Dr. Muhammad Shakeel Faridi
D.2 SOFTWARE ENGINEERINGÂ Â Â Â Software Engineering Cloud Computing and Resource Management Cloud computing security Internet of Things and AI Service science, management and engineering Food Supply Chain Traceability Business, Education, Mathematics Research Component-based software engineering Decision Support System Applications Information Retrieval and Data Mining Management information systems Cybersecurity and Information Systems Software Engineering Techniques and Practices Cloud Data Security Solutions Big Data and Business Intelligence Face and Expression Recognition ERP Systems Implementation and Impact Technology and Security Systems Selection (genetic algorithm) Modality (human-computer interaction) Software Engineering Research Accounting Artificial Intelligence Computer Networks and Communications Computer Vision and Pattern Recognition Food Science Human-Computer Interaction Information Systems Software

Bio

Dr. Muhammad Shakeel Faridi is a dedicated researcher and academic with a strong background in computer science and engineering. He has been affiliated with the University of Agriculture, Faisalabad, Pakistan, and the Department of Electrical Engineering at the University of South Asia, Lahore, Pakistan. Dr. Faridi holds an MS in Computer Science and is currently pursuing a PhD in Computer Science at the University of Agriculture. His research interests span data warehousing and data mining for decision making, software engineering, and electrical engineering applications. He has authored several notable works including 'Usability of Data Warehousing and Data Mining for Interactive Decision Making in Textile Sector' and 'High Speed Voltage Switching Converter from Single Phase to Three Phase: Design and Implementation Process'. With a total of 26 publications, 113 citations, an h-index of 7, and an i10-index of 4, Dr. Faridi has made meaningful contributions to his fields. He also serves as a reviewer for the Global Journal of Computer Science and Technology (GJCST), reflecting his active engagement in the academic community.

Educational Journey

University of Agriculture

PhD Computer Science in Department of Computer Science • Department of Computer Science

2025

MS (Computer Science)

Experience

University Of Agriculture, Faisalabad, Pakistan

0 - 0

The University of Agriculture, Peshawar

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0 - 0 • Department of Electrical Engineering

Editors Role

Reviewer

GJCST

2011 -

Research

Unsolved Tricky Issues on COTS Selection and Evaluation

Article August 22, 2012

Component Based Software Engineering (CBSE) approach is based on the idea to develop software systems by selecting appropriate components and then to assemble them with a well-defined software architecture. (CBSE) offers developers the twin benefits of reduced software life cycles, shorter development times , saving cost and less effort as compare to build own component. However the success of the component based paradigm depends on the quality of the commercial off-the-shelf (COTS) components purchased and integrated into the existing software systems. It is need of the time to present a quality model that can be used by software programmer to evaluate the quality of software components before integrating them into legacy systems. The evaluation and selection of the COTS components are the most critical process. These evaluation and selection method cannot be resolved by the IT professionals itself. In this study the author tried to compare the twenty three available systematic methods for best evaluation and selection of COTS components.

Usability of Data Warehousing and Data Mining for Interactive Decision Making in Textile Sector

Article January 1, 1970

Data warehouse is one of the most rapidly growing areas in management information system. With this approach, data for Executive Information System (EIS) and Decision Support System (DSS) applications are separated from operational data and stored in a separate database. This process is called data warehousing. The major advantages of this approach are: improved in performance, better data quality, and the ability to consolidate and summarize data from heterogeneous systems. A data warehouse is part of a larger infrastructure that includes legacy data sources, external data sources, a repository, data acquisition software, and user interface and related analytical tools. The aim of this research work is to elaborate that how the textile industry can manage and improve their production capacity and resources at optimum level to produce a good quality result using data warehousing and data mining techniques. This research work is conduction in Masood Textile Mills Limited, Faisalabad, Pakistan (MTML). The results may hopefully opened-up an era of research and methodology that could further benefit the Industry to support in decision support system.