Motonobu Kanagawa

I am currently an Assistant Professor in the Data Science department at Eurecom since September 2019.  I also hold a Chair at 3IA Côte d’Azur since 2021. Previously I was a research scientist at the Chair for the Methods of Machine Learning in the University of Tuebingen (Oct 2018 - Aug 2019), and at the Probabilistic Numerics Group in the Max Planck Institute for Intelligent Systems (Sep 2017 - Sep 2018), working with Prof. Philipp Hennig. Prior to this, I was a postdoc (Apr 2016 - Aug 2017) and a PhD. student (Apr 2013 - Mar 2016) at Institute of Statistical Mathematics, working with Prof. Kenji Fukumizu.

I am currently working on the following research topics: 

- Kernel methods and Gaussian processes in machine learning 

These are statistical learning methods that make use of positive definite kernels. See our recent review paper on the connections and equivalence between the two approaches.

- Machine learning for computer simulation

Machine learning methods, in particular those based on kernels and Gaussian processes, are very useful in enhancing the power of computer simulation. They enable automatic parameter tuning and model selection, as well as quantification of various kinds of uncertainties.   

- Computer simulations for real world problems

Current projects include simulations for evacuation planning  and emulations for tsunami early warning. 

Contact Information

Eurecom, Data Science Department, Office 429

Campus SophiaTech, 450 Route des Chappes, 06410 Biot, France

Email: motonobu.kanagawa [CHAN]  (Please replace [CHAN] by @)


Academic Services

Antibes, September 2019

Tuebingen, April 2019