Panagiotis Liaparions, Professor, Department of Biomedical Engineering, University of West Attica, Greece, liapkin@uniwa.gr

Stratos David, Associate Professor (elected), Department of Biomedical Engineering, University of West Attica, Greece, sdavid@uniwa.gr

Katerina Skouroliakou, Professor, Department of Biomedical Engineering, University of West Attica, Greece, kskourol@uniwa.gr

Manolis Athanasiadis, Assistant Professor, Department of Biomedical Engineering, University of West Attica, Greece, mathan@uniwa.gr

Evanglia Pantatosaki, Assistant Professor, Department of Biomedical Engineering, University of West Attica, Greece, epantatosaki@uniwa.gr

Aikaterini Vantoni, Assistant Professor,  Department of History and Philosophy of Science, National and Kapodistrian University of Athens, avlantoni@uniwa.gr 

Upon successful completion of the course, students will be able to:

1. Acquire comprehensive and specialized knowledge of the scientific field of biomedical engineering, identifying and analyzing in depth its key areas.
2. Critically evaluate the roles and applications of biomedical engineering in the modern professional and research environment, anticipating developments and emerging trends.
3. Design and implement advanced research studies by applying sophisticated methods of data collection and analysis, using specialized statistical and computational tools.
4. Analyze and resolve complex ethical issues in research and professional practice, proposing evidence-based solutions consistent with current regulatory and legal frameworks.
5. Prepare and present complete scientific papers and research proposals, applying advanced documentation techniques, and effectively communicate results to both specialized and non-specialized audiences.
6. Apply advanced research skills for the interpretation and evaluation of scientific data.
7. Demonstrate in-depth understanding of the ethical challenges posed by continuous technological progress, formulating strategies for responsible professional practice in the field of biomedical engineering.

Dr. Mimika Thomaidou, Hellenic Pasteur Institute, Greece

dthomaidou@uniwa.gr

Dr. George Panayotou, BSRC Alexander Fleming, Greece

g.panayotou@fleming.gr

• The course will provide a concise description of biological concepts and functions including exchange of matter and energy flow in the cell, structure and function of proteins and nucleic acids, cell membranes, basic principles of gene regulation, structure and function of viruses. A more analytical and detailed description will be provided regarding methodologies and tools of biotechnology applied in the field of medicine. These will include but are not limited to, recombinant DNA technology, stem cell biology and proteomics. 
• The acquired knowledge can be applied to the design of innovative diagnostic tools, drugs and therapies capable of curing diseases and improving human health.

The purpose of the course is to study the fundamental structure of diagnostic imaging systems using non-ionizing radiation. The course analyzes the main components of Ultrasound systems and Magnetic Resonance Imaging (MRI) systems.

In addition, fundamental concepts will be examined, including:

• Physical principles of ultrasound generation and propagation
• Physical principles of magnetic resonance and superconductivity
• Imaging techniques and instrumentation of clinical imaging systems

The course includes individual assignments and presentations on topics related to modern and combined imaging methods using non-ionizing radiation.

Upon completion of the course, students will:

1. Gain knowledge of the basic physical principles of ultrasound, magnetic resonance, and the interactions of wave attenuation with matter.
2. Acquire a comprehensive understanding of the scientific field of diagnostic imaging systems using non-ionizing radiation.
3. Develop the ability to describe and distinguish the individual components (block diagrams) that make up a complete imaging system.
4. Understand the operating principles in order to carry out comparative evaluations among different medical imaging systems.
5. Develop research skills through literature review and project presentations.

George Loudos, Co-Founder, CEO BIOEMTECH
george@bioemtech.com

Invited biomedical engineers from the industry sector

• Service, calibration, repair and quality control of biomedical equipment 
• Sales, promotion and marketing of biomedical products 
• Application specialist 
• Clinical and hospital engineering 
• Researcher in biomedical engineering 
• Education and certification in biomedical engineering 
• Career prospects in biomedical engineering 

Upon successful completion of the course, students will be able to:

1. Fully understand the roles and applications of biomedical engineering in the job market, recognizing different career paths and future prospects.
2. Identify and analyze the interdisciplinary nature of biomedical engineering, understanding its interaction with medicine, technology, and other related fields.
3. Critically evaluate current trends, challenges, and developments in the field, proposing strategies for professional adaptation and growth.

The learning outcomes of the course are designed to provide students with a fundamental understanding of statistical concepts and methods. These outcomes aim to equip students with the necessary skills for data analysis and interpretation, evidence-based decision-making, and the application of statistical techniques. Upon completion, students will be able to:

1. Develop a solid understanding of fundamental statistical concepts, including probability, hypothesis testing, confidence intervals, and basic descriptive statistics.
2. Summarize and present data effectively using descriptive statistics such as measures of central tendency, variability, and graphical representations.
3. Understand the principles of inferential statistics, including hypothesis testing, p-values, and interpretation of statistical significance.
4. Explore basic probability distributions.
5. Gain practical experience with statistical analysis tools commonly used in the field, such as the R programming language.
6. Develop critical thinking skills to analyze real-world problems and apply appropriate statistical methods to solve them.
7. Create effective data visualizations to communicate statistical findings using charts, graphs, and other graphical representations.
8. Communicate statistical results clearly and concisely, both in written reports and oral presentations.
9. Become familiar with common statistical tests and understand when they should be applied.
10. Gain experience in conducting small independent research projects, applying statistical methods to analyze data and draw conclusions.

