Andreas Ask

Andreas is a Deep Learning researcher at Embedl. He received his PhD in Physics from Chalmers University of Technology in 2021, where he worked on quantum computing, and his M.Sc. in physics from the University of Gothenburg in 2015. With a keen interest in everything deep-learning related, Andreas specializes in optimizing deep learning models for embedded systems. He is especially interested in model compression techniques centered around network pruning, neural architecture search, and knowledge distillation, and how to tailor these techniques to industrial needs.