Contact Information
Bio
Dr. Jesse Eickholt is a Distinguished Visting Professor at the U.S. Air Force Academy and a Professor of Computer Science at Central Michigan University. He has been teaching courses in computer science, machine learning and artificial intelligence at Central Michigan University since 2013. Prior to starting at Central Michigan University, he taught at Westminster College and the University of Missouri, where he obtained his doctorate in 2013. He is an active member of the Association for Computing Machinery (ACM) and volunteers as a commissioner for the Computing Accreditation Commission of ABET.
Dr. Eickholt’s research focuses on applications of machine learning and educational technology. He has published in numerous journals including IEEE Transactions on Education, ACS Applied Material Interfaces, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and ICES Journal of Marine Science and presented his work at venues such as the ACM SIGCSE Technical Symposium. His current research interests are selective fish passage and large language models for computer science education.
Education
Doctor of Philosophy, Computer Science, University of Missouri
Doctor of Educational Technology, Central Michigan University
Master of Science, Applied Mathematics, University of Missouri
Master of Arts, Education: Curriculum and Instruction, Central Michigan University
Bachelor of Philosophical and Theological Studies, Conception Seminary College
Bachelor of Science, summa cum laude and honors scholar, Computer Science & Mathematics, University of Missouri
Professional Experience
Distinguished Visiting Professor, Department of Computer and Cyber Sciences, U.S. Air Force Academy (AY 2025-26)
Professor, Department of Computer Science, Central Michigan University (2020 – present)
Sponsored Research Affiliate, School of Information, University of Michigan (2017 – 2020)
Associate Professor, Department of Computer Science, Central Michigan University (2017 – 2020)
Assistant Professor, Department of Computer Science, Central Michigan University (2013 – 2017)
National Library of Medicine Biomedical Informatics Pre-doctoral Fellowship, University of Missouri (2011-2013)
Publications
J. Gregory, S. Miehls, J. Eickholt, D. Zielinksi. (2025) A Real-Time Fish Detection System for Partially Dewatered Fish to Support Selective Fish Passage. Sensors. 25(4), 1022, 10.3390/s25041022.
J. Eickholt, D. Kelly, J. Bryan, S. Miehls, D. Zielinski. (2020) Advancements Towards Selective Barrier Passage by Automatic Species Identification: Applications of Deep Convolutional Neural Networks on Images of Dewatered Fish. ICES Journal of Marine Science. 10.1093/icesjms/fsaa150
J. Eickholt, M.R. Johnson, P. Seeling. (2020) Practical Active Learning Stations to Transform Existing Learning Environments into Flexible, Active Learning Classrooms. IEEE Transactions on Education, 64, 2. 10.1109/TE.2020.3009919
R. Joshi, J. Eickholt, L. Li, M. Fornari, V. Barone, J. Peralta. (2019) Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries. ACS Applied Material Interfaces. 11, 20 https://doi.org/10.1021/acsami.9b04933.
M. Spencer, J. Eickholt, and J. Cheng. (2014) A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. DOI:10.1109/TCBB.2014.2343960.