Prof. Yusuf Uzzaman Khan

    D.Phil., M. E.




    Signals and Systems, Digital Signal Processing, Control Systems, Artificial Intelligence and Neural Networks, Biomedical Engineering


    Electrical Engineering Department, Z H College of Engg & Tech., AMU




    Time TableTime Table 2021-22


Yusuf Uzzaman Khan is a Professor in Electrical Engineering Department since 2012. He is  the Coordinator of Centre of Interdisciplinary Biomedical and Human Factors Engineering from 2018 onwards. 

He received his D.Phil. from University of Oxford, UK in Trinity term 1997 as a Felix Scholar and Master of Engineering in Electrical Engineering from University of Roorkee in 1993.  During 1994-1997 he was awarded  Felix Scholarship to study at University of Oxford. He was awarded with the University medal for securing First position in Master of Engineering in Electrical Engineering.

During 2017-18, he was a Shastri Fellow to McGill University, Canada under Indo-Canada Shastri Mobility Program and in 2008-2009 he was a visiting researcher to McGill University. In 2007-2008 he was a Commonwealth Academic Fellow to Essex University, UK.

To further explore the research work done during his post-doctoral work, he was a visiting scientist to Montreal Neurological Institute in the summer of 2000 and 2001. From 1999  till end of 2000 he was Post-Doctoral Fellow at Montreal Neurological Institute, Montreal, Canada.

He is an avid researcher. His research interests lie in the area of signal processing, control systems, biomedical engineering, artificial intelligence, neural networks and wavelets.  He has collaborated actively with researchers in disciplines of biomedical engineering, particularly on problems related to biomedical signals.

He is a senior member of IEEE, Fellow of IETE, Life Member of IES.

  1. Key Publications
    • A. T. Khan, Y. U. Khan, “Time domain based seizure onset analysis of brain signatures in pediatric EEG”, Int. Journal of Information Technology, 2021.
    • Kashif A Khan, M Shanir P. P., Yusuf Uzzaman Khan, Omar Farooq, “A hybrid local binary pattern and Wavelets based approach for EEG classification for diagnosing epilepsy”, Expert Systems With Applications, Vol. 140, 2020.
    • G. Chandel, P. Upadhyaya, O. Farooq, Y U Khan, “Detection of Seizure event and its onset/offset using Orthonormal Triadic Wavelet Based Features”, IRBM - Innovation and Research in BioMedical Engineering, Vol. 40, issue 2, p 103-112, 2019..
    • Muhammed Shanir P P, Sadaf Iqbal, Yusuf U. Khan, Omar Farooq, "Feature Extraction using Pythagorean Means for Classification of Epileptic EEG Signals", International Journal of Biomedical Engineering and Technology, Vol. 28, issue 3, p243-260, 2018
    • Ayesha Tooba Khan, Yusuf Uzzaman Khan, “Dual tree complex wavelet transform based analysis of epileptiform discharges”, International Journal of Information Technology, Springer, p543-550, April 2018.
    • Muhammed Shanir P P, Kashif Ahmad Khan, Yusuf Uzzaman Khan, Omar Farooq, Hojjat Adeli, “Automatic seizure detection based on morphological features using one dimensional local binary pattern on long term EEG”, Clinical EEG and Neuroscience, p1-12, Dec. 2017.
    • Garima Chandel, Mohammad Shanir P.P., Omar Farooq, Yusuf Uzzaman Khan, “A simplified method for classification of epileptic EEG Signals”, International Journal of Biomedical Engineering and Technology, Vol. 25, No. 1, p60-76, 2017
    • Sadaf Iqbal, Yusuf Uzzaman Khan, Omar Farooq, “EEG analysis of Imagined Speech”, International Journal of Rough Sets and Data Analysis (IJRSDA), Vol. 3, No. 2, p32-44, Apr 2016.
    • Nidal Rafiuddin, Md. Tabrez, Yusuf Uzzaman Khan, Omar Farooq,  "Wavelet packet-based classification of brain states during English and mother tongue script writing", International Journal of Biomedical Engineering and Technology, Vol. 22, Issue 4, pp 325-337, 2016.         
    • Priyanka Sharma, Yusuf Uzzaman Khan, Omar Farooq, Manjari Tripathi, and Hojjat Adeli, " A Wavelet-Statistical Features Approach for Nonconvulsive Seizure Detection", Clinical EEG and Neuroscience, vol. 45, no. 4, p274-284, Oct 2014.
    • M. Bedeeuzzaman, Thasneem Fathima, Yusuf U Khan, Omar Farooq, “Seizure prediction using statistical dispersion measures of intracranial EEG (BSPC365)”, Biomedical Signal Processing and Control, Vol. 10, pp 338-341, March 2014.
    • Yusuf U Khan, F. Sepulveda, ‘EEG single-trial classification of different motor imagery tasks using measures of dispersion and power in frequency bands’, International Journal of Biomedical Engineering and Technology (IJBET), Vol. 8, No. 4, pp343-356, 2012.
    • Yusuf U. Khan, F. Sepulveda, Wrist Movement Discrimination in Single-Trial EEG for Brain Computer Interface using band powers, International Journal of Biomedical Engineering and Technology (IJBET), Vol. 6, No. 3, pp272-285, 2011.
    • Maeike Zijlmans, Julia Jacobs, Yusuf U. Kahn, Rina Zelmann, Francois Dubeau, Jean Gotman, Ictal and interictal high frequency oscillations in patients with focal epilepsy, Clinical Neurophysiology, Vol. 122, issue 4, pp664 – 671, April 2011.
    • Y. U. Khan, F. Sepulveda, Brain Computer Interface for single-trial EEG classification for wrist movement imagery using spatial filtering in the Gamma band,  Journal of Institution of Engineering and Technology (IET) Signal Processing, Vol. 4, Issue 5, October 2010, pp 510 – 517.
    • Yusuf U. Khan, Imagined wrist movement classification in single trial EEG for brain computer interface using wavelet packet, International Journal of Biomedical Engineering and Technology (IJBET), Vol. 4, No. 2, pg 169 – 180, 2010.
    • Cota Navin Gupta, Yusuf U. Khan, Ramaswamy Palaniappan and Francisco Sepulvada, Wavelet Framework for Improved Target Detection in Oddball Paradigms Using P300 and Gamma Band Analysis, International Journal of Biomedical Soft Computing and Human Sciences, Japan, Vol. 14, No. 2, pp 61-67, 2009.
    • Y. U. Khan and J Gotman, Wavelet based automatic seizure detection in intracerebral electroencephalogram, Journal of Clinical Neurophysiology, Vol. 114, pp. 899 – 908, 2003.
    • L. Tarassenko, Y. U. Khan, and M.R.G. Holt, Identification of inter-ictal spikes in the EEG using neural network analysis, IEE Proceedings –Science, Measurement & Technology, Vol. 145 No. 6, November 1998, pp. 270-278.