Mustafa Tosun

Assoc. Prof. Dr. Mustafa Tosun is a faculty member at Simav Faculty of Technology, Dumlupinar University, where he serves in the Department of Electrical-Electronic Engineering. With a PhD in Electrical and Electronic Engineering from Sakarya University, he has established himself as a researcher specializing in the application of artificial intelligence to biomedical signal processing.

His educational background includes a Bachelor's degree in Electrical-Electronic Engineering from Selcuk University (1988-1992), followed by a Master's degree from Dumlupinar University (1994-1997), and ultimately his doctorate from Sakarya University (1998-2004). Prior to his current academic position, he gained valuable industry experience working at Turk Telekom Inc. from 1999-2006 in the Information Networks Directorate.

Professor Tosun's research primarily focuses on Artificial Intelligence applications in biomedical engineering, with special emphasis on EEG signal processing using deep learning techniques. His work spans multiple domains including Brain Computer Interfaces, cognitive workload measurement, pain threshold estimation, and neurological disorder classification. He has published extensively in these areas, with a notable increase in publications during 2020-2022.

His recent publications demonstrate a strong trend toward applying advanced machine learning techniques to solve complex biomedical problems, particularly in EEG signal analysis and classification. The research shows consistent focus on improving signal processing methods, artifact removal, and developing more accurate classification systems for various medical applications.

As an educator, Professor Tosun teaches a wide range of courses including:

• Fundamentals of Biomedical Engineering
• Fuzzy Logic
• Introduction to Electrical and Electronics Engineering
• Electronics I & II
• Artificial Neural Networks
• Neural Networks and Deep Learning

He actively supervises graduate students, with numerous ongoing and completed theses in areas such as EEG-based psychiatric disease investigation, brain-computer interfaces, and pain classification systems. His research group appears well-established with multiple concurrent projects addressing different aspects of AI applications in biomedical engineering.