Dr. Mohammad Farhan Khan completed his PhD from University of Kent in Electronic Engineering, MTech and BTech from Aligarh Muslim University (India) in Electronics Engineering. Prior joining Cranfield University, Dr Khan has worked as a MHRD Fellow in Indian Institute of Technology Roorkee (India), and Postdoctoral Research Associate in an EPSRC project that was in joint collaboration between University of Warwick (PI) and University of Central Lancashire (Co-I). The expertise of Dr Khan broadly lies in computer vision, image processing, applied statistics, machine learning, mathematical modelling of biosystems and applied control theory.
Dr Khan is working as a Research Fellow in Machine Learning in the School of Water, Energy and Environment, Cranfield University. The core objective of the Innovate UK funded project is to improve animal welfare and agricultural productivity by developing an advanced artificially intelligent IoT platform for screening and diagnosing common diseases such brucellosis, mastitis, metritis in livestock.
Articles In Journals
- Ali A, Irshad K, Khan MF, Hossain MM, Al-Duais IN & Malik MZ (2021) Artificial intelligence and bio-inspired soft computing-based maximum power plant tracking for a solar photovoltaic system under non-uniform solar irradiance shading conditions - a review, Sustainability, 13 (9) Article No. 10575.
- Khan MF, Haider F, Al-Hmouz A & Mursaleen M (2021) Development of an intelligent decision support system for attaining a sustainable growth within a life insurance company, Mathematics, 9 (12) Article No. 1369.
- Khan MF, Gazara RK, Nofal MM, Chakrabarty S, Dannoun EM, Al-Hmouz R & Mursaleen M (2021) Reinforcing synthetic data for meticulous survival prediction of patients suffering from left ventricular systolic dysfunction, IEEE Access, 9 72661-72669.
- Khan MF, Spurgeon SK, Yan XG, Nofal MM & Al-Hmouz R (2021) Inbuilt Tendency of the eIF2 Regulatory System to Counteract Uncertainties, IEEE Transactions on NanoBioscience, 20 (1) 35-41.
- Khan MF, Khan E, Nofal MM & Mursaleen M (2020) Fuzzy Mapped Histogram Equalization Method for Contrast Enhancement of Remotely Sensed Images, IEEE Access, 8 112454-112461.
- Khan MF, Goyal D, Nofal MM, Khan E, Al-Hmouz R & Herrera-Viedma E (2020) Fuzzy-Based Histogram Partitioning for Bi-Histogram Equalisation of Low Contrast Images, IEEE Access, 8 11595-11614.
- Khan MF, Spurgeon S, Nofal M & Yan X (2019) Semi-Disparate Impact of Kinases GCN2 and PERK in Modulating the Dynamic Control Properties of eIF2 Pathway, IEEE Access, 7 68132-68139.
- Khan MF & Khan MA (2018) Information preserving histogram segmentation of low contrast images using fuzzy measures, Optik, 157 1397-1404.
- Khan MF, Spurgeon S & von der Haar T (2018) Origins of robustness in translational control via eukaryotic translation initiation factor (eIF) 2, Journal of Theoretical Biology, 445 92-102.
- Khan MF, Spurgeon S & Yan X (2018) Modeling and Dynamic Behavior of eIF2 Dependent Regulatory System with Disturbances, IEEE Transactions on NanoBioscience, 17 (4) 518-524.
- Khan MF, Ren X & Khan E (2015) Semi dynamic fuzzy histogram equalization, Optik, 126 (21) 2848-2853.
- Khan MF, Khan E & Abbasi Z (2015) Image contrast enhancement using normalized histogram equalization, Optik, 126 (24) 4868-4875.
- Khan MF, Khan E & Abbasi Z (2014) Segment dependent dynamic multi-histogram equalization for image contrast enhancement, Digital Signal Processing, 25 (1) 198-223.
- Khan MF, Khan E & Abbasi Z (2014) Segment selective dynamic histogram equalization for brightness preserving contrast enhancement of images, Optik, 125 (3) 1385-1389.
- Mursaleen M, Mohiuddine S, Danish Lohani Q & Khan MF (2013) Nonlinear operators on fuzzy 2-normed spaces and Fréchet derivative, Journal of Intelligent and Fuzzy Systems, 25 (4) 1043-1051.