Mathematics of Computerized Learning (MapLe)
Hoomaan received his BSc and MSc degrees in Electrical Engineering from Iran University of Science and Technology. In 2018, he also received the Graduate Student Award from the EE Department. Currently, he is a PhD student at Umeå University and also affiliated with the Wallenberg AI, Autonomous Systems and Software Program. His research interests include compressed sensing, neural networks, and optimization theory. Hoomaan's previous publications:
H. Hezave, M. Javadzadeh, M. H. Kahaei, Signal reconstruction using blind super-resolution with arbitrary sampling, in IEEE Signal Processing Letters, 2020.
H. Hezave, I. Valiulahi, M. H. Kahaei, OFDM-based sparse time dispersive channel estimation with additional spectral knowledge, in IET Communications, 2020.
Ali received his BSc and MSc degrees in Electrical Engineering from Tabriz university, Iran. Ali was recongized as Exceptional Talent and granted direct admission to graduate studies without entrance exam. He was previously an intern with Prof. Pascal Frossard at EPFL, and later a visiting researcher with Prof. Jean-Marc Vesin and Prof. Farhad Rachidi at EPFL. Currently, he is a PhD student at Umeå University and also affiliated with the Wallenberg AI, Autonomous Systems and Software Program. His research interests include statistical inference, optimization theory, machine learning and signal processing. Ali's previous works:
A. Dadras, B. Pasdeloup, Classifying non-stationary time-varying signals on graphs through their deviation from a stationary behavior: Preliminary results on EEG signals, GSP18 workshop, EPFL, 2018.
A. Dadras, A. Luca, J. M. Vesin, F. Rachidi, Localizing cardiac arrhythmia using time reversal techniques, pending patent (PCT/EP2019/081744).