Mehmet Fatih Karakaş

MATLAB

I actively use MATLAB for data analysis, signal processing, and algorithm development. It serves as one of my core tools for implementing and validating research models in biomedical engineering.

R Programming

R is one of the main tools I use for statistical analysis and experimental validation. It supports my workflow in hypothesis testing, visualization, and reproducible data processing.

Python

Python is central to my daily research for machine learning, deep learning, and automation tasks. I use it extensively for data preprocessing, model training, and performance evaluation.

Signal and Image Processing

I work on biomedical signal and image processing to extract meaningful information from complex datasets. My focus is on EEG analysis, feature extraction, and disease classification.

Metaheuristics

I apply metaheuristic optimization techniques to improve model performance and parameter tuning. These methods help solve complex, nonlinear problems in signal analysis and machine learning.

Deep Learning

Deep learning is a key component of my research for decoding brain activity of EEG signals. I use CNN-based and hybrid models to explore pattern recognition and cognitive decoding.

Optimization

I employ optimization algorithms for feature selection, model refinement, and classifier improvement. They are integral to achieving reliable and efficient computational models.

Medical Device Development

I’m involved in the development of medical devices that combine hardware and software for diagnostic and monitoring purposes. My work emphasizes functionality, reliability, and patient safety.

Project Management

I manage multidisciplinary R&D projects from concept to prototype. My experience includes planning, execution, and coordination of funded research and industrial collaborations.

Mehmet Fatih Karakaş

Biomedical Engineer (PhD)

Research Areas