Dirk Deschrijver

Dirk Deschrijver

Dirk Deschrijver

email: Dirk.Deschrijver@UGent.be
tel.: +32 9 331 49 96
research group: IDLab
website

Dirk Deschrijver obtained in 2007 the PhD in Computer Science from the Dept. of Mathematics and Computer Science at the University of Antwerp, Belgium. In May-October 2005, he was a Marie Curie Fellow in the Scientific Computing group at the Eindhoven University of Technology in Eindhoven, The Netherlands. In 2006 and 2008, he was a visiting researcher at SINTEF Energy Research in Trondheim, Norway and the University of L’Aquila in Italy. From 2008-2014, he worked as an FWO post-doctoral research fellow in the IDLab research group in the Department of Information Technology at Ghent University. In 2012, he obtained a second PhD degree degree, in engineering, at Ghent University. Since October 2014, he has been working as a senior researcher at iMinds/imec. Since October 2016, he is as an associate professor in the IDLab research group of Ghent University, working on data analytics, machine learning and surrogate modeling algorithms.

Keywords: Data analytics, machine learning, time series, surrogate modeling

Key publications

  • K. Crombecq, D. Gorissen, D. Deschrijver, T. Dhaene, A Novel Hybrid Sequential Design Strategy for Global Surrogate Modeling of Computer Experiments, SIAM Journal on Scientific Computing, vol. 33, no. 4, pp. 1948-1974, 2011.

  • I. Couckuyt, D. Deschrijver, T. Dhaene, Fast Calculation of the Multiobjective Probability of Improvement and Expected Improvement Criteria for Pareto Optimization, Journal of Global Optimization, vol. 60, no. 3, pp. 575-594, November 2014.

  • N. Staelens, D. Deschrijver, E. Vladislavleva, B. Vermeulen, T. Dhaene, P. Demeester, Constructing a No-Reference H.264/AVC Bitstream-based Video Quality Metric using Genetic Programming-based Symbolic Regression, IEEE Transactions on Circuits and Systems in Video Technology, vol. 32, no. 8, pp. 1322-1333, August 2013.

  • J. van der Herten, I. Couckuyt, D. Deschrijver, T. Dhaene, A Fuzzy Hybrid Sequential Design Strategy for Global Surrogate Modeling of High-Dimensional Computer Experiments, SIAM Journal on Scientific Computing, vol 37, no. 2, pp. A1020–A1039, April 2015.

  • .L. De Baets, J. Ruyssinck, C. Develder, T. Dhaene, D. Deschrijver, On the Bayesian Optimization and Robustness of Event Detection Methods in NILM, Energy and Buildings, vol. 145, pp. 57-66, June 2017.

Publication links