Engr. Dr. Muhammad Hanif

Dr. Muhammad Hanif
Ext: 2504

Engr. Dr. Muhammad Hanif

Assistant Professor

Qualifications: Ph. D. Australian National University, Canberra (2015)
Research Interests: Image Deconvolution, Sparse Image and Signal Representation, Image and Video Compression, Image Restoration, Registration and Segmentation, Object Detection and Tracking


Dr. Hanif pursued his Ph.D. degree (Jun. 2011 – Jun 2015) in Computer Vision from College of Engineering and Computer Science, Australian National University (ANU), Canberra, Australia. He was associated with Computer Vision and Robotics research group (ANU) and National ICT Australia (NICTA) Canberra Labs, now known as DTAT61. I am privileged to be working under the mentoring of Professor Dr. Abd-Krim Seghouane at ANU and University of Melbourne. During his Ph. D. studies, the research focus of Dr. Hanif was mainly on blind image deconvolution and sparse image processing.  Specifically, his thesis outlined some novel information geometric based approaches for blind image deconvolution and optimized dictionary learning methods for sparse image modeling.

Dr. Hanif was invited under the “Visiting Professorship” program to the Information Technology Centre, University of Tokyo (Japan) in 2022. He worked with Prof. Dr. Hill H. Kobayashi in his bio autistic research lab.

Dr. Hanif is the recipient of the European Research Consortium for Informatics and Mathematics (ERCIM) fellowship (Jan 2017 – Nov 2019) for his postdoc at Italian National Research Council (CNR), Pisa, Italy. Dr. Hanif was associated with Signals and Images Laboratory, Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”, Pisa. During his postdoc, Dr. Hanif mainly worked on sparse signal representation based approaches to address ancient manuscripts restoration, retrieval and classification.

In 2010, Dr. Hanif received TUBITAK fellowship from the Scientific and Technological Research Council of Turkey to work as visiting researcher with Prof. Dr. Gozde Unal on brain image registration at Engineering and Natural Sciences, Sabanci University, Istanbul (Turkey).

Dr. Hanif completed his M.Sc degree (Aug 2007 – Aug 2009) in Information Technology with specialization in Signal Processing from the Department of Signal Processing, Faculty of Engineering Sciences at Tampere University of Technology, Tampere, Finland. His master thesis, which was part of a joint funded project from European Union (EU), focused on the digital image processing applications in paper industry. Specifically, in his thesis he outlined the three dimensional (3D) reconstruction of fiber flocs from two orthogonal views. The reconstructed 3D flocs model is then used to get the statistical analysis like volume, dimensions, shape, and flow direction of flocs during the paper making process. The findings of his thesis were published in Journal of Engineered Fibers and Fabrics (JEFF).  After completing his master studies, he served as Researcher in Faculty of Engineering, Tampere University of Technology.

Research Interests

  • Sparse Image Processing
  • Dictionary learning
  • Image deconvolution
  • Surveillance systems
  • Statistical Signal & Image Processing
  • Text and data mining
  • Deep learning

Prior to joining the GIK Institute, Dr. Hanif  served as Visiting Staff and course tutor at School of Engineering, University of Melbourne, Melbourne (Australia). In 2013 during his Ph. D. studies, he was part of the Florey Institute of Neuroscience and Mental Health, Melbourne (Australia) as visiting researcher. He also served as Researcher at Faculty of Engineering Sciences, Tampere University of Technology, Tampere (Finland). Dr. Hanif also served as Lecturer at Electrical and Computer Engineering Department, COMSATS University, Islamabad (2007 – 2009).

Funded Research Projects

  •  Artificial Intelligence Based Portable Microscopic Urine Sediment Analysis System. (Dec, 2022 – Dec-2025) Funding Agency: Pakistan Science Foundation (PSF) and TUBITAK. Role: Principal Investigator (PI). Amount: PKR 50 million
  •  AI Based Water Resource Management and Crop Health Monitoring (Oct, 2023 – Nov, 2025). Funding Agency: HEC NRPU. Role: Co-PI. Amount: PKR 5.8 million
  •  Target Tracking from Up Above the Sky (Mar 2019 – Mar 2021) Funding Agency: HEC NRPU. Role: Co-PI. Amount: PKR 2.6 million
  •  Data Mining for Automatic Data Retrieval of Judicial Data (Jan, 2018 – July, 2018) Role: Research Associate. Amount: AUD 0.85 million
  • Electoral Data Mining (Aug, 2018 – Feb, 2019). Funding Agency: Research School of Economics, Australian National University. Role: Research Associate. Amount: AUD 0.22 million
 Research Collaborations

Professional Affiliations

  • Registered MemberAustralian Computer Society. (Jan, 2014 – to-date)
  • ReviewerIEEE Transaction on Signal Processing (May, 2018 – to-date)
  • ReviewerJournal of Imaging (Feb2018 – to-date)
  • ReviewerIEEE Transactions on Image Processing (Feb, 2015 – Nov, 2016)
  • Review CommitteeIEEE Intl. Workshop on Statistical Signal Processing 2014
  • Student MemberIEEE Signal Processing Society (2012 – to-date)
  • Registered MemberPakistan Engineering Council (2006 – to-date)
  • Organizing CommitteeIEEE Intl. Multitopic Conference (INMIC)
Research Publications

