athanasioskoutras
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athanasioskoutras

Academic Supervision

Throughout my academic career, I have had the privilege of guiding numerous students through their research journeys, from undergraduate projects to doctoral dissertations. I believe that effective mentorship is essential for nurturing the next generation of researchers and engineers.

Post-Doc Supervision

Dr. Nyi Nyi Tun, Biomedical Engineer

Project Title:* Brain-Computer Interfaces for Silent Speech Decoding Using EEG Signals (2023 - )

Research Focus: The project explores the development of non-invasive BCI systems capable of decoding imagined speech from EEG signals. It combines advanced signal processing, deep learning, and neurotechnology with the goal of enabling communication in individuals with speech impairments.

Current Thesis Supervision

I’m currently supervising the following PhD students:

PhD Candidates

  • Dionysios Anyfantis, "Advanced Deep Learning Techniques for Medical Image Analysis" (2022 - )

    This research focuses on developing novel deep learning architectures for improved breast cancer detection in mammographic images, with particular emphasis on transforming breast density to reveal occult malignancies.

  • Ioannis Vassilakakis, "Creation of an intelligent system for sleep analysis in epileptic patients, for the localization of the epileptogenic zone, through analysis of electroencephalogram brain signals" (2021 - )

    This research focuses on developing an intelligent system using artificial intelligence methods to analyze EEG signals from epileptic patients during sleep. The goal is to assist neurologists in accurately identifying the epileptogenic zone, potentially improving surgical decision-making and patient outcomes. The system aims to serve as an effective decision-support tool for healthcare professionals in epilepsy management.

Master’s Students

Completed Theses

  1. A. Alexopoulos (Medical School, MSc in Life Sciences Informatics)
    “Design and Implementation of a Tool for Detecting Rhythms and Waves in Electroencephalogram”
    Supervisor and Member of the Examination Committee

  2. G. Damaskos (Medical School, MSc in Life Sciences Informatics)
    “Electroencephalographic Study of Sleep Spindles Topography”
    Supervisor and Member of the Examination Committee

  3. G. Patsi (Medical School, MSc in Life Sciences Informatics)
    “Computational Tool for Visualizing Temporal Correlation of Sleep Brain Rhythms”
    Supervisor and Member of the Examination Committee

  4. A. Tsintoni (Medical School, MSc in Life Sciences Informatics)
    “Detection of Slow and Fast Spindles in Sleep Electroencephalogram”
    Supervisor and Member of the Examination Committee

  5. A. Giannakopoulou (Medical School, MSc in Life Sciences Informatics)
    “Electroencephalogram Analysis and Automatic Detection of Sleep Spindles Using Neural Networks”
    Supervisor and Member of the Examination Committee

  6. M. Kalafati (Department of Electrical & Computer Engineering, MSc in Biomedical Engineering)
    “Testing of Motor Coordination in Degenerative Neurological Diseases”
    Member of the Examination Committee

  7. K. Salagianni (Department of Electrical & Computer Engineering, MSc in Biomedical Engineering)
    “Low and High Frequency Oscillations Study of Ictal EEG with Typical Absences in Children”
    Supervisor and Member of the Examination Committee

  8. D. Zarmpoutis (Department of Electrical & Computer Engineering, MSc in Biomedical Engineering) “Electroencephalogram brain computer interface during inner speech”
    Supervisor and Member of the Examination Committee

