Muhammad Fayyaz

Assistant Professor
  • Department of Computer Science
  • m.fayyaz@nu.edu.pk
  • (041) 111-128-128
  • Ext: 160

Introduction

  • Experience:
  • Interests:
  • Date of Joining:
  • Number of Students Supervised (BS/MS/PhD):
  • H-Index:
  • Google Scholar Citations:
  • 14
  • Computer Vision, Image Analytics, NLP, Machine/Deep Learning
  • 21/01/2022
  • 6
  • 5
  • 121

Dr. Muhammad Fayyaz is currently serving as an Assistant Professor and Head of the Computer Science Department at FAST – National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan. His responsibilities encompass overseeing the overall functioning of the department, teaching at the undergraduate/graduate level, research work, thesis/FYP supervision/evaluation, student guidance/counseling, administrative activities, organizing co-chair (ICIT Pakistan 2022-2023), and member of TPC (ICIT & ICET, Pakistan 2022 and 2023), and co/extracurricular activities at the university level. Before this, he worked as a Lecturer at the Department of Computer Science COMSATS University Islamabad (CUI), Wah Campus, Pakistan, from September 2014 to January 2022. Moreover, he served as SST (Computer Science) in the Punjab Education Department, Sargodha District from September 2009 to August 2014. During his stay at CUI, he has been fulfilling several academic and administrative duties such as a member of various administrative committees (proposal/FYP project internal evaluation, scrutiny, Visio Spark, COVID rapid action force, open house & job fair), FYP undergraduate head (CS), responsible/member of the session management committee (FIT Conference) and many other events, along with teaching and research. His overall job experience both at undergraduate and graduate levels in teaching, as well as research, pertains to 14+ years. Dr. Muhammad Fayyaz received his Ph.D. in Computer Science in September 2021 from COMSAT University Islamabad, Pakistan. He remained a very active research member in fields related to Pedestrian Analysis, Computer Vision, and Pattern Recognition. Overall, he has published high-impact factor papers in journals of international repute with a cumulative impact factor of 38+ and a few articles are under review. He is leading a Machine Vision and Intelligent Systems (MVIS) research group at FAST NUCES CFD Campus. His areas of interest are digital image processing, machine/deep learning, computer vision, and natural language processing. He has supervised/co-supervised 5 MSCS students and more than 35 R&D projects for BSCS/BSSE/MCS students. He is a reviewer of several prestigious journals and conferences. Along with teaching and research activities, he remained an active member of administrative and managerial committees. His objectives are (1) to improve students’ behavior and to instill in students with intrinsic motivation to learn, and (2) to pursue a career in a progressive organization that opens new vistas of broadening knowledge and pursuing the zenith of professionalism in teaching and research.

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Education

  • Ph.D. (Computer Science), COMSATS University Islamabad, Pakistan (2021)
  • Masters (Education), University of Sargodha, Sargodha (2015) [Gold Medalist]
  • MS (Computer Science), University of Sargodha, Sargodha (2014) [Second Position]
  • Bachelors (Education), University of Sargodha, Sargodha (2012)
  • Masters (Computer Science), University of Sargodha, Sargodha (2007)
  • Bachelor (Computer Science), AIOU, Islamabad (2003)

Publications

Journals Publications

1. Mian Muhammad Talha, Hikmat Ullah Khan, Saqib Iqbal, Mohammed Alghobiri, Tassawar Iqbal, Muhammad Fayyaz. “Deep Learning in News Recommender Systems: A Comprehensive Survey, Challenges and Future Trends” Neurocomputing 126881, (2023). [IF 6.0, Q1]

2. Farhat Abbas, Mussarat Yasmin, Muhammad Fayyaz, Usman Asim. “ViT-PGC: Vision Transformer for Pedestrian Gender Classification on Small-Size Dataset” Pattern Analysis and Applications, 1-15, (2023).[IF 3.9, Q2]

3. Muhammad Fayyaz*, Mussarat Yasmin, Muhammad Sharif, Tasswar Iqbal, Mudassar Raza, Muhammad Imran Babar. “Pedestrian gender classification on imbalanced and small datasets using fusion of deep and traditional features.”Neural Computing and Applications 1-32 (2023). [IF 6.0, Q1]

4. Marryam Murtaza, Muhammad Sharif, Mussarat Yasmin, Muhammad Fayyaz, Seifedine Kadry, Mi Young Lee “Clothes Retrieval using M-AlexNet with Mish Function and Feature Selection using Joint Shannon’s Entropy Pearson’s Correlation Coefficient (JSE-PCC)” IEEE Access 10, 115469-115490 (2022). [IF 3.9, Q1]

5. Farhat Abbas, Mussarat Yasmin, Muhammad Fayyaz, Mohamed Abd Elaziz*, Songfeng Lu*, Ahmed A. Abd El-Latif. “Gender Classification using Proposed CNN-based Model and Ant Colony Optimization.” Mathematics 9(19), 2499(2021). [IF 2.4, Q2]

6. Mehshan Ahad*, Muhammad Fayyaz. “Pedestrian gender recognition with handcrafted features ensembles.” Azerbaijan journal of high performance computing, Volume 4 (1), June 2021, Pages 60-90.

