Funded Projects
| Project Title: | Lean Integrated Management System (LIMS) Implementation in Public Sector Maintenance, Repair, Overhaul (MRO) Organizations |
| Members: | Dr Yasir Ahmad, Engr Muhammad Mohsin Khan, Engr Fatima |
| Project Abstract: | A major project is currently underway in Pakistan’s MRO (Maintenance, Repair, and Overhaul) sector with the implementation of a modern and advanced Quality Management System (QMS), a complete framework designed to ensure high-quality maintenance, repair, and overhaul services. Developed in line with three well-known international standards – ISO 9001, ISO 14001, and ISO 45001 – this funded project is being rolled out across 17 important installations across the country. With an investment of around PKR 20 million, this ongoing project is set to improve the MRO sector by promoting better quality, greater efficiency, and stronger focus on sustainability. By adopting global best practices, Pakistan’s MRO sector is moving toward setting new standards of quality and reliability. |
| Project Title | Integrated Decision Support System for optimizing Public Procurement process in Pakistan (16062) |
| Member | Dr Afshan Naseem |
| Project Abstract | Secured Rs.11.1 million worth funding support from Higher Education Commission (HEC) Pakistan as Principal Investigator under National Research Program for Universities (NRPU) | 2022 |
| Project Title | Developing a Machine Learning based Software for Choosing Diverse Teams for Biomedical Research Projects |
| Member | Dr Asjad Shahzad |
| Project Abstract | This endeavour will benefit academia and the education sector. Biomedical departments (universities) and research centres would select efficient project teams, that shall ensure that projects shall be completed within the allocated budget. Most institutions conduct biomedical research projects by appointing just departmental team members, mostly sharing the same knowledge base and abilities. As a result, this does not fully benefit the projects regarding biomedical research. In biomedical research projects, the technical aspect is usually stronger than the management aspect. Concerning this, the software will assist the project team in forming a team that will not only stop them from overbudgeting but also foster better communication and learning |
| Project Title | Development of Environmental Assessment Matrix using Hybrid Machine Learning Approach for Manufacturing industry |
| Member | Dr Asjad Shahzad |
| Project Abstract | The environmental assessment matrix will quantify the impacts of cement manufacturing processes and products in terms of carbon emissions. 2. The ML and AI techniques shall be used on the LCA data with regard to the severity of causes and their impact on the environment in terms of carbon emissions, which shall result in proposing carbon abatement strategies. 3. Scenario Analysis: LCAs facilitate scenario analysis to assess the potential environmental benefits of adopting alternative technologies, materials, or production practices within the cement industry. |
| Project Title | Developing a Software Module for Selecting Diverse Teams for Cost-Effective Biomedical Projects Using Support Vector Machine Technique |
| Member | Dr Asjad Shahzad |
| Project Abstract | Biomedical research projects aim to develop and commercialize products. Despite initial cost estimations, actual costs often exceed these estimates, leading to over-budgeting and incomplete projects. This reduces product cost-effectiveness and makes them too expensive for customers. To address this, using a diverse team in these research projects is proposed. Currently, these research teams are often homogenous, typically consisting only of engineers. By forming diverse teams, over-budgeting is proposed to be mitigated, which leads to more cost-effective and competitively priced products accessible to hospitals and patients. |
| Project Title: | AI-Powered Web Portal and Crowdsourced Mobile App for Real-Time Telecom Performance Monitoring in Pakistan |
| Members: | Dr. Sundus Younis |
| Project Abstract: | Pakistan’s telecommunication sector faces persistent mobile network quality issues, with a disconnect between regulatory reports and actual user experiences due to potential network manipulation. This research proposes an AI-powered web portal that aggregates official QoS data, crowdsourced metrics from platforms like Opensignal, and user-generated data from a dedicated mobile app. By employing machine learning to analyze trends and detect manipulation, the portal will provide real-time, geo-referenced insights for consumers, regulators, and operators, enhancing transparency and improving network quality in Pakistan’s digital economy. |