Summary
Christos Ferles is a laboratory teaching staff and researcher with eight years of professional experience and a PhD-level background in machine learning and AI, currently focused on hybridizing deep learning with unsupervised models for radar signal pattern recognition and human gene/cell analysis. He has led applied projects from concept to embedded prototype—most notably a real-time, non-intrusive sleep-apnea screening device—and has driven research on self-organizing convolutional maps that cluster unlabeled image data. His work spans deep learning (CNNs, autoencoders), self-organizing maps, HMMs and neuro-fuzzy systems, and includes postdoctoral applied research on cancer detection from gene expression. Based in Athens, he combines academic publication track record with hands-on embedded and biomedical ML development, and has a history of translating theoretical methods into practical diagnostic tools. An uncommon strength is his cross-domain fluency: blending signal-processing expertise for radar with genomics-informed ML for medical diagnostics.
8 years of coding experience
11 years of employment as a software developer
Postdoctoral Research in Scientific Computing, Informatics and Visualization, field of study: Machine Learning and Artificial Intelligence, Postdoctoral Research in Scientific Computing, Informatics and Visualization, field of study: Machine Learning and Artificial Intelligence at University of Cape Town
Ph.D. in Information Technology and Computer Science, field of study: Machine Learning and Artificial Intelligence, Ph.D. in Information Technology and Computer Science, field of study: Machine Learning and Artificial Intelligence at National Technical University of Athens