Dominik L. Michels, Assistant Professor of Computer Science and Applied Mathematics, and Head of the Computational Sciences Research Group within KAUST's Visual Computing Center, was recently awarded one of the six Artificial Intelligence Grants of the State of North Rhine-Westphalia (NRW), Germany, for his contributions to the simulation of complex physical environments. The grant, amounting to 1.25 million euros, will fund Michels’ research on algorithmic methods to use synthetic data for training of neural networks in Machine Learning. “Synthetic data are data that were not obtained by direct measurement but were generated by specific algorithms,” Michels explains, “in neural networks, the use of synthetic data is needed whenever the amount of data available is less than required.”
About
by Francesca Serra
Dominik L. Michels, Assistant Professor of Computer Science and Applied Mathematics, and Head of the Computational Sciences Research Group within KAUST's Visual Computing Center, was recently awarded one of the six Artificial Intelligence Grants of the State of North Rhine-Westphalia (NRW), Germany, for his contributions to the simulation of complex physical environments. The grant, amounting to 1.25 million euros, will fund Michels’ research on algorithmic methods to use synthetic data for training of neural networks in Machine Learning.
“Synthetic data are data that were not obtained by direct measurement but were generated by specific algorithms,” Michels explains, “in neural networks, the use of synthetic data is needed whenever the amount of data available is less than required.”
Capturing data in the real world may be difficult, too expensive, and in many cases, significant data are simply not available at all. An example of impractical data collection is teaching an autonomous agent to react to risky situations. “In hazardous conditions, a data-driven approach would be too dangerous to follow, and the contour conditions could be difficult to reproduce,” he added.
Since 2007, NRW’s Ministry of Culture and Science annually nominates few international German scientists to become the recipients of these state grants. These activities, as part of NRW’s academic expat program, aim to sustainably strengthen the international competitiveness of NRW as an excellent place to conduct cutting-edge research. This year, for the first time, the ministry awarded six research grants in the field of Artificial Intelligence (AI) and Machine Learning (ML), each endowed with 1.25 million euros.
Current research focus
Michels’ current research focus on developing computational methods for simulation tasks in the fields of Visual and Scientific Computing. To do so, Michels makes use of fundamental research comprising algorithmics, artificial intelligence and machine learning, computer algebra, mathematical modeling, as well as numerical analysis.
Michels obtained a Ph.D. in Mathematics and the Natural Sciences at the University of Bonn and did his postdoctoral studies at Caltech. After that, he joined Stanford’s Computer Science Department before moving to KAUST. Among the many achievements, Michels was recently selected as a member of the top-class jury for the German AI Award.
