Ebisa Wollega

Dr. Ebisa Wollega is an associate professor of industrial engineering at Florida Polytechnic University. He joined Florida Poly in the fall of 2024 following a position at Colorado State University Pueblo, where he taught industrial engineering courses, served as the director of the undergraduate industrial engineering program, and mentored graduate and undergraduate student research for nine years.

Wollega researches the areas of artificial intelligence and large-scale optimization for efficient planning of scarce resources, as well as engineering education. He has documented his work in top-tier journals and conference proceedings, such as in the Neural Information Processing Systems and Applied Energy. In addition, he demonstrated exemplary leadership during his five-year tenure as an officer, including as a division chair for the Industrial Engineering Division of the American Society for Engineering Education. Wollega has been recognized for excellence in research and teaching awards more than half a dozen times.

Awards and Honors

• Students’ Choice Award recipient (2020) and nominee (2021) by the Associated Students’ Government, Colorado State University Pueblo.
• Best Energy Track Paper Award, 5th North American IEOM Detroit Conference 2020.
• Excellence in Teaching/Student Learning Award (2019), Colorado State University Pueblo.
• Four-time Outstanding Teaching Assistant Award (2010, 2011, 2012, 2013), School of Industrial and Systems Engineering, University of Oklahoma.
• Engineering Student Research Performance Award (2013), second place, University of Oklahoma.

Education

• Ph.D. in Industrial Engineering, University of Oklahoma, 2015
• M.S. in Industrial Engineering, University of Oklahoma, 2010
• B.S. in Industrial Engineering, Mekelle University, 2005

Expertise

• Machine learning
• Optimization
• Simulation
• Energy planning
• Engineering education

Professional Activities

• Member, Institute for Operations Research and Management Sciences (INFORMS), 2011-current.
• Officer and Member, American Society for Engineering Education (ASEE), 2015-current.

Select Publications

• Wollega, E., Braddock, M., and Bosman, L. (2024). Awareness of Feature Importance in Artificial Intelligence Algorithms. Proceedings of the 2024 American Society of Engineering Education (ASEE) Annual Conference.
• Soto, E., Wollega, E., Vizcarrondo-Ortega, A., Hernandez-Guzman, A., and Bosman, L. (2024). Reduction in Emissions by Massive Solar Plant Integration in the US Power Grid. Energies, 17 (7). https://doi.org/10.3390/en17071611
• Soto, E., Bosman, L., Wollega, E.D., and Leon-Salas, W. (2022). Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange. Applied Energy, 4, 118562.
• Ramirez-Vergara, J., Bosman, L. B., Leon-Salas, W. D., and Wollega, E. (2022). Predicting on-site solar energy generation using off-site weather stations and deep neural networks. International Journal of Energy and Environmental Engineering, 1-13.
• Soto, E. A., Bosman, L. B., Wollega, E., and Leon-Salas, W. D. (2022). Analysis of Grid Disturbances Caused by Massive Integration of Utility Level Solar Power Systems. Eng, 3(2), 236-253.
• Ramirez-Vergara, J., Bosman, L.B., Wollega, E., and Leon-Salas, W.D. (2022). Review of forecasting methods to support photovoltaic predictive maintenance. Cleaner Engineering and Technology, 100460.
• Ramirez-Vergara, J., Bosman, L.B., Leon-Salas, W.D., and Wollega, E. (2021). Ambient Temperature and Solar Irradiance Forecasting Prediction Horizon Sensitivity Analysis. Machine Learning with Applications, 6, 100128.
• Soto, E., Bosman, L., Wollega, E.D., and Leon-Salas, W. (2020). Peer-to-Peer Energy Trading: A Review of the Literature. Applied Energy, 116268.
• Ghosh, S., Squillante, M. S., and Wollega, E. D. (2021). Efficient Generalization with Distributionally Robust Learning. Advances in Neural Information Processing Systems 34 (NeurIPS 2021).
• Wollega, E. D., Ghosh, S., and Squillante, M. S. (2016). Bi-level stochastic approximation for joint optimization of hydroelectric dispatch and spot-market operations. In Winter Simulation Conference (WSC), 2016 (pp. 1769-1780).