Prof Sotirios Tsaftaris




+44(0)131 6505796


2.06 Alexander Graham Bell building

Personal Page: 

Engineering Discipline: 

  • Electronics and Electrical Engineering

Research Institute: 

  • Imaging, Data and Communications

Research Theme: 

  • Signal and Image Processing
Dr Sotirios Tsaftaris
Dr Sotirios Tsaftaris

Academic Qualifications: 

  • 2000 - Diploma (5 year), Aristotle University of Thessaloniki (Greece), Electrical and Computer Engineering
  • 2003 - MSc, Northwestern University (USA), Electrical and Computer Engineering
  • 2006 - PhD, Northwestern University (USA), Electrical and Computer Engineering


  • MSc Level Machine Learning for Signal Processing (2018-)
  • MSc Level Advanced Concepts in Signal Processing (2016-2018)
  • 3rd year undegradute, Electromagnetics, Signals and Communications 3 (2017-)
  • 3rd year undegradute, Signals and Communications 3 (2015-2017)

Research Interests: 

While I have contributed to several research domains my mission is via image analysis to help diagnose and understand disease and provide food for everyone. The population increase exerts tremendous pressure on our healthcare systems and agricultural needs. Imaging methodologies are increasingly used to aid diagnoses and to build image-driven physiological models in the natural and life sciences. However, the explosion of the amount of data cannot be met by the current approaches used to analyse the generated images/volumes/movies and unravel the complicated patterns that exist. Our mission, is to address these limitations by integrating the state of the art in computer vision, deep learning, machine learning, compression, and distributed infrastructures. Our unique approach has the potential to provide efficient and affordable solutions towards a sustainable healthcare system and agriculture, of immense benefit and importance to the society.

My research interests are image analysis, image processing, data mining and machine learning, and distributed computing. Core research applications are in computer aided diagnosis in medicine and phenotyping in biology.

Personal Website:



  • Medical Image Computing and Analysis
  • Computer Vision and Machine Learning