Three EEMCS scientists receive Vidi's
The Netherlands Organisation for Scientific Research (NWO) has awarded Vidi grants to three scientists from the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). The fortunate ones are Jan van Gemert, Martijn Caspers and Sicco Verwer. The NWO grant offers them the possibility of developing their own line of research and building their own research group.
Vidi is aimed at excellent researchers who have already carried out several years of successful research following their PhD. The scientists belong to the top ten to twenty per cent of their field. A Vidi grant enables them to do research for a period of five years. Each scientist receives a grant for a maximum of 800,000 euros. The NWO selects the Vidi laureates based on the quality of the researcher, the innovative character of the research, the expected scientific impact of the research proposal and possibilities for knowledge utilisation.
Below a brief description of the three EEMCS-research projects that will receive Vidi funding:
- The harmony of operator algebras
Martijn Caspers, Applied Mathematics Analysis: ‘Operator algebras give the mathematical description of quantum mechanical observables, like the place and impulse of small particles. This research develops techniques from harmonic analysis (or wave analysis) to unravel the fine structure of these quantum systems. We expect that exactly these methods enable us classify them.’
- Innate knowledge for Deep Learning
Jan van Gemert, Intelligent Systems: ‘Deep learning is the engine behind the world’s arms race on artiﬁcial intelligence. Deep learning allows a computer to learn from expensive, huge, datasets. I will add innate knowledge to deep learning: What is built-in no longer has to be learned, saving valuable training data.’
- Insightful analysis of software logs
Sicco Verwer, Intelligent Systems: ‘Software problems have severe effects on our society. Fortunately, software leaves many traces that can be used to uncover these problems. Software traces are therefore stored in massive log databases. Unfortunately, the tools that provide the insight required to analyze this data do not yet exist. This proposal rectifies this.’