7.Muhammad Fayyaz*, Mussarat Yasmin, Muhammad Sharif, and Mudassar Raza. “J-LDFR: joint low-level and deep neural network feature representations for pedestrian gender classification.” Neural Computing and Applications33 (2021): 361-391. [IF 6.0, Q1]

8. Muhammad Pervez Akhtar*, Zheng Jiangbin, Irfan Raza Naqvi, Mohammed Abdelmajeed, and Muhammad Fayyaz. “Exploring deep learning approaches for Urdu text classification in product manufacturing.” Enterprise Information Systems volume 16, issue 2, 2020. [IF 4.4, Q1]

9. Muhammad Fayyaz, Mussarat Yasmin, Muhammad Sharif, Jamal Hussain Shah*, Mudassar Raza, and Tassawar Iqbal. “Person re-identification with features-based clustering and deep features.” Neural Computing and Applications 32, no. 14 (2020): 10519-10540. [IF 6.0, Q1]

Journal Submissions (On-going)

1. Marryam Murtaza, Muhammad Fayyaz*, Mussarat Yasmin, “AIG: A large-scale dataset and robust multi-feature representation with maximum correlation-based feature fusion and matching for apparel image retrieval”  (2024). [Under Review]

2. Muhammad Ramzan, Muhammad Ramzan, Adnan Abid, Muhammad Fayyaz, Tahani Jaser Alahmadi*, Haitham Nobanee, and Amjad Rehman” A novel hybrid approach for driver drowsiness detection using a custom deep learning model.”(2024). [Under Review]

3. Mian Muhammad Talha, Hikmat Ullah Khan*, Muhammad Hamza, Ammar Saeed, Muhammad Fayyaz. “News Recommendations Based on Click Rate Feature Matrix Using Deep Learning Models”  (2023). [Minor Revision, Under Review]

Collaborations at National and International Level

[International Level]

  • I am doing collaborative research work with Usman Asim, Associate Researcher, at DeltaX, Seoul, South Korea, Dr. Muhammad Bilal, Senior Lecturer, Sunway University, Malaysia, and Dr. Muhammad Imran Babar, Assistant Professor, University of Southampton, Malaysia. We are focusing on deep learning-based models for tasks related to multi-view medical images and vision transformers for pedestrian image analysis.

[National Level]

  • I am doing collaborative research work with Dr. Tehseen Zia, Associate Professor, at COMSATS University Islamabad (CUI), Pakistan. In this collaborative work, we are investigating patch-by-patch interpretable medical images to report generation using report grounding. This work will be generally applicable in enhancing the diagnostic performance and generality of report-generating models and enabling the integration of these systems into clinical workflows.
  • I am in contact with Dr. Mussarat Yasmin, and Dr. Tassawar Iqbal Associate Professors at the Department of Computer Science, CUI, Pakistan, and Dr. Mudassar Raza, Head of Department AI/Cyber Security, HITEC University, Pakistan for collaborative research work which covers different research areas such as deep learning, computer vision, image analytics, and information retrieval.
  • I am also in contact with Prof. Dr. Hikmat Ullah Khan, and Dr. Muhammad Ramzan, Faculty of Computing and Information Technology, University of Sargodha, Pakistan for collaborative research work in which we are investigating deep learning models for social data analytics, and driver drowsiness detection.

Detail of Funded Projects

    1. Research project Title” Pose-Based Pedestrian Orientation Analysis Using Machine/Deep Learning Techniques” funded by ORIC FAST NUCES, Pakistan, (2023-24). Amount 7,00,000/- PKR [Completed]
    1. Research project Title” Assistive Technology for Elderly People with Dementia” funded by ORIC FAST NUCES, Pakistan, (2023-24). Amount 8,40,000/- PKR [Completed]
    2. At undergraduate level, he has worked on National Grassroot ICT Research Initiative (NGIRI) funded project named Water and Land Garbage Cleaner, at CUI, Wah Campus, Pakistan, during 2017-18, Amount 28,650/- PKR [Completed]