Jan N. van Rijn

Jan van Rijn

Curriculum Vitae

March 2018 - now
Post-doc in Data Science Institute, Columbia University (New York, USA).
September 2016 - February 2018
Post-doc in ML4AAD, Freiburg University (Germany).
September 2012 - August 2016
PhD candidate within the Algorithms cluster (LIACS), Leiden University. Project: Massivly Collaborative Data-Mining, Thesis: Massively Collaborative Machine Learning
September 2004 - June 2008
Bachelor Informatica, Hogeschool Leiden.

Teaching

This list shows the courses I assisted during my PhD in Leiden. For a comprehensive list, please request my resume.
February 2016 - June 2016
Teaching Assistent Kunstmatige Intelligentie, Leiden University
September 2015 - January 2016
Teaching Assistent Programmeermethoden, Leiden University
September 2014 - January 2015
Teaching Assistent Data Mining, Leiden University
September 2013 - January 2014
Teaching Assistent Datastructuren, Leiden University
February 2013 - June 2013
Teaching Assistent Algorithms, Leiden University
September 2012 - January 2013
Teaching Assistent Datastructuren, Leiden University
February 2012 - June 2012
Teaching Assistent Algorithms, Leiden University
September 2011 - January 2012
Teaching Assistent Programmeermethoden, Leiden University
February 2011 - June 2011
Teaching Assistent Algorithms, Leiden University

Publications

This list was last updated in November 2018. For an up to date list, please visit my Google Scholar profile.

Academic Visits

February 2016 - March 2016
University of Waikato, worked with Geoffrey Holmes and Bernhard Pfahringer on The online performance estimation framework: heterogeneous ensemble learning for data streams
Februay 2015 - May 2015
University of Waikato, worked with Geoffrey Holmes and Bernhard Pfahringer on Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams
Februay 2014 - May 2014
University of Waikato, worked with Geoffrey Holmes and Bernhard Pfahringer on Algorithm Selection on Data Streams

Organization

OpenML 2016 poster

Open Machine Learning 2016


from 14 Mar 2016 through 18 Mar 2016
OpenML is a networked science platform that aims to connect and organize all this knowledge online, linking data, algorithms, results and people into a coherent whole so that scientists and practitioners can easy build on prior work and collaborate in real time online.

Contact Information

E-mail: j.n.vanrijn (at) columbia (dot) edu

Visiting address

Columbia University
Mudd Building (office 425)
116th St and Broadway
New York
United Stated