Selchuk C. joined the Suleyman Demirel University (SDU) in Kazakhstan in 2021 as a head of Information System department. Presently he works as lecturer with title of an assistant professor. His research interests lie in machine learning, ensemble learning, reinforcement learning, deep learning, data warehousing and data mining, data science and big data.

PHD in Ensemble Learning (2015). Engineering and Information Technologies Faculty (in English). International Burch University, Sarajevo, Bosnia and Herzegovina.
Master’s Degree in Machine Learning (2011). Engineering and Information Technologies Faculty (in English). International Burch University, Sarajevo, Bosnia and Herzegovina.
Bachelor’s degree in Information Technologies in English (1997), Technical Education Faculty, Marmara University, Istanbul, Turkey.
English Prep School (1992). Marmara University, Istanbul, Turkey.

Certificate for Solar Consultant and Trainer for Photovoltaics systems from DGS – International Solar Energy Society, German (2021).

CSS 615 - Master level - Big Data Analytics
CSS 516 - Master level - Research Tools and Methods

Cankurt, S., Subaşi A. (2016). Tourism demand modelling and forecasting using data mining techniques in multivariate time series: A case study in Turkey. Turkish Journal of Electrical Engineering & Computer Sciences, the Scientific and Technological Research Council of Turkey – TÜBİTAK, 24, 3388 – 3404, doi: 10.3906 / elk-1311-134. (SCI Exp. Indexed)
Cankurt, S. & Subaşi A. (2015). Developing tourism demand forecasting models using machine learning techniques with trend, seasonal, and cyclic components. Balkan Journal of Electrical & Computer Engineering, 3(1), 42-49.
Tourism Demand Forecasting Using Stacking Ensemble Model with Adaptive Fuzzy Combiner, S. Cankurt, A. Subasi Soft Computing (2022). (SCI Indexed)

Cankurt, S. & Subaşi A. (2012). Comparison of linear regression and neural network models forecasting tourist arrivals to Turkey. Proceeding of 3rd International Symposium on Sustainable Development, ISSD. Sarajevo, Bosnia and Herzegovina.
Cankurt, S. (2016). Tourism Demand Forecasting using Ensembles of Regression Trees. Proceeding of IEEE 8th International Conference on Intelligent Systems, IS’16 (pp.702-708). Sofia, Bulgaria, doi: 10.1109/IS.2016.7737388 (Scopus Index)
Yıldırım M., Aksu C., Cankurt S. (2016). Performance evaluation of MIMO receivers in two-way decode and forward relaying. Proceeding of 2nd International Engineering Conference on Developments in Civil & Computer Engineering Applications, IEC2016 (pp. 154-161), ISSN 2409 – 6997 (Print). Erbil, Iraq.
Cankurt S.&Yasin M. (2018). Modelling energy demand forecasting using neural networks with univariate time series. Proceeding of 4th International Engineering Conference on Developments in Civil & Computer Engineering Applications, IEC2018 (pp.341-349). Erbil, Iraq, doi: 10.23918/iec2018.26
Subasi A., Cankurt S.(2019) Prediction of default payment of credit card clients using Data Mining Techniques, Proceeding of IEEE International Engineering Conference (IEC2019) (pp.115-120) doi: 10.1109/IEC47844.2019.8950597 (Scopus Index)
MS Gaso, S Cankurt, A Subasi (2021) Electromyography Signal Classification Using Deep Learning. Proceeding of IEEE 16th International Conference on Electronics doi: 10.1109/ICECCO53203.2021.9663803 (Scopus Index)

Machine learning, ensemble learning, reinforcement learning, deep learning, data warehousing and data mining, data science and big data