Researcher Google DeepMind |
Carnegie Mellon University
Alex Smola is a highly accomplished computer scientist interested in machine learning and statistical modeling. He completed his Master's in Physics from the University of Technology, Munich, and his Doctoral Degree in Computer Science from the University of Technology, Berlin. After working as a researcher in different organizations, he moved to Google Research in 2012 and continued working there until 2014. He then joined Amazon Web Services in 2016 as VP / Distinguished Scientist for Machine Learning.
Alex's primary research interests lie in deep learning, scalability of algorithms, kernel methods, and statistical modeling, primarily with Bayesian non-parametric. He is particularly interested in developing algorithms for state updates, invariances, and statistical testing. He is also interested in pushing algorithms to the internet scale, distributing them on many machines, and modifying models to fit these requirements.
Alex's research also focuses on applying machine learning techniques to solve problems such as user modeling, document analysis, temporal models, and modeling data at scale. He is always looking for talented interns and team members with experience in deep learning, statistical modeling, efficient algorithms, and high-performance computing systems. Although he is not currently accepting Ph.D. students, he suggests that interested applicants apply to the Machine Learning Department at Carnegie Mellon University.
Dive into Deep Learning -- Interactive Book