GAWDIYA SANDEEP

Presentation

Dr. Gawdiya’s research focuses on nutrient-use efficiency, soil–plant interactions, biochar-based soil enhancement, and climate-resilient agronomy. With a strong background in field experimentation, stress physiology, and advanced data-driven modeling, his work bridges traditional agronomy with modern machine learning, remote sensing, and systems-level crop prediction.

His current research integrates multi-season field trials, soil amendments, crop physiology, and predictive analytics to identify strategies that enhance productivity, resource-use efficiency, and sustainability in cereal-based systems, particularly in rice and wheat across diverse Indian agroecologies. Dr. Gawdiya is also increasingly engaged in AI-enabled agronomy—developing ML models for yield prediction, genotype evaluation, and environment–management interactions.

Growing up in the arid regions of Rajasthan, he brings a soil-centric perspective to agricultural resilience. His activities span experimental research, model development, and collaborative work with students and research teams to advance climate-smart, farmer-focused solutions. Across his projects, Dr. Gawdiya emphasizes practical technologies, data-driven insights, and sustainable approaches that improve soil health, crop performance, and long-term agroecosystem stability.

What I can bring to this network ?

Expertise in agronomy, soil–plant interactions, and AI-driven systems analysis of agricultural systems. Contributions include data-driven tools, predictive modelling workflows, educational material, and practical methods for sustainable crop and soil management.

What I seek in this network ?

Engagement with researchers and educators working on simulation modelling, digital agronomy, and systems analysis, along with opportunities to learn new tools, datasets, and pedagogical approaches that support AI-enabled, data-driven agricultural research.