MPI IS Stuttgart

Matej Balog

Heisenbergstr. 3

70569 Stuttgart

Matej Balog

Matej Balog

Matej Balog


PhD Student

Main Focus

Markov Chain Monte Carlo methods for Bayesian machine learning

Curriculum Vitae

Matej Balog

Max Planck Institute for Intelligent Systems, Spemannstr. 38, 72076 Tubingen, Germany

Contact:, +44 7426599342


Cambridge-Tubingen PhD Fellowship in Machine Learning

Department of Engineering, University of Cambridge

Max Planck Institute for Intelligent Systems, Tubingen

2015 -present

Focus: Probabilistic Machine Learning

Supervisors: Prof Zoubin Ghahramani, Prof Bernhard Scholkopf

Master of Mathematics and Computer Science

Merton College, University of Oxford

2011 -2015

Focus: Machine Learning, Probability, Algorithms and Data Structures

Result: First Class in all examinations


Work Experience

Research Intern

Microsoft Research, Cambridge, United Kingdom

July 2016 { November 2016

Project: Source code generation from input-output examples, using deep learning.

Mentors: Daniel Tarlow, Alex Gaunt, Marc Brockschmidt, Sebastian Nowozin

Research Intern

Microsoft Research, Cambridge, United Kingdom

June 2014 { August 2014

Project: Probabilistic modeling of team games, using probabilistic programming.

Mentors: Daniel Tarlow, Ali Eslami

Software Development Engineer Intern

Microsoft, Bellevue, WA, US

Bing Core Relevance team

July 2013 { September 2013

Project: Analysis of Contextual Search techniques in Bing.

Mentors: Wei Chu, Sebastian de la Chica


Awards and Achievements

Hoare Prize for best performance in Mathematics and Computer Science 2015, Oxford

International Olympiad in Informatics (IOI) 2011 Silver Medal Pattaya, Thailand

International Olympiad in Informatics (IOI) 2010 Bronze Medal Waterloo, Canada

Middle European Mathematical Olympiad (MEMO) 2011 Bronze Medal Slovakia

International Physics Olympiad (IPhO) 2011 Silver Medal Bangkok, Thailand

International Junior Science Olympiad (IJSO) 2008 Silver Medal South Korea

Google Code Jam 2012  266th place worldwide


Professional Skills

Critical and analytical thinking, problem solving, research

Machine learning research, algorithm design and implementation using tools including

TensorFlow, Python, Matlab

Algorithms and data structures design, analysis and implementation in programming

languages such as Python, Scala, Java, C#, C++


Probabilistic Machine learning, quantifying uncertainty in machine learning models

Education, taking online courses at Coursera

Urban transportation and planning, cycling

Organizational Unit (Department, Group, Facility):

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