Mahmoud Keshavarzi


My research involves designing paradigms for EEG and MEG experiments, programming them, and analysing the data, as well as testing children using both kinds of brain imaging equipment.

Research Focus


Auditory neuroscience

Brain stimulation


Artificial intelligence

Signal processing

Clinical conditions


Hearing and balance deficits

Language disorders


Electroencephalography (EEG)


Transcranial alternating current stimulation



Usha Goswami

Associated News Items

    Key publications

    Keshavarzi M, Kegler M, Kadir S, Reichenbach T (2020), “Transcranial alternating current stimulation in the theta band but not in the delta band modulates the comprehension of naturalistic speech in noise” NeuroImage 210: 116557

    Keshavarzi M, Goehring T, Zakis J, Turner RE, Moore BCJ (2018), “Use of a deep recurrent neural network to reduce wind noise: effects on judged speech intelligibility and sound quality” Trends in hearing 22: 2331216518770964



    Keshavarzi M, Reichenbach T (2020), “Transcranial alternating current stimulation with the theta-band portion of the temporally-aligned speech envelope Improves speech-in-noise comprehension” Frontiers in human neuroscience 14


    Goehring T, Keshavarzi M, Carlyon RP, Moore BCJ (2019), “Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants ” The Journal of the Acoustical Society of America 146(1): 705-18

    Keshavarzi M, Goehring T, Turner RE, Moore BCJ (2019), “Comparison of effects on subjective intelligibility and quality of speech in babble for two algorithms: A deep recurrent neural network and spectral subtraction” The Journal of the Acoustical Society of America 145(3):1493-503


    Keshavarzi M, Baer T, Moore BCJ (2018), “Evaluation of a multi-channel algorithm for reducing transient sounds” International journal of audiology 57(8): 624-31