Kris De Brabanter (Assistant Prof.)
Department of Statistics
Department of Computer Science


Iowa State University
2419 Snedecor Hall, Ames, Iowa, 50011-1210
515-294-8253
kbrabant@iastate.edu

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Research interests

mathematical statistics, nonparametric regression, analysis of big data sets, machine learning, model selection methods, density estimation, nonparametric inference  

 

Curriculum Vita                                       Calendar

 

Education

PhD, Katholieke Universiteit Leuven, Leuven, Belgium, 2011

MS, Katholieke Universiteit Leuven, Leuven, Belgium, 2007

MS, Erasmus hogeschool Brussel, Anderlecht, Belgium, 2005

BS, Erasmus hogeschool Brussel, Anderlecht, Belgium, 2003


Previous academic positions

October 2012 – August 2013: FWO fellow postdoctoral researcher

October 2011 - September 2012: Postdoctoral researcher, Special Research Fund, KU Leuven

April 2011 - September 2011: Postdoctoral researcher, Dep. Electrical Engineering, KU Leuven

October 2007 - April 2011: Ph.D. student, Dep. Electrical Engineering, KU Leuven

 

Invited seminars & keynote talks

  1. 07/10-12/2018, Local polynomial regression with correlated errors and unknown correlation structure, Workshop on New Developments in Statistics: Big Data, a Challenge or a Curse for Statistics? Heverlee, Belgium

  2. 05/14-17/2018, Midwest Big Data Summer School, Introduction to Statistics, Iowa State University

  3. 07/10-14/2017, Midwest Big Data Hub, 3 seminars about Statistics and Machine Learning, Iowa State University

  4. 06/14/2017, Local Polynomial Regression with Unknown Correlation Structure, Mini Symposium on New Developments in Nonparametric Statistics, Leuven, Belgium

  5. 06/20-24/2016, Midwest Big Data Hub, 3 seminars about Statistics and Machine Learning, Iowa State University

  6. 02/20/2015, Smoothed Nonparametric Derivative Estimation Based on Weighted Difference Sequences, 12th Workshop on Stochastic Models, Statistics and Their Applications, Wrocław, Poland

  7. 09/11/2014, Department of Statistics & Actuarial Science, University of Iowa, IA, USA

  8. 10/11/2013, Challenges in Big Data: Theory and Applications, LAS College Signature Theme Workshop on Data Rich environments, Iowa State University, Iowa, USA

  9. 05/14/2013, Common Pitfalls in Statistical Data-analysis: Hypothesis Testing & Regression, Department of mathematics section of statistics, KU Leuven (FLAMES), Belgium

  10. 04/01/2013, Nonparametric Regression in the Presence of Correlated Errors, Department of statistics, Iowa State University, Iowa, USA

  11. 11/26/2012, Nonparametric Techniques for Analyzing Correlated Data, Department of statistics, Colorado State University, Fort Collins, CO, USA

  12. 06/26/2012, Theoretical Aspects of Nonparametric Techniques for Correlated Data, Department of statistics, Melbourne University, Australia

  13. 01/16/2012, How to Detect Correlation between Variables, Department of chemical engineering, KU Leuven, Belgium

 

Tutorials

  1. 04/26/2012, Deconvolution in nonparametric statistics (session tutorial), ESANN 2012, Brugge, Belgium

 

Seminars

  1. 12/06/2017,  Nonparametric regression with unknown correlation structure, Industrial and manufacturing Systems Engineering, Iowa State University, Iowa, USA

  2. 10/23/2013, Big data and nonparametric regression, Department of Statistics (Computational Statistics group), Iowa State University, Iowa, USA

  3. 10/22/2013, Support vector machines and its applications. Department of Statistics, Iowa State University, Iowa, USA

  4. 09/19/2013, Nonparametric techniques: big data meets statistics. Department of Computer Science, Iowa State University, Iowa, USA

  5. 02/09/2012, Asymptotic properties of linear smoothers, Department of Electrical engineering ESAT-SCD, KU Leuven, Belgium

  6. 09/23-24/2010, Approximate confidence and prediction intervals for least squares support vector regression, OPTEC Meeting event, Spa, Belgium

  7. 06/17/2009, Least squares support vector machines for large data sets: a fixed size approach, Department of Electrical engineering ESAT-SCD, KU Leuven, Belgium

  8. 06/09/2009, Least squares support vector machines: a large scale approach, Department of Electrical engineering ESAT-SCD, KU Leuven, Belgium