I am a postdoctoral researcher at Empirical Inference Department, Max Planck Institute for Intelligent Systems working with Bernhard Schölkopf. I work in the field of machine learning (intersection of computer science and statistics). More specifically, my research interests range from non-parametric statistical tests, approximate Bayesian inference, to kernel-based feature representation of data. I completed my PhD study at Gatsby Computational Neuroscience Unit, UCL where I worked with Arthur Gretton on various topics related to kernel-based non-parametric statistical tests. I received MEng from Tokyo Institute of Technology where I worked with Masashi Sugiyama on supervised feature selection using squared-loss mutual information. Before that I was a research assistant working with Thanaruk Theeramunkong on a Thai news relations discovery project. I received BSc in Computer Science from SIIT, Thammasat university, Thailand.

My works are listed on this page. Software packages I released can be found here. I occasionally update my blog summarizing what I learn. Some photos I have taken are on Flickr.

I am always open for a research discussion. If there is a chance that I could contribute to your projects, please get in touch to discuss. If you are a bachelor, master, or PhD student working in a field related to machine learning, and are looking for an internship opportunity (for 2-6 months) at the Empirical Inference department, please contact me.

Contact: Wittawat Jitkrittum (วิทวัส จิตกฤตธรรม) ( ) Address:
Wittawat Jitkrittum
Max Planck Institute for Intelligent Systems
Max-Planck-Ring 4
72076 Tuebingen
Phone: +49 7071 601


Updated: 09-Oct-18
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