  1. Usman.H, Hanif, M., Rashid, A., Aurengzeb, K. Discriminative Dictionary Learning using Penalized Rank-1 Approximation for Breast Cancer Classification with Imbalanced Dataset. IEEE Access, vol. 12, pp. 5837-5850, 2024, doi: 10.1109/ACCESS.2023.3347339. (IF. 3.9)
  2. Usman.H, Hanif, M., Rashid, A. Ajmal, S. EEG-based Schizophrenia Classification using Penalized Sequential Dictionary Learning in the Context of Mobile Healthcare. Biomedical Signal Processing & Control, Vol. 90, 2024. https://doi.org/10.1016/j.bspc.2023.105856. (IF. 5.06)
  3. Usman.H, Hanif, M., Rashid, A. Dictionary-enabled efficient training of ConvNets for image classification. Image and Vision Computing, Volume 135, 2023 https://doi.org/10.1016/j.imavis.2023.104  (IF. 4.7)
  4. Hanif,M., Tonazzini, A., Hussain, S.F., Khalil, A., Habib,U. Restoration and Content Analysis of Ancient Manuscripts via Color Space based Segmentation. PLoS ONE 18(3), 2023 doi.org/10.1371/journal.pone.0282142 (IF. 3.75)
  5. Hanif, M., Tonazzini, A., Hussain, S.F. et al. Blind bleed-through removal in color ancient manuscripts. Multimed Tools Appl 2022. https://doi.org/10.1007/s11042-022-13755-6 (IF. 3.6)
  6. Usman, H, Waqas, M.,Hanif, M. Network load prediction and anomaly detection using ensemble learning in 5G cellular Network. Computer Communications,2023. https://doi.org/10.1016/j.comcom.2022.10.017 (IF. 6.0)
  7. Ahmad, W., Ansari, S., Hanif, M. PCA drivenmixed filter pruning for efficient convNets. PLoS ONE Vol. 17(1) 2022: https://doi.org/10.1371/journal.pone.0262386.(IF. 3.75)
  8. Khan, S.U.,Nazir, B. Hanif, M., et al – Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing. Computers, Materials Continua 2022, 71(3). https://doi.org/10.32604/cmc.2022.020852.(IF. 3.86)
  9. Hussain, S.F.,Butt, I.A. Hanif, M..-Clustering Uncertain Graphs Using Ant Colony Optimization (ACO).Neural Computing and Applications, 34(14). https://doi.org/10.1007/s00521-022-07063-1 (IF. 5.60)
  10. Ullah, F., Ansari, S., Hanif, M., et al – Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net. Sensors 2021, 21(22), 7528; https://doi.org/10.3390/s21227528 (IF. 3.9).
  11. Rashid, S.N., Hanif, M., et al – Early-Stage Segmentation and Characterization of Brain Tumor. Computers, Materials / Continua 2022, 73(1), https://doi.org/10.32604/cmc.2022.023135(IF. 3.86)
  12. Khan, S.U., Islam, N., Hanif, M., et al – A machine learning-based approach for the segmentation and classification of malignant cells in breast cytology images using gray level co-occurrence matrix (GLCM) and support vector machine (SVM). Neural Comput / Applic 34, (2022). https://doi.org/10.1007/s00521-021-05697-1. (IF. 6.00)
  13. F. Ali, H. Ahmad, S. Ansari, Hanif, M., et al – Detection of subclinical rheumatic heart disease in children using a deep learning algorithm on digital stethoscope.. BMJ Open 2021. doi: 10.1136/bmjopen-2020-044070. (IF. 3.09)
  14. S. Tu, M. Waqas, Q. Lin, Hanif, M., et al – Tracking area list allocation scheme based on overlapping community algorithm. Computer Networks, https://doi.org/10.1016/j.comnet.2020.107182.(IF. 5.6)
  15. Hanif, M.,Tonazzini, A., Savino, A. and Salerno, E. – Non-local Sparse Image Inpainting for Document Bleed Through Removal. Journal of Imaging, Vol. 4(5), 68; https://doi.org/10.3390/jimaging40500682018.(IF. 3.2)
  16. S. Tu, M. Waqas, Y. Meng, Hanif, M., et al- Mobile fog computing security: A user-oriented smart attack defense strategy based on DQL. Computer Communications, 160, https://doi.org/10.1016/j.comcom.2020.06.019.(IF. 6.0)
  17. J. Wan, M. Waqas, S. Tu, S. M. Hussain, Hanif, M., et. al. An Efficient Impersonation Attack Detection Method in Fog Computing Computers, Materials / Continua 2021, 68(1), https://doi.org/10.32604/cmc.2021.016260.(IF. 3.86)
  18. J.Larkomaa, M.Honkanen, Hanif, M., J.Niinimaki, P.Saarenrinne- (2009) Effect of Fibre Properties on Flocculation and Fractionation of Cellulosic Fibres in Dry State. Journal of Engineered Fibers and Fabrics, Vol.4 (IF. 2.9).
  19. Hanif, M., Anna Tonazzini, Pasquale Savino, and Emanuele Salerno Blind Bleedthrough Removal in Color Ancient Manuscripts Using GMM Based Segmentation. Int. Journal on Document Analysis and Recognition (IJDAR), -2019
  20. Hanif, M., Anna Tonazzini, Pasquale Savino, Emanuele Salerno, Greg Tsagkatakis – Document Bleedthrough Removal using Sparse Image Inpainting. IAPR Document Analysis Systems (DAS), 2018
  21. Franca Debole, Hanif, M., Anna Tonazzini- A First Step towards NLP from Digitized Manuscripts: Virtual Restoration. IEEE Machine Learning and Natural Language Processing, 2018. (Best Paper Award)
  22. Hanif, M., Anna Tonazzini- Sparse Representation Based Inpainting for Bleed-Through Restoration. European Signal Processing Conference 2017 (EUSIPCO).
  23. A. K. Seghouane and Hanif, M.– A Sequential Dictionary Learning Algorithm with Enforced Sparsity. IEEE Int. Conference on Acousics Speech and Signal Processing (ICASSP) 2016, pp. 3876-3880.
  24. Hanif, M. Non-local Noise Estimation for Adaptive Image Denoising. Int. Conference on Digital Image Computing Techniques and Applications, (DICTA- 2015)
  25. Hanif, M. and A. K. Seghouane –Blind Image Deblurring Using Non-negative Sparse Approximation.IEEE Int. Conference on Image Processing (ICIP-2014)
  26. Hanif, M.and A. K. Seghouane- An E?ective Image Restoration using Kullback- Leibler Divergence. IEEE Int. Conference on Image Processing (ICIP-2014)
  27. Hanif, M. and A. K. Seghouane- Maximum Likelihood Orthogonal Dictionary Learning. IEEE Int. Workshop on Statistical Signal Processing (SSP-2014)
  28. Hanif, M. and A. K. Seghouane- An EM Based Hybrid Fourier Wavelet Image Deconvolution Algorithm. IEEE Int. Conference on Image Processing (ICIP-2013)
  29. A. K. Seghouane and Hanif, M.– A Kullback-Leibler Divergence Approach For Wavelet-Base Blind Image Deconvolution. IEEE MLSP-2012
  30. Hanif, M. and A. K. Seghouane- An EM Based Hybrid Fourier Wavelet Image Deconvolution Algorithm. IEEE Int. Conference on Image Processing (ICIP-2013) pp. 591-595. doi:10.1109/ICIP.2013.6738122.
  31. A. K. Seghouane and Hanif, M.– A Kullback-Leibler Divergence Approach For Wavelet-Base Blind Image Deconvolution. IEEE Int. Workshop on Machine Learning for Signal Processing, (MLSP-2012)pp. 1-5.
  32. Hanif, M. and A. K. Seghouane- Blurred Image Restoration using Gaussian Scale Mixtures Model in Wavelet Domain. International Conference on Digital Image Computing Techniques and Applications,(DICTA-2012) pp. 1-6.
  33. J.Larkomaa, M.Honkanen, Hanif, M., J.Niinimaki, P.Saarenrinne- E?ect of Fibre Properties on Flocculation and Fractionation of Cellulosic Fibres in Dry State. Journal of Engineered Fibers and Fabrics (JEFF-2009) Vol.4 Issue 4. Pages 1-10.
  34. Hanif, M. and Usman Ali- Optimized Visual and Thermal Image Fusion for E?icient Face Recognition. IEEE Int. Conference on Information Fusion (FUSION 2006) pp. 1-6