Undergraduate Students

  • Pappa A., Development and Validation of a Real-Time Multimodal System for Music-Induced Emotion Recognition Based on EEG and Autonomic Responses (Diploma Thesis)
  • Agrafioti S., Time Series Analysis and Machine Learning for Dance Movement Classification Using Sensor Data (Diploma Thesis)
  • Fragkou V., Exploring Physiological Responses to Game Difficulty: An Experimental Study Using a Custom Computer Game and Multi-Modal Biosignal Acquisition (Diploma Thesis)
  • Korres I., Petrakis D. A., Development of a Dynamic Web-Based Platform for Emotion Annotation in Music: A User-Centric Approach to Emotion Analysis (Diploma Thesis)
  • Christopoulou A., Deep Learning for Automated Breast Cancer Detection from Histopathological Images: A Comparative Study of CNN Architectures (Diploma Thesis)
  • Kioulachoglou D., Emotion Recognition from Stress Calls for Emergency Response Prioritization (Diploma Thesis)
  • Papadimitriou E., Deep Learning for Breast Cancer Diagnosis Using Digital Breast Tomosynthesis: Evaluating Network Architectures and Fusion Strategies (Diploma Thesis)
  • Christopoulou A., Explainable AI in Breast Cancer Detection: A Systematic Review of Methods, Challenges, and Clinical Impact (Diploma Thesis)
  • Karadimitropoulou M., EEG-Based Connectivity Analysis for Differentiating Alzheimer’s Disease and Frontotemporal Dementia (Diploma Thesis)
  • Sypsas O. M., HealthGuard: An AI-Enhanced Smart Medication Management and Tracking Application (Diploma Thesis)
  • Vasilikopoulos G., Dynamic Game Design Using Real-Time Biosignal Integration (Diploma Thesis)
  • Kourgiala G., Identification of Major Psychiatric Disorders Using Image Processing and Deep Learning Techniques (Diploma Thesis)

Completed Supervisions

Throughout my academic career, I have successfully supervised over 160 graduate theses and 7 doctoral dissertations across various institutions. These projects have led to numerous publications in international journals and conference proceedings, contributing significantly to their respective fields.

Notable completed supervisions include:

  • Theotokatos I., Exploratory Data Analysis of Different Metal Music Genres from Europe, America, and Asia, 2024 (Diploma Thesis)
  • Mataragkas G., Design and Implementation of an Application for Training Users on BCI Devices Using VR Technologies, 2024 (Diploma Thesis)
  • Milopoulos P., Design and Development of a Serious Game for Training in Brain-Computer Interface Applications, 2024 (Diploma Thesis)
  • Volakis D., Frouzis I., Song Emotion Recognition Using Machine Learning Techniques, 2024 (Diploma Thesis)
  • Dafnis I., Stavridi N., Sentiment Analysis and Recognition on Reddit News Headlines Using the Natural Language Toolkit (NLTK) (2024) (Diploma Thesis)
  • Stathoulas K., Konini C., Design and Development of a Mobile Application for Integrating and Presenting an Internet Radio Station, 2024 (Diploma Thesis)
  • Vaskantiras A., Computer-Aided Diagnosis of Breast Cancer Using Deep Learning, 2024 (Diploma Thesis)

IEEE Mentorship Programs

Beyond formal academic supervision, I’m actively involved in mentorship through IEEE programs:

  • IEEE EMBS Student Mentoring Program (2024)
    Currently mentoring one student through their research in biomedical engineering, providing guidance on methodology, literature review, and career planning.

  • IEEE EMBS Student Mentoring Program (2023)
    Currently mentoring one student through their research in biomedical engineering, providing guidance on methodology, literature review, and career planning.

  • IEEE EMBS Student Mentoring Program (2022)
    Mentored three students through their research journey, focusing on signal processing applications in healthcare.

  • IEEE EMBS Student Mentoring Program (2021)
    Guided two students in biomedical engineering projects, helping them develop research skills and professional networks.

  • IEEE ME-UYR Mentoring Program (2022)
    Participated in the IEEE Mentoring Experiences for Underrepresented Young Researchers Program, providing support to researchers from underrepresented countries.

Supervision Philosophy

My approach to supervision is guided by several core principles:

  • Independence with Support: I encourage students to develop their own research ideas while providing the necessary guidance and resources.
  • Interdisciplinary Thinking: I emphasize the importance of drawing connections between different fields and methodologies.
  • Research Integrity: I instill strong ethical standards and rigorous methodological approaches.
  • Professional Development: Beyond research skills, I focus on helping students develop communication, networking, and career management abilities.

Prospective Students

If you’re interested in pursuing a thesis or dissertation under my supervision, please feel free to contact me to discuss potential research topics. I’m particularly interested in supervising projects related to:

  • Signal processing and machine learning applications in healthcare
  • Brain-computer interfaces and neural engineering
  • Digital audio and music information retrieval
  • Pattern recognition in biomedical signals
  • Medical Imaging

Contact: koutras@uop.gr