I am Yorgos from Greece. I majored in programming and mathematics, knowledge I acquired through my studies in Mechanical and Aeronautical Engineering from University of Patras, Greece. I completed my master’s degree in Computational Mechanics from Technical University of Munich, Germany. My area of interest focuses on machine learning, deep learning, statistics, and artificial intelligence. I find this programme ideal to combine the knowledge and techniques which I have acquired in these fields with research in the spheres of medicine, healthcare, and biology.

My abilities in the field are rooted in an education and early life in mathematics and problem solving. During my school years I was competing with success in competitions of mathematics, while I was following a professional career in chess, since a very young age. Later, during my university years, I had the chance to test myself in many different fields, from space to medical engineering, always having as point of reference my programming and mathematical skills. I did, also, learn and use many programming languages, mastering among others in Python, C++, C#, MATLAB,  and having experience in SQL, JavaScript, html. I attribute my success in my fields of interest mainly to my self-learning, not only in programming and statistics, but also in the specializations I completed in online courses in deep learning, data science, algorithms.

Concerning my work experience, I would highlight my position as a Software and Machine Learning Engineer in Universitat Politecnica de Catalunya (UPC), in the Aeronautics Department, handling algorithms on optimization of trajectories in Air Traffic Management; and my work experience in Honda Research Institute Europe GmbH, where I completed my master thesis in the field of deep learning for structure applications. In addition, I gained work experience with Autodesk, in coding and developing applications related to Virtual Reality, my role as a Data Scientist in Ernst & Young Spain, and last, my short period as an intern in the Institute of Rechtsmedizin GmbH, in Munich, where I had the chance to apply my engineering skills in medical applications.

The objectives of my project are to design and develop software, based on Artificial Intelligence and Machine Learning techniques, to support the research in assisted reproductive technologies (ART). The contribution of this project includes (i) the design of new machine learning algorithms, (ii) the facilitation of the acquisition, analysis and validation of new knowledge through the analysis of ART data, and the (iii) the introduction of new, proven AI methods for the evaluation of in-vitro fertilization (IVF).

Additionally, visual simulation of several techniques and processes might be developed, for educational and research purposes.