sarafis [at] mug.ee.auth.gr
Ioannis Sarafis received his diploma in 2010 from Department of Electrical and Computers Engineering, Aristotle University of Thessaloniki (AUTh), after completing his thesis entitled “Development of an Autonomous Poker Agent Software using Reinforcement Learning Techniques”. Currently, he is pursuing his PhD in the same department as a member of the Multimedia Understanding Group (MUG) and working as a research associate for the H2020 EU-funded BigO project. His research interests include concept-based image retrieval and machine learning under label noise.
2012-today – PhD candidate, Aristotle University of Thessaloniki, GreeceThesis: Semantic classification of multimedia data.
2005 – Diploma of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece
Thesis: “Development of an Autonomous Poker Agent Software using Reinforcement Learning Techniques”
2009 – Award from the Greek State Scholarships Foundation for excellence in the academic year 2007-2008
2013-2017 – Research associate, Aristotle University of Thessaloniki, Greece
Project: BigO – Big Data against Obesity H2020.
Project: SPLENDID – Personalised Guide for Eating and Activity Behaviour for the Prevention of Obesity and Eating Disorders, FP7-610749. Developed an ontology for the description of the eating and behaviour domain and implemented the Decision and Support System of SPLENDID. For the latter, machine learning models for assessing the risk for obesity and/or eating disorders based on the user’s behavioural indicators were implemented. Also, involvement in the surveying and the documentation of SPLENDID system requirements and the development and documentation of the system use cases.
2012-2013 – Web developer, Vidavo S.A.
Projects: Vida24 – mhealth patient telemonitoring service which enables remote monitoring of patients via wearable monitoring devices (ECG monitor, spirometer, oximeter, blood pressure monitor, blood glucose monitor, triglycerides / cholesterol monitor, weight scale, etc) over 2/3/4G and wifi networks.