Research

Research Projects Approved for Funding:

Sr. No.Title of Research ProposalName of PIName of Co-PIName of Research GrantDurationAmount
1Automatic Meeting Minutes and Analytics Generation for UrduDr. Farah AdeebaMs. Sana ShamsHEC TTSF2 Year17 Million PKR
2A graph-based model for detecting malware in Windows environmentDr. Irfan Yousuf______Korea Institute of Science and Technology (KIST), South Korea1 Year1.5 Million RS. (approx.)
3A Smart Interactive Solution for Soil Type Identification using Remote Sensing Data and Machine Learning TechniquesProf. Dr. Muhammad ShahbazProf. Dr. Shahzad AsifHEC NRPU3 Years7 Million RS.

Research Projects Completed:

Sr. No.Title of Research ProposalName of PIName of Co-PIName of Research GrantDurationAmount
1A Multi-Modal Approach for Enhanced Crop Monitoring using Remote Sensing and Machine LearningProf. Dr. Shahzad AsifProf. Dr. Muhammad ShahbazMicrosoft AI4Earth1 YearUSD 15000/-
2Using Artificial Intelligence to identify the Soil Types in Pakistan.Prof. Dr. Muhammad ShahbazProf. Dr. Shahzad AsifMicrosoft AI4Earth1 YearUSD 10000/-
3Crop Yield Forecasting using Satellite and Land DataProf. Dr. Shahzad AsifProf. Dr. Muhammad ShahbazHEC NRPU3 Years3 Million RS.

Publications of the Department (In the Last Five Years):

YearHEC Recognized International
Journal Publications
HEC Recognized
Local Publications
Conference
Publications
Total
Publications
2022130316
2021201122
2020120113
201940913
20184004

Research Projects Completed by our Students:

Sr. No.StudentsSupervisorCo-SupervisorTitle of the ProjectKey FeaturesLink
1Muhammad Tayyab
(2018-CS-623)

Muhammad Ahmad Khan
(2018-CS-615)

Muhammad Bilal 
(2018-CS-610)
Mr. Zeeshan RamzanProf. Dr. Shahzad AsifA Smart Crops Monitoring System based on Remote Sensing & Machine LearningThis system offers a Web-based Decision Support System (DSS) for crop monitoring which includes:

• Area estimation of crops in acres or square meters using embedded Azure Map.
• Both Manual and automated yield prediction by polygon drawn by users on Azure Map embedded on the system
• Data visualization of data sets collected from the fields of the tea crop

Agricultural policy makers at various levels can perform these tasks remotely without going into the fields with high accuracy and save all the land survey costs.
Crop Monitoring System