2810379750 bmi@hmu.gr


Head of the BMI Lab

  • Tsiknakis Manolis, Ph.D., Visiting Research Professor, Computational BioMedicine Lab, FORTH

Collaborating Researchers

  • Koumakis Lefteris, Ph.D., Collaborating Researcher, Computational BioMedicine Lab, FORTH
  • Marias Konstantinos, Ph.D., Collaborating Researcher, Head of the Computational BioMedicine Lab, FORTH

Software Engineers

Doctoral Students

  • Chatzaki Roula, M.Sc.
    • Research topic: “A multimodal approach for the assessment of mental stress based on the analysis of physiological signals”
  • Chatzimina Maria, M.Sc.
    • Research topic: “Conversational agents as a new diagnostic tool: a proof-of-concept study in the field of palliative care
  • Gkikas Stefanos, M.Sc.
    • Research topic: “A Pain Assessment Framework based on multimodal data and Deep Machine Learning methods”

Postgraduate students

  • Pavlidou Elsa, B. Sc.
    • Thesis: “Multimodal pain intensity assessment based on physiological biosignals
    • Description: The purpose of the thesis is to develop computational, predictive models and conduct validation experiments by using multimodal physiological biosignals such as Electrocardiogram, Electromyogram and Galvanic Skin Response.

Undergraduate students

  • Adam Giannis
    • Thesis: “Development of an app for measuring Heart Rate and Heart Rate Variability using wearable sensors
  • Garganourakis Vasileios, Ph. D., Phycisian
    • Thesis: “Emotion detection through video and biosignal analysis
  • Garefalaki Magdalini
    • Thesis: “Pain detection through video analysis and biosignal analysis
  • Gialelaki Irini
    • Thesis: “Design and development of an embodied conversational agent (ECA) and its application for improving the well-being of cancer patients
  • Dogramatzaki Zaxarenia
    • Thesis: “Assessment of emotional state through video and biosignal analysis”
  • Droumalia Foteini
    • Thesis: “Gene expression and gene regulatory network analysis with statistical methods and machine learning algorithms
  • Katsanevakis Aris
    • Thesis: “Usage of deep learning techniques for the development of predictive models for future disease risks by analyzing data from patients’ electronic health records
  • Oikonomou Nikos
    • Thesis: “Multi-omics analysis of genomic data for the classification of Glioblastoma”
  • Papadaki Maria
    • Thesis: “Analysis of freezing of gait (FOG) using smart wearable insoles
  • Stavrakakis Marinos
    • Thesis: “Development of an app for assessing the user’s cognitive ability
  • Strataki Despina
    • Thesis: “Architectures and platforms for connected smart objects