People

Janick Frasch

PhD student in the MathOpt research group
at the HGS MathComp
at the Interdisciplinary Center for Scientific Computing (IWR)
at the University of Heidelberg

Address

Room 407
Im Neuenheimer Feld 368
69120 Heidelberg, Germany

phone: +49 6221 54-8809
fax: +49 6221 54-5444

Curriculum Vitae

I studied mathematics, computer science and control engineering at TU Kaiserslautern, University of Heidelberg, National University of Singapore, University of California, Berkeley and KU Leuven. I obtained a Dipl.-Math. degree (the German equivalent to a MSc degree) from TU Kaiserslautern in 2009. I am currently pursuing a PhD degree in applied mathematics, advised by Sebastian Sager, Moritz Diehl and Georg Bock.
A detailed resumee is available on request.

Research interests

• Mixed-Integer Optimal Control
• Model-Predictive Control
• Embedded Optimization
• Combinatorial Optimization
• Scheduling

• Industrial Applications
• Automotive Applications

• Machine Learning
• Data Mining

Refereed Publications and Theses

• F. Kehrle, J. V. Frasch, C. Kirches, S. Sager. Optimal Control of Formula 1 Race Cars in a VDrift based Virtual Environment. Proceedings of the 18th IFAC World Congress, 2011, pp. 11907-11912. DOI: 10.3182/20110828-6-IT-1002.02954
• J. V. Frasch, A. Lodwich, F. Shafait, T. M. Breuel. A Bayes-true data generator for evaluation of supervised and unsupervised learning methods. Pattern Recognition Letters, Volume 32, Issue 11, 2011, pp. 1523-1531. ISSN 0167-8655, DOI: 10.1016/j.patrec.2011.04.010
• J. V. Frasch, S. O. Krumke, S. Westphal. MIP Formulations for Flowshop Scheduling with limited Buffers. Theory and Practice in (Computer) Systems, A. Marchetti-Spaccamela, M. Segal (Eds.). Lecture Notes in Computer Science, Volume 6595, 2011, pp. 127-138. DOI: 10.1007/978-3-642-19754-3_14
• J. Frasch. Algorithms and Complexity for Steel Production Scheduling. Diploma Thesis, Kaiserslautern University of Technology, 2009.

Non-refereed Publications

• A. Lodwich, J. Frasch, T. M. Breuel. Report on Practical Bayes-True Data Generators for Evaluation of Machine Learning, Pattern Recognition and Data Mining Methods. Technical Report, German Research Center for Artificial Intelligence, 2009. Available at http://paren.iupr.com/downloads
• J. Seewig, T. Damm, J. Frasch, D. Kauven, S. Rau, J. Schnebele. Reconstruction of Shape using Gradient Measuring Optical Systems. Proceedings of Fringe 2009, The 6th International Workshop on Advanced Optical Metrology, W. Osten, M. Kujawinska (Eds.). Springer, 2009. ISBN: 978-3-642-03050-5

Preprints available on request.

Scientific Trivia

• Das Rucksackproblem der Bundesliga-Manager - optimierte Entscheidungen bei der Kaderzusammenstellung (in German)
• On the Reconstruction of Sensor Locations from Distance Measurements (Report for the 2011 MOPTA Competition)