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
- Maniadi Evangelia, M.Sc.
- Tsichlaki Stella, M.Sc.
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“