Ugur Sener

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Ugur Sener

Assistant Professor of Computer Information Systems

Computer Information Systems and Business Analytics

Bio

Dr. Ugur Sener holds a Ph.D. in Business Management from Istanbul Aydin University, an MBA from Beykent University, a B.S. in Industrial Engineering from METU in Ankara. Dr. Sener spent nine years in the steel industry, where he worked in sales engineering and business development roles at Borusan Mannesmann. Dr. Sener’s research focuses on hybrid forecasting, machine learning, and deep learning. His work integrates traditional statistical approaches—such as ARIMA and regression models—with modern artificial intelligence techniques including neural networks and deep learning architectures to improve predictive performance in economic and business contexts. His recent publications appear in peer-reviewed journals such as Computational Economics, Review of Economics, Sage Open and Cogent Economics & Finance. Dr. Sener regularly teaches courses in Business Analytics and Data Science.

Degree

PhD in Business Management

Istanbul Aydin University

MBA

Beykent University

BS in Industrial Engineering

Middle East Technical University

Published Works

  • Sener, U., Terregrossa, J. S. (2025). Contemporary approaches to hybrid forecasting. Computational Economics.
  • Sener, U., Terregrossa, J. S. (2025). The impact of outlier detection algorithms on statistical, machine learning and deep learning forecast models. Review of Economics, 76(1), 1-21. https://doi.org/10.1515/roe-2024-0017.
  • Isler, B., Sener, U., Tokgozlu, A., Aslan, Z., Rene, H. (2025). Spatio-temporal Variation of Solar Irradiance in the Mediterranean Region: A Deep Learning Approach. Sustainability, 17(15)(6696). https://doi.org/10.3390/su17156696.
  • Isler, B., Sener, U., Tokgozlu, A., Aslan, Z. (2025). Prediction of solar energy potential with machine learning and deep learning models. Springer Proceedings in Mathematics & Statistics ((PROMS,volume 482)), https://doi.org/10.1007/978-981-96-3460-6_2
  • Haqi, T., Sener, U. (2024). Enhancing Repurchase Intentions of Online Music Platform Customers for the Middle East. Communications in Computer and Information Science by Springer Nature, https://doi.org/10.1007/978-3-031-72287-5_16
  • Sener, U., Terregrossa, J. S. (2024). A Transcendental LASSO Function for Combining Machine Learning and Statistical Model Forecasts. Sage Open, 14(3), 1-19. https://doi.org/10.1177/21582440241262695.
  • Altinkaya, Z., Adli, A. K., Sener, U. (2023). Türkiye’s Export Analysis with Specific Reference to OECD Countries: 1982Q1 and 2021Q1. Journal of the Human and Social Science Researches, 12(2). https://dergipark.org.tr/en/download/article-file/2937510.
  • Sener, U., Isler, B., Tokgozlu, A., Aslan, Z. (2023). Prediction of Wind Speed by Using Machine Learning. Lecture Notes in Computer Science, Springer Nature, https://doi.org/10.1007/978-3-031-37105-9_6
  • Terregrossa, J. S., Sener, U. (2023). Employing a generalized reduced gradient algorithm method to form combinations of steel price forecasts generated separately by ARIMA-TF and ANN models. Cogent Economics & Finance , 11(2169997). https://doi.org/10.1080/23322039.2023.2169997.
  • Adli, A. K., Sener, U. (2021). Forecasting of the U.S. Steel Prices with LVAR and VEC Models. Business and Economics Research Journal, 14(3). . http://dx.doi.org/10.20409/berj.2021.335.
  • Ukah, O., Sener, U. (2021). Mediation of Online Brand Community On The Relationship Of Social Media And Purchase Intention. International Journal Of Scientific Research And Engineering Development, 4(6), 183-193. .
  • Collins, D. F., Sener, U. (2021). The Impact of Trade Unions On Employee Performance In Cameroon: Teachers’ And Drivers’ Unions Cases. Florya Chronicles Of Political Economy, 7(2), 105-126. https://doi.org/ 10.17932/IAU.FCPE.2015.010/fcpe_v07i2002.
  • Kedra, A., Sener, U. (2020). The Mediating Role of Social Media And Customer Engagement In The Impact Of Digital Content Marketing On Brand Awareness. nternational Research Journal Of Marketing & Economics, 7(11). .

Office Hours

Tuesday 12:15-13:45 and 15:15-16:00
Thursday 12:15-13:45 and 15:15-16:00