Doc. dr Predrag Tadić
Assistant Professor
University of Belgrade
School of Electrical Engineering
Signals and Systems Department
Computer center, room RC-7
tel: (011)3218-397
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CURRICULUM VITAE
Predrag R. Tadić got his Dipl. Ing. degree in 2005, Magister Diploma in 2009 and PhD in 2015, all from the Department of Signals and Systems, School of Electrical Engineering, University of Belgrade. He graduated in the field of Robust Control and did his magister studies on Speech Processing. The focus of his PhD studies was the application of particle filters to fault diagnosis problems.
As a PhD student, he has attended courses on "Model Predictive Control" (2009) and "Cooperative Control of Multiple Autonomous Vehicles" (2010) organized by the HYCON-EECI Graduate School of Control in Paris, France. More recently, he has participated in the 2018 Transylvanian Machine Learning Summer School organized by DeepMind in Cluj-Napoca, Romania.
After graduating, he worked in the field of Heating, Ventilation and Air Conditioning, programming PLC controllers and SCADA applications. Since 2007 he is with the Signals and Systems Department at the Faculty of Electrical Engineering, University of Belgrade, where currently holds an assistant professor position. He has taken part in several research and development project, mainly focused on the design and implementation of automatic regulation and fault diagnosis algorithms in two thermal power plants in Serbia (TENT and TEKO), and on the development of simulators and autopilots for guided missiles. More recently, he has led several projects related to various applications of Machine Learning.
His teaches undergraduate courses in Signals and Systems, Stochastic Systems and Estimation, Spectral Estimation, Artificial Intelligence, and Automatic Guidance of Objects in Space. He also teaches a postgraduate course in Machine Learning, which he introduced. He has previously taught courses in Automatic Control Systems, Digital Signal Processing, Speech Recognition and Processing, Real-Time Programming, Soft Computing Methods, and Optimal Control.
His main research interests are Machine Learning, Artificial Intelligence, and Statistical Signal Processing. He has published more than 30 scientific papers (selected bibliography available here).
