  • Yang, Wenti; Guan, Zhitao; Wu, Longfei; and He, Zhaoyang, "A Secure Neural Network Inference Framework for Intelligent Connected Vehicles" (2024)
  • Yang, Wenti; Wang, Xiaodong; Guan, Zhitao; Wu, Longfei; Du, Xiaojiang; and Guizani, Mohsen, "SecureSL: A Privacy-preserving Vertical Cooperative Learning Scheme for Web 3.0" (2023). 

Dr. Jiahua Zhou, Assistant Professor of Accounting, Department of Accounting, Finance, Healthcare Administration, Information Systems and Business Analytics, Broadwell College of Business and Economics.

  • Zhou, J. (2024). Empowering Internal Control: A Case Study in Leveraging Data and Technologies. Journal of Accounting, Ethics & Public Policy, JAEPP, 25(2), 26. https://doi.org/10.60154/jaepp.2024.v25n2p26. 
  • Zhou, Jiahua, (2022). The Ethical Implementation of Algorithm-based Decision-making: An Analytical Roadmap to Examine Accountability and Responsibility of Designing and Implementing Audit Data Analytics, Journal of Accounting, Ethics & Public Policy, 23 (2), 309-351 (cited by 1). DOI: https://www.jaepp.org/index.php/jaepp/article/view/44.
  • Zhou, J. (2024). Agentic AI: Pioneering the Next Breakthrough in Smart FinTech Development, FSU FinTech Conference, Fayetteville, NC (October 11-12)
  • Zhou, J. & McGee, R. (2023). A Novel Pedagogic Solution to Integrate Real-world Questions, Data-driven Solutions, and Business Domain Knowledge, Presentation at the 2023 American Accounting Association Annual Conference, Denver CL (August 5-9, 2023).
  • Zhou, Jiahua; Issa, Hussein; Brown, Helen. IT-supported Internal Control as a Sociomaterial Process: A Framework to Harness IT Potentials. Presented at the 2018 American Accounting Association Annual Conference in Washington, DC.
  • Zhou, Jiahua & Bushelle-Edghill, Jennifer (2023). A Proposal to Develop a Risk Analytics Course and a Computer-Supported Collaborative Learning Platform to Scaffold Data-driven Risk Management. Spencer Education Foundation: Spencer_202311. Funding Source: Private, Spencer Foundation. Fund Amount: $19,000. Project Title: Risk Analytics and Smart Monitoring System Design.
  • Zhou, Jiahua, Bushelle-Edghill, Jennifer & McGee, Robert (2022). Collaboratory Project ID: collab_377. Funding Source: State, non-reverting funds. Project title: Dancing Around Emerging Data and Analytics: Using a Novel Decision Intelligence Platform to Integrate Teaching Data Analytics and Offering Data-driven Solution Consultancy for Small Businesses. Fund Amount: $50,000.
  • Zhou, Jiahua, Faculty Coach. The second award of the FSU FinTech competition, Fayetteville, NC (October 11-12, 2024). Project: A Design of a FinTech—An Investment Alert System Based On Peer Group Investment Strategy. Team members: Jazmin Daniel, Bina Patel, Julian Ravilious, Martin Sanchez.