Hi, I'm Minas.
About me
I am a Postdoctoral Fellow at the University of California, Berkeley, where I conduct research at the intersection of artificial intelligence, statistics, and physics. My focus involves developing Bayesian machine learning techniques with applications in the physical sciences. I received my PhD in Astrophysics in 2022 from the University of Edinburgh, where my thesis pioneered novel methods for scalable and gradient-free Bayesian inference with applications in astronomy. Prior to my doctorate, I obtained a Master's degree in Applied Mathematics from the University of Cambridge and a Bachelor's degree in Physics from Aristotle University of Thessaloniki.
My recent research focuses on developing artificial intelligence and machine learning tools to facilitate Bayesian inference in the physical sciences. I am particularly interested in designing algorithms that can efficiently sample from high-dimensional posterior distributions when the gradient is intractable. By combining Bayesian probabilistic methods and AI, I aim to push the boundaries of statistical and computational modeling. My goal is to create generalizable techniques that can provide insight into fundamental questions across astronomy, physics, and chemistry.
Contact
minaskar@gmail.com