Research focus: Optimization, parallel algorithms
Michal is working as a Research Assistant at the Cybernetics and Robotics group at CEITEC BUT and is currently trying to finish his Ph.D. His research and study interests are optimization, parallel algorithms, and especially the application of nonlinear model predictive control to the drive with an electrical motor. The combination of these research interests helps him pursue the real-time solution of motor predictive control.
During his doctoral study, Michal had an opportunity to undertake his internship at Technical University in Munich (TUM). The internship was done under the leadership of Professor Ralph Kennel, who was among the first scientists who came with the idea of the application of predictive control to the electrical drive. The RICAIP project helps Michal with the implementation and verification of his designed algorithms.
What do you find the most challenging as a researcher?
I would say that coming up with new approaches is the most challenging part of working as a researcher.
I think working as a researcher is entirely different from any other job. You may have some goals, but usually, you set them. There is nobody who can tell you what to do. You have to come up with new ideas. But there are days when they don’t come. And that is frustrating. So, I would say that coming up with new approaches is the most challenging part of working as a researcher.
What do you find the most promising/exciting as a researcher?
If you work as a researcher, you can still be a child. You play with new things. You analyze them. You can ask, “Why?” and “How?” You HAVE to explore new things. Read about them and learn.
Constant learning – that is the most exciting part of working as a researcher.