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Personal profile

Quote

“To democratize machine learning, we need a more principled approach to experimentation, understand how to build machine learning systems, and progressively automate this process as much as possible."

Research profile

Joaquin Vanschoren is an Assistant Professor of Machine Learning at the Eindhoven University of Technology (TU/e). His research focuses on the progressive automation of machine learning. He founded and leads OpenML.org, an open science platform allowing scientists to share datasets and train many machine learning models from many software tools in a frictionless yet principled way. It also organizes all results online, providing detailed insight into the performance of machine learning techniques, and allowing a more scientific, data-driven approach to building new machine learning systems. Subsequently, he uses this knowledge to create automatic machine learning (AutoML) techniques that learn from these experiments to help people build better models, faster, or automate the process entirely. 

Machine learning is the science of making computers act without being explicitly programmed. Instead, algorithms are used to find patterns in data. During his courses, Joaquin explains the foundations of machine learning algorithms work internally, understand when and how to use key concepts and techniques, and offers hands-on experience in getting them to work for yourself. Students are stimulated to engage in the key underpinnings of machine learning, and leverage this to quickly and powerfully apply this knowledge to tackle new problems.

Academic background

Joaquin Vanschoren received his PhD in Engineering from the University of Leuven, Belgium, where he also obtained an MSc in Engineering Computer Science (with honors). Research visits have taken Joaquin to IBM and Amazon Research, the Jozef Stefan Institute and the Universities of Waikato, Aberystwyth, Paris-Sud, Dortmund, Geneva, Zurich, Porto, Bournemouth, Aberdeen, and Indiana. Before joining TU/e, Joaquin was a Data Scientist at CityLife (now Joyn).

He has been keynote speaker at the European Conference on Data Analysis, Statistical Computing, and workshops at Neural Information Processing Systems (NIPS) and the International Conference on Machine Learning (ICML). He also co-organized machine learning conferences (e.g. ECMLPKDD 2013, LION 2016) and many workshops, including the AutoML Workshop series at ICML. He is co-chair of the W3C ML-Schema Community Group and a senior member of the Dutch School for Information and Knowledge Systems. Joaquin is a member of wide range of committees, including Neural Information Processing Systems, ACM SIGKDD Conference on Knowledge Discovery and Data Mining and International Joint Conferences on Neural Networks and Artificial Intelligence. He also acts as a referee for various journals, such as Machine Learning Journal, Journal of Machine Learning Research and Data Mining and Knowledge Discovery.

Affiliated with

* Philips Research

* Amazon Research

Fingerprint Dive into the research topics where Joaquin Vanschoren is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Learning systems Engineering & Materials Science
Classifiers Engineering & Materials Science
Experiments Engineering & Materials Science
Data mining Engineering & Materials Science
Metadata Engineering & Materials Science
Ontology Engineering & Materials Science
Tuning Engineering & Materials Science
Testing Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2006 2019

46 Citations (Scopus)
1 Downloads (Pure)

Aslib: a benchmark library for algorithm selection

Bischl, B., Kerschke, P., Kotthoff, L., Lindauer, M., Malitsky, Y., Fréchette, A., Hoos, H., Hutter, F., Leyton-Brown, K., Tierney, K. & Vanschoren, J., 2016, In : Artificial Intelligence. 237, p. 41-58 18 p.

Research output: Contribution to journalArticleAcademicpeer-review

scenario
Benchmark
artificial intelligence
Set theory
performance
11 Citations (Scopus)
5 Downloads (Pure)

Reduction of false arrhythmia alarms using signal selection and machine learning

Eerikäinen, L. M., Vanschoren, J., Rooijakkers, M. J., Vullings, R. & Aarts, R. M., 2016, In : Physiological Measurement. 37, 8, p. 1204-1216

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
Learning systems
Cardiac Arrhythmias
Electrocardiography
Noise
Ventricular Flutter
4 Downloads (Pure)

OpenML : networked science in machine learning

Vanschoren, J., van Rijn, J. N., Bischl, B. & Torgo, L., 2013, In : SIGKDD Explorations. 15, 2, p. 49-60 12 p.

