Ömer Muhammet Soysa has earned BS and MSc degrees in Electronics Engineering and a PhD in Computer Science. His area of research is Data Science, with a focus on the application of Machine Learning to Spatiotemporal Signals, such as Computational Neuroscience. His research interests are the Theory and Applications of Machine Learning, Computer Vision, and Data Mining; application-wise, his interests are Computational Neuroscience, Computational Biomedicine, Human–Computer Interaction, and Computer Aided Detection & Diagnosis Systems. He has research experience in Computer Vision, Machine Learning, Pattern Recognition, Medical Image Processing, Computational Neuroscience, Geographic Information Systems, Computer-Aided Detection and Diagnosis, Content-Based Image Retrieval, Shape Representation, Image Registration, Data Mining, Neural Networks, Decision Trees, Association Rule Mining, Visual Data Exploration by Parallel Coordinates, Wavelets, Database Systems, Statistical Data Analysis, Traffic Accident Data Analysis, Parallel Coordinate Visualization For Microarray Data, Finite Difference/ Element Methods, Fuzzy Logic and Control, and Heat Transfer Simulation.