Dr. Muhammad Fayyaz is serving as an Assistant Professor in Department of Computer Science, FAST – National University of Computer and Emerging Sciences (NUCES), Chiniot-Faisalabad Campus, Punjab, Pakistan since January 2022. His responsibilities Include teaching at undergraduate/graduate level, research/creative work, thesis/project supervision, student’s guidance/counseling, administrative activities, and co/extra-curriculum activities of university. Prior to that, he was being affiliated with COMSATS University Islamabad (CUI), Wah Campus, Pakistan, as Lecturer in department of Computer Science from September 2014 to January 2022. During stay at CUI, he was fulfilling several academic and administrative duties along with teaching and research including 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 session management committee (FIT Conference) and many other events. He has also served as SST (Computer Science) in Punjab Education Department, Sargodha District from September 2009 to August 2014. He has an overall job experience (teaching + research) of 13 years both at undergraduate and graduate levels.
Dr. Muhammad Fayyaz received his Ph.D. in Computer Science in September 2021 from COMSAT University Islamabad, Pakistan during which he remained a very active research member of fields related to Pedestrian Analysis, Computer Vision and Pattern Recognition. Overall, he has published four impact factor papers in journals of international repute with cumulative impact factor 17+. His areas of interest are image processing, deep learning, computer vision, and natural language processing. He has supervised/co-supervised 3 MSCS and more than 25 R&D projects of BSCS/BSSE/MCS students. He is reviewer of several prestigious journals and conferences. Besides teaching and research activities, he is also remained active in handling the administrative tasks and completed them as well with success. He is active member of research group named computer vision and intelligent system (CVIS). My objectives are (1) to improve students’ behavior and to instill students with intrinsic motivation to learn, and (2) to pursue career in a progressive organization that opens new vistas of broadening my knowledge and supports me to reach the zenith of professionalism in teaching and research.
Natural Language Processing
- PhD [Philosophy of Doctorate] Computer Science (Sep, 2021), Department of Computer Science, COMSATS University Islamabad (CUI), Wah Campus, Punjab, Pakistan
- M. Ed [Master of Education] (Feb, 2015), Department of Education, University of Sargodha, Punjab, Pakistan (1st Position, Gold Medal)
- MS (CS) [Master of Science in Computer Science] (April, 2014), Department of Computer Science, University of Sargodha, Punjab, Pakistan (2nd Position)
- B. Ed [Bachelors in Education] (Jan, 2012), University of Sargodha, Punjab, Pakistan
- MCS [Master of Computer Science] (June, 2007), Department of Computer Science, University of Sargodha, Punjab, Pakistan
- BCS [Bachelors in Computer Science] (Aug, 2003), Allama Iqbal Open University (AIOU) Islamabad, Pakistan
- Intermediate [Diploma of Associate Engineer] (June, 1999), Punjab Technical Board Lahore, Punjab, Pakistan
- Matriculation [Secondary School Certificate] (May, 1995), BISE Sargodha, Punjab, Pakistan.
1. 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 (2021). [Impact Factor 2.258, Q2]
2. 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.
3. 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 Applications 33 (2021): 361-391. [Impact Factor 5.606, Q1]
4. 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 (2020): 1-26. [Impact Factor 4.350, Q2]
5. 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. [Impact Factor 5.606, Q1]
Muhammad Fayyaz*, Mussarat Yasmin, Muhammad Sharif, Tassawar Iqbal, and Mudassar Raza. “Pedestrian gender classification on imbalanced and small datasets using fusion of deep and traditional features.” (2021). [Under Review]