Course Content:

The purpose of this course is to study the methodologies used in the design of Machine Learning systems for applications in medicine and biology. Topics include:

• Data acquisition and preprocessing (e.g., csv, excel, json, xml, yaml formats).
• Feature extraction from medical and biological images.
• Statistical data analysis.

The course also covers supervised Machine Learning methodologies for algorithm design in programming languages, applied to classification of diseases and disease prediction. Students are further trained in the design of unsupervised and deep learning systems using real medical or biological data and modern software libraries.

Upon completion of the course, students will be able to:

1. Understand the theory and implementation technologies of Machine Learning methodologies applied to Medicine and Biology.
2. Comprehend the methods employed in modern computational systems utilizing Machine Learning.
3. Distinguish and understand the data preprocessing and analysis methods required for various applications, as well as select appropriate Machine Learning algorithms.
4. Apply Machine Learning algorithms in programming code using modern software technologies, developing integrated Machine Learning systems for Medicine and Biology.

Yiannis Troulis, BCOM, MBA, CEO, TTMI Consulting LTD.

yet@ttmi.gr

• Introduction
  • Fundamentals of Marketing with examples from the biomedical sector
  • Customer Value

• • Components of perceived Value & Cost
  • Customer satisfaction
  • Market oriented companies
  • Marketing micro and macro environment
  • Porter Five Forces Analysis
  • SWOT Analysis
  • The Marketing mix
  • Products and brands
  • Product’s levels
  • Value Proposition Canvas & Unique Value Proposition
  • Product lifecycle
  • Market Segmentation and market targeting strategies

• Figures of the Biomedical Market
• Innovation and Technology Transfer
  • Innovation (general aspects)
  • Technology Transfer
  • The operation of Technology Transfer
  • Technology Transfer in the Biomedical Sector
  • Sources of Funding
  • Intellectual Property Rights
  • R&D Figures in EU
  • Innovations in the biomedical sector

This course familiarizes graduate students with the science and engineering of biomaterials and their modern applications, emphasizing the relationship between structure–properties–processing–performance for optimizing biomaterial design across scales, tailored to biomedical applications.

It covers the microscopic structure of biomaterials, their physicochemical, mechanical, and interfacial properties. Special attention is given to in vivo corrosion and degradation, and the mechanical response of materials to applied loads comparable to those in biological tissues.

The course explores both traditional biomaterials (metals, ceramics, polymers, composites) and advanced biomaterials (Porous Coordination Polymers, Metal-Organic Frameworks, Zeolitic Imidazolate Frameworks, Graphene, Carbon Nanotubes, Lipid and Lipopeptide Nanoparticles, etc.) for targeted therapies, genetic vaccines, multifunctional scaffolds for tissue engineering, and novel in vitro diagnostic tools.

The course concludes with the study of molecular interactions between materials and biological tissues, aiming to understand the mechanisms of successful in vivo integration of biomaterials and minimizing adverse biological responses.

Upon successful completion of the course, students will be able to:

1. Distinguish and compare traditional and advanced biomaterial categories, analyze their physicochemical and mechanical properties, and formulate and evaluate the structure–properties–processing–performance relationship across scales.
2. Describe and analyze the processes involved in molecular interactions between materials and biological tissues, aiming to design advanced multifunctional biomaterials with optimal performance for biomedical applications.

The aim of the course is to understand the structural and functional organization of the nervous system and how this knowledge supports modern diagnostic and therapeutic applications in neurological disorders.

The course consists of:

• Theoretical lectures, practical exercises, and seminars on human macro- and micro-neuroanatomy and related imaging methods.
• Training in 3D printing methodologies and applications for educational and clinical purposes in neuroanatomy, including hands-on 3D printing practice.
• Introduction to biomarkers, related technologies/clinical platforms, and their clinical utility in traumatic brain injury and Alzheimer’s disease.
• Study of the pathophysiology and diagnostics of neurological diseases such as Parkinson’s disease, dystonia, and epilepsy, along with modern neuromodulation techniques for their management.

Upon completion of the course, students will:

1. Acquire comprehensive knowledge of the structural and functional organization of the nervous system and related imaging methods.
2. Develop the ability to identify anatomical and vascular structures of the human brain.
3. Gain theoretical knowledge and practical expertise in 3D printing of neuroanatomical structures.
4. Understand the pathophysiological mechanisms, diagnostic methods, and modern therapeutic approaches for common neurological disorders, such as Alzheimer’s disease, Parkinson’s disease, dystonia, epilepsy, and traumatic brain injury.
5. Understand the concept of molecular biomarkers, related technologies, and their clinical applications in neurological diseases.
6. Comprehend the fundamental principles and modern therapeutic applications of neuromodulation in neurological disorders.