Environmental AI
RNN, LSTM, WaveNet, TensorFlow, Python, and hybrid deep learning frameworks for climate and hydrological prediction.
About
AI climate and smart agriculture specialist with a field-to-model perspective.
My background connects agricultural engineering, climate change, hydrology, agrometeorology, water systems, GIS, and modern AI modeling for resilient food and water systems.
Profile
Research grounded in real environmental problems.
I bring more than 10 years of hands-on research and development experience from Pakistan, Thailand, and South Korea. My work focuses on turning complex climate, water, and agricultural datasets into reliable forecasts, scientific publications, decision-support tools, and practical recommendations for climate-resilient systems.
Research Identity
AI climate, hydrology, and smart-agriculture work with measurable outputs.
The portfolio brings together publication records, model workflows, research services, international collaborations, and applied dashboard systems in one cleaner professional profile.
48 Papers
10+ Years
8 Collaboration regions
Expertise
Research and technical strengths
Climate and Weather
Precipitation forecasting, climate variability, CMIP6 analysis, ENSO impacts, downscaling, and numerical weather models.
Agricultural Engineering
Irrigation and drainage, crop water requirements, greenhouse water systems, composting, and sustainable agriculture.
Data and GIS
Hydrological data analysis, QGIS, statistical modeling, ANOVA, SPSS, decision trees, random forests, and research workflows.
Education
Academic background
Doctorate in Environment, Climate Change, and Sustainability
King Mongkut's University of Technology Thonburi, Bangkok, Thailand
Master of Agricultural Engineering
Bahauddin Zakariya University, Multan, Pakistan
Bachelor of Agricultural Engineering
Bahauddin Zakariya University, Multan, Pakistan