Congratulations to Vojtěch Mrázek and Martin Trneček on their appointments as associate professors!

Two new associate professors have been appointed at the Faculty of Information Technology at BUT. Vojtěch Mrázek and Martin Trnečka received their appointment decrees on Wednesday, May 20, in the Rector’s Auditorium at BUT.

B Vojtěch MrázekB delivered his public habilitation lecture at our faculty as early as late February. In it, he built upon the topic of his habilitation thesis, “Evolutionary Optimization of Neural Network Accelerators,” which accurately captures the main direction of his research in recent years. Mrázek does not focus on the design of neural networks themselves, but rather on the question of how to implement them as efficiently as possible in specific hardware—particularly where computational power and energy resources are limited. His research focuses on neural network accelerators, and he seeks ways to design their parameters so that they offer the best possible balance between performance, power consumption, and computational accuracy. Evolutionary algorithms play a key role in his work. He recently built on his research to date by winning the prestigious GA ČR Junior Star grant.

The second associate professor appointed at FIT VUT is Martin Trnečka. He delivered his habilitation lecture, “Boolean Matrix Factorization,” at our faculty in March. He earned his Ph.D. in 2017 at the Faculty of Science, Palacký University in Olomouc, where he continues to work at the Department of Computer Science. His research focuses on data analysis, particularly Boolean matrix factorization. This method helps identify hidden structures in data expressed as 0/1 values—for example, true/false or yes/no. Such data arises whenever we examine whether a particular object has or lacks a defined property. A typical example would be records of patients and their symptoms: individual symptoms may not reveal much on their own, but their combination can point to a deeper pattern. The purpose of the factorization method is to replace a large and difficult-to-interpret matrix with a smaller number of more comprehensible factors. Trneček’s habilitation thesis specifically focuses on the development of algorithms that perform factorization more accurately and efficiently than existing methods.

We warmly congratulate both new associate professors and wish them continued success in research, teaching, and the development of new research teams.

You can read more about the research focuses of both new associate professors here.