MACHINE LEARNING GROUP

TECHNISCHE UNIVERSITÄT KAISERSLAUTERN

Prof. Dr. Marius Kloft

Professor

Bio

Since 2017 Marius Kloft has been a professor of computer science at TU Kaiserslautern, Germany. Previously, he was an adjunct faculty member of the University of Southern California (09/2018-03/2019), an assistant professor at HU Berlin (2014-2017) and a joint postdoctoral fellow (2012-2014) at the Courant Institute of Mathematical Sciences and Memorial Sloan-Kettering Cancer Center, New York, working with Mehryar Mohri, Corinna Cortes, and Gunnar Rätsch. From 2007-2011, he was a PhD student in the machine learning program of TU Berlin, headed by Klaus-Robert Müller. He was co-advised by Gilles Blanchard and Peter L. Bartlett, whose learning theory group at UC Berkeley he visited from 10/2009 to 10/2010. In 2006, he received a master in mathematics from the University of Marburg with a thesis in algebraic geometry.

Research interests

Marius Kloft is interested in theory and algorithms of statistical machine learning and its applications, especially in statistical genetics and chemical engineering. He has been working on, e.g., multiple kernel learning, transfer learning, anomaly detection, extreme classification, and adversarial learning. He co-organized workshops on these topics at NIPS 2010, 2013, 2014, 2017, ICML 2016, and Dagstuhl 2018. His dissertation on Lp-norm multiple kernel learning was nominated by TU Berlin for the Doctoral Dissertation Award of the German Chapter of the ACM (GI). In 2014, he received the Google Most Influential Papers 2013 Award.

Appointments and administration
neu@cs.uni-kl.de
Grant administration
reithermann@cs.uni-kl.de
Scientific matters
kloft@cs.uni-kl.de
Office
TUK, Building 36, Room 310/312 - 67653 Kaiserslautern
Office hours
--- suspended until further notice ---

Curriculum Vitae

Education

2011
Doctoral Degree in Computer Science, TU Berlin, Germany
2006
Diploma in Mathematics, Marburg University, Germany

Professional Experience

since 2019
Full Professor, TU Kaiserslautern, Kaiserslautern, Germany
2018-2019
Adjunct Associate Professor, University of Southern California, Los Angeles, CA, USA
2017-2019
Associate Professor, TU Kaiserslautern, Kaiserslautern, Germany
2014-2017
Junior Professor, HU Berlin, Berlin, Germany
2012-2014
Postdoctoral Researcher, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
2012-2014
Postdoctoral Researcher, Courant Institute of Mathematical Sciences, New York, NY, USA
2011
Postdoctoral Researcher, TU Berlin, Berlin, Germany
2009-2010
Research Associate, UC Berkeley, CA, USA

Research expertise

Statistical machine learning, deep learning, statistical learning theory, regularization, kernel-based learning, data integration, extreme classification, learning-based anomaly detection

Activities and honors

2020 -
Associate Editor, IEEE TNNLS
Senior member, IEEE
2020
Area chair, AAAI '21 and AISTATS '21
PC member, SPP 2331
2019
Senior area chair, AAAI '19
Area chair, ECML '19 and AISTATS '19
Best Reviewer Awards, NIPS '19 and ICML '19
2015–2017
Action Editor, JMLR
2015
Emmy-Noether Career Award by the German NSF (DFG)
2014
Google Most Influential Papers 2013 Award
2011
Best Dissertation Award, EECS, TU Berlin
2011
1st place at ImageCLEF Visual Object Recognition Challenge
since 2009
Co-organizer of 7 international workshops at ICML (1x), NIPS (4x), and Dagstuhl(2x)
since 2007
Reviewer for >50 international conference and >30 journals

Key publications