Alireza Malekmohammadi is a doctoral student at the Technical University of Munich (TUM), Department of Electrical and Computer Engineering. He is working on "Brain Sound Computer Interface" (Deep/Machine learning methods to decode sound sequences from the human brain) at the Institute for Cognitive Systems (ICS). He received his bachelor’s degree in “Electrical Engineering” under the supervision of Prof. Mohammad Eshghi from Shahid Beheshti University, Tehran, Iran, in 2013. In 2015, he was awarded his M.Sc. degree in “Digital Electronics Engineering” from Sharif University of Technology. During his master's, he attended the Brain-Computer Interface (BCI) group, under the supervision of Prof. Mahdi Shabany, developing an efficient design and hardware implementation machine learning methods (i.e., SVM, LDA, KNN, ANN) for a BCI system based on motor imagery on a Virtex-6 FPGA. From 2017 till 2018, he spent one year as a research assistant at Tuebingen University in Germany, where he studied the effects of intra-operative monopolar deep brain stimulation of the subthalamic nucleus on cortical physiology in Parkinson’s disease. He joined ICS in 2018 and is now working on signal processing and machine/deep learning algorithms to map neural activity recorded by EEG with music/speech stimuli.
Signal processing (EEG, LFP, MEG)
Implementation of Biomedical Signal Processing Algorithms
Alireza Malekmohammadi, Stefan K Ehrlich, Gordon Cheng: Modulation of theta and gamma oscillations during familiarization with previously unknown music. Brain Research 1800, 2023 mehr…BibTeX
Alireza Malekmohammadi, Stefan K. Ehrlich, Josef P. Rauschecker and Gordon Cheng: Listening to familiar music induces continuous inhibition of alpha and low-beta power. JNP Journal of Neurophysiology Volume 19 (6), 2023, 1344-1358 mehr…BibTeX