This research investigates tropical atmospheric waves that influence rainfall, storms, and seasonal weather patterns. Using satellite observations and machine learning, the study shows that wave propagation depends on geographic location, upper-level winds, and topography. The findings can improve weather forecasting models and help communities better prepare for extreme rainfall events.

This research investigates feronia, a plant protein essential for heat adaptation. By studying how feronia regulates auxin signaling and plant growth under temperature stress, the work aims to uncover mechanisms that could support the development of heat-resilient crops, improving agricultural productivity and food security in a warming global climate.

This research transforms human urine into sustainable fertilizer using solar-powered systems that recover nutrients like nitrogen, phosphorus, and potassium. By turning toilets into decentralized fertilizer factories, the approach improves sanitation, reduces reliance on energy-intensive production, and provides affordable fertilizers to underserved farmers, supporting both environmental sustainability and economic development.

This research enhances canola productivity by reintroducing genetic diversity from related crops like cabbage and broccoli. Using embryo culture and genome-wide association studies, it identifies beneficial genetic traits that improve yield. The work addresses limitations caused by narrow breeding, supporting agricultural resilience and safeguarding a major sector of Canada’s economy.

This research improves phosphorus use efficiency in canola by identifying plant traits that unlock soil-bound nutrients. By screening varieties and targeting genetic markers, it aims to breed crops that reduce fertilizer dependence, lower costs, and minimise environmental impact, contributing to more sustainable and resilient agricultural systems.

This talk explains how climate change can increase insect-driven defoliation by raising insect activity, survival, and range expansion. It argues that defoliation threatens forests, crops, and food security, and shows how remote sensing and machine learning can help detect outbreaks early, support monitoring, and guide policy and prevention efforts.

Pakistan is highly vulnerable to climate change due to low forest cover, rising temperatures, glacier melting, floods, droughts, and agricultural decline. With only 4.2 million hectares of forest, impacts are severe. Government initiatives like the 10 Billion Tree Tsunami and mangrove restoration aim to improve resilience and environmental sustainability.

This study documented wild edible plant diversity and traditional knowledge in northern Ethiopia. Forty species were identified, mainly trees and shrubs. Knowledge varied by gender, age, and occupation, with key informants showing greater expertise. Wild plants provide critical seasonal food security but face threats from deforestation, agriculture, and overgrazing.

This research examines whether long-term organic soil management improves climate resilience. Using a 27-year field experiment, the study shows that compost and manure significantly improve soil structure, reduce compaction, and increase water retention. Results demonstrate that sustained organic practices can transform fragile soils into resilient systems for future food security.

My research uses field images to predict crop yield, leveraging machine learning techniques to extract patterns and features correlating yield.  These features include plant health indicators, growth stages,  or canopy coverage. I am particularly interested in using these features to develop models  that improve the accuracy of yield prediction, helping farmers make  data-driven decisions. My approach considers temporal changes in the crop, capturing how its characteristics evolve. My work contributes to precision agriculture, a field that seeks to optimize resource use, increase productivity, and promote sustainability in farming. My research has the potential to transform traditional agricultural practices by integrating advanced AI methods.