Papers
2
Total Citations
11
H-Index
2
About
Nonita Sharma is a researcher at the forefront of applying machine learning to critical real-world challenges, with a primary focus on precision agriculture and natural language processing for low-resource languages. Her most cited work, "Application of Machine Learning in Precision Agriculture" (2021, 6 citations), demonstrates how ML methods can revolutionize agriculture by producing robust predictions for crop development and disease identification—a vital contribution to global food security. Sharma also pioneers novel approaches in knowledge graph construction, as evidenced by her paper "HKG: A Novel Approach for Low Resource Indic Languages to Automatic Knowledge Graph Construction" (2023, 5 citations). This work addresses the significant challenge of building semantic networks for underrepresented languages, enabling smarter AI systems for question answering, recommendation, and information retrieval. Her research bridges the gap between advanced computational techniques and practical, socially impactful applications. By tackling both agricultural sustainability and linguistic inclusivity, Sharma is making notable strides in democratizing AI technologies for diverse, resource-constrained environments.
Research Focus
Key Achievements
Top Papers
- 1Application of Machine Learning in Precision Agriculture6 citations · 2021
- 2