Miroslav Strupl

Miroslav Strupl is affiliated with the Department of Innovative Technologies at SUPSI. He holds a PhD in Electrical Engineering Theory (2007) and a Bachelor's in General Mathematics (2010) from Charles University, alongside a Computer Science engineering degree from Czech Technical University (2002). His professional career includes roles such as Assistant Professor at CTU (2004-2016), followed by research scientist positions at NNAISENSE (2019-2020), US Research (2017-2018), and RTSmunity (2016-2017). His expertise focuses on Bayesian methods, reinforcement learning, parallel algorithms, and hardware architecture design.

Education:

• Czech Technical University in Prague, FEE: Ing (Computer Science and Engineering, 2002)
• Czech Technical University in Prague, FEE: PhD (Electrical Engineering Theory, 2007)
• Charles University in Prague, MFF: Bc (General Mathematics, 2010)

Research emphasizes theoretical and applied aspects of probability theory, machine learning, and computational systems. Though no specific publications are listed, his professional trajectory indicates contributions to AI and algorithmic research.

Grants and lab affiliations are not detailed in the provided texts.