Under Review

  1. Muhammad Hanif, Anna Tonazzini, Pasquale Savino, Emanuele Salerno Blind Degradation Removal in Color Ancient Manuscripts Using Sparse Dictionary based Segmentation. International Journal on Document Analysis and Recognition- IJDAR (Submitted)
  2. Muhammad Hanif and A. K. Seghouane– Double Sparsity Revisited: Regularized Sequential Dictionary Learning. IEEE Transaction on Signal Processing (Under Review)
  3. Muhammad Hanif and A. K. Seghouane– Regularized Sequential Dictionary Learning Algorithms for Image RestorationSignal, Image and Video Processing (Under Review).

  • Research Fellow: European Research Consortium for Informatics and Mathematics (ERCIM) Fellowship (Jan 2017 – Oct 2018)
  • PhD Scholar:  Austarlian National University PhD Scholarship (Jun 2011- Jun 2015).
  • Research Scholar: National ICT Australia (NICTA)  research award (Jun 2011- Jun2015).
  • Visiting Researcher: The Scientific and Technological Research Council of Turkey (TUBITAK) research grant (2010).
  • M. Sc Scholarship: Higher Education Commission (HEC) merit scholarship (Aug 2007- Aug 2009),
  • Merit Scholarship:  Pakistan Ministry of Science merit scholarship (March 2002- March 2006).
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