Welcome to my personal webpage. I am Charilaos (Harry) Mylonas, and I am a Ph.D. candidate on the topic of Machine Learning & Uncertainty Quantification for Remaining Useful Life Predictions in Wind Energy. I use large-scale simulations and machine learning techniques to gain insight and quantitatively model structural and operational quantities of interest in wind turbines and wind farms.

My research is on deep generative models (in particular VAEs & normalizing flows), graph machine learning (Graph Networks) and combinations thereof. My application domains of interest are scientific computing, structural condition monitoring and remaining life assessment. I am also interested in applications of AI in healthcare and solving engineering and societal problems in general.

My hobbies include guitar playing, electronics/microcontrolers and digital art.

For a list of posts on some of my academic works click here

For a list of posts on some of my personal projects click here

Curriculum Vitae

Google scholar