Research output: Contribution to journalArticleAcademicpeer-review

science
learning
student
63 Citations (Scopus)
5 Downloads (Pure)

A survey of intelligent assistants for data analysis

Serban, F., Vanschoren, J., Kietz, J. U. & Bernstein, A., 2013, In : ACM Computing Surveys. 45, 3, p. 31/1-35

Research output: Contribution to journalArticleAcademicpeer-review

Data analysis
Decision making
Expertise
Leverage
Refinement

Selecting classification algorithms with active testing

Leite, R., Brazdil, P. & Vanschoren, J., 2012, International Workshop on Machine Learning and Data Mining in Pattern Recognition. p. 117-131 15 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Prizes

Dutch Data Prize

Joaquin Vanschoren (Recipient), 9 Nov 2016

Prize: OtherDiscipline relatedScientific

Microsoft Azure research Award

Joaquin Vanschoren (Recipient), 13 Jul 2017

Prize: OtherDiscipline relatedProfessional

Cloud computing

Amazon Research Award

Joaquin Vanschoren (Recipient), 15 Jan 2019

Prize: OtherDiscipline relatedScientific

recipient
supervision
contact
Group
student

Microsoft Azure Research Award

Joaquin Vanschoren (Recipient), 13 Jul 2016

Prize: OtherDiscipline relatedProfessional

Cloud computing

Activities 2018 2018

  • 3 Invited talk
  • 1 Keynote talk

Machine Learning, better, together.

Joaquin Vanschoren (Speaker)
8 Dec 2018

Activity: Talk or presentation typesInvited talkScientific

Tutorial on Automatic Machine Learning

Frank Hutter (Speaker), Joaquin Vanschoren (Speaker)
3 Dec 2018

Activity: Talk or presentation typesKeynote talkScientific

Democratizing and Automating Machine Learning

Joaquin Vanschoren (Speaker)
28 Aug 2018

Activity: Talk or presentation typesInvited talkScientific

Democratizing and Automating Machine Learning

Joaquin Vanschoren (Speaker)
15 Jun 2018

Activity: Talk or presentation typesInvited talkScientific

Courses

CSE - Web Science

1/09/15 → …

Course

Data mining

1/09/15 → …

Course

Press / Media

4. The internet will continue to make life better

Joaquin Vanschoren

28/10/19

1 item of Media coverage

Press/Media: Expert Comment

21st International Conference on Discovery Science (DS 2018)

Joaquin Vanschoren

18/04/18

1 item of Media coverage

Press/Media: Expert Comment

Missing data hinder replication of artificial intelligence studies

Joaquin Vanschoren

14/02/1816/02/18

2 items of Media coverage

Press/Media: Expert Comment

Student theses

A computational biology framework: a data analysis tool to support biomedical engineers in their research

Author: Beishuizen, T., 29 Nov 2018

Supervisor: Bosnacki, D. (Supervisor 1), Cheplygina, V. (Supervisor 2), Hilbers, P. (Supervisor 2), Fletcher, G. (Supervisor 2) & Vanschoren, J. (Supervisor 2)

Student thesis: Master

Active learning for text classification

Author: Šostak, T., 24 Sep 2018

Supervisor: Vanschoren, J. (Supervisor 1) & Schaefers, K. (External person) (External coach)

Student thesis: Master

File

Anomaly detection in wireless mesh lighting networks

Author: Chand, S., 25 Sep 2017

Supervisor: Vanschoren, J. (Supervisor 1), Zappaterra, L. (External person) (External coach), Syed, E. (External person) (External coach) & Casale, P. (External coach)

Student thesis: Master

File

Automated machine learning with gradient boosting and meta-learning

Author: van Hoof, J., 28 Jan 2019

Supervisor: Vanschoren, J. (Supervisor 1)

Student thesis: Master

File

Automatic construction of machine learning pipelines

Author: Gijsbers, P., 30 Oct 2017

Supervisor: Vanschoren, J. (Supervisor 1), Pechenizkiy, M. (Supervisor 2) & Buchin, K. (Supervisor 2)

Student thesis: Master

File