Dr. Shagun Jain is an Assistant Professor and Ph.D. researcher in Computer Science with a strong interdisciplinary focus on artificial intelligence for smart agriculture, soil science, and remote sensing. She combines academic excellence with industry experience as a former SDE-II, and her research integrates machine learning, deep learning, hyperspectral imaging, and satellite data analytics to address real-world agricultural and environmental challenges.
Online Profiles
Dr. Jain maintains active academic and professional profiles on Google Scholar, ResearchGate, LinkedIn, GitHub, and institutional platforms of Delhi Technological University and VIPS-TC, ensuring global visibility of her research contributions, publications, and collaborative work in AI, agriculture, and geospatial intelligence.
Education
She is currently pursuing a Ph.D. in Computer Science and Engineering at Delhi Technological University (thesis submitted), following an MCA with 89% from Bharati Vidyapeeth’s Institute of Computer Applications and Management and a BCA with 93.2% from Vivekananda Institute of Professional Studies, demonstrating consistent academic excellence from undergraduate to doctoral levels.
Research Focus
Her research focuses on artificial intelligence–driven smart agriculture, hyperspectral and multispectral remote sensing, soil nutrient estimation, satellite image processing, transformer-based deep learning models, and precision farming systems aimed at sustainable agricultural innovation.
Experience
Dr. Jain currently serves as an Assistant Professor at Vivekananda Institute of Professional Studies – Technical Campus, where she teaches computer science and mentors undergraduate research, while previously working as a researcher at DTU’s Samsung Lab and as an SDE-II at Busy Infotech Pvt. Ltd., contributing to both academic research and enterprise-level software development.
Research Timeline & Research Contributions
Her research trajectory evolved from software engineering and data-driven systems to advanced AI models for soil and agricultural analytics, resulting in systematic reviews, novel spectral indices, transformer-based frameworks, and deep multitarget learning models published in high-impact SCI journals and IEEE conferences.
Research Impact
Dr. Jain’s work has made significant contributions to precision agriculture and environmental monitoring, with publications in SCI-indexed journals such as Computers and Electronics in Agriculture, Environmental Monitoring and Assessment, and IEEE Geoscience and Remote Sensing Letters, influencing data-driven soil nutrient prediction and smart farming practices.
Innovation & Intellectual Property
Her research introduces novel deep learning architectures, spectral indices, and hybrid AI frameworks for soil property estimation, advancing methodological innovation in hyperspectral analytics and agricultural decision-support systems, with strong potential for translational and applied research outcomes.
Research Projects & Funding
She has contributed to multidisciplinary research projects at Delhi Technological University, Samsung Lab, and the Indian Agricultural Research Institute, focusing on UAV-based hyperspectral data processing, neural network–based soil prediction models, and smart agriculture applications supported through institutional research initiatives.
Conference Contributions
Dr. Jain has authored and co-authored multiple IEEE and Springer conference papers, received a Best Paper Award, and actively participated in international conferences on agricultural computation, geoinformatics, and artificial intelligence, contributing to global academic discourse in AI-driven agriculture.
Academic Excellence
She is UGC-NET qualified, recipient of the Research Excellence Award 2025 from Delhi Technological University, and holds multiple advanced certifications in machine learning and artificial intelligence, reflecting sustained academic distinction and scholarly commitment.
Societal / Industry Contribution
Her research supports sustainable agriculture and food security through AI-enabled soil assessment, while her industry experience in enterprise software development bridges academic research with practical, scalable technological solutions benefiting farmers, researchers, and policymakers.
Global Recognition
With SCI-indexed journal publications, IEEE conference acceptances, international collaborations, and global research indexing, Dr. Jain’s work has achieved international recognition in the fields of artificial intelligence, remote sensing, and smart agriculture.
Publications (Journals & Conferences)
Journal Articles (SCI / SCIE):
Jain, S., Sethia, D., & Tiwari, K. C., “A Critical Systematic Review on Spectral-Based Soil Nutrient Prediction Using Machine Learning,” Environmental Monitoring and Assessment, vol. 196, 699, Springer, 2024, SCIE, IF: 3.0.
Jain, S., Sethia, D., & Tiwari, K. C., “Developing Novel Spectral Indices for Precise Estimation of Soil pH and Organic Carbon Using Hyperspectral Data and Machine Learning,” Environmental Monitoring and Assessment, vol. 196(12), 1255, Springer, 2024, SCIE, IF: 3.0.
Jain, S., Sethia, D., & Tiwari, K. C., “CAT-MTLNet: A Novel Deep Multi-Target Framework for Hyperspectral Soil Properties Estimation Using Concrete Autoencoder and Transformer,” IEEE Geoscience and Remote Sensing Letters, vol. 23, pp. 1–5, 2025, SCIE, IF: 4.4.
Jain, S., Sethia, D., & Tiwari, K. C., “TLM-Stack: A Deep Learning-Based Framework for Soil Nutrients Estimation Using Hyperspectral Data,” Computers and Electronics in Agriculture, Elsevier, 2025, SCIE, IF: 8.9.
Conference Papers (IEEE / Springer):
5. Jain, S. & Sethia, D., “A Review on Applications of Artificial Intelligence for Identifying Soil Nutrients,” International Conference on Agriculture-Centric Computation, Springer, 2023.
6. Jain, S., Sethia, D., & Tiwari, K. C., “A Hybrid Approach for Soil Nutrient Estimation Using Multispectral Data,” IEEE ICAEECI, 2023.
7. Jain, S., Sethia, D., & Tiwari, K. C., “Comparative Analysis of Machine Learning-Based Soil pH Prediction,” ICA 2024, Springer CCIS, 2025.
8. Shah, A., Sah, S., Singhal, S., Jain, S., & Sethia, D., “DSeP-xNet: A Feature Optimized Ensemble Framework for Hyperspectral-Based Soil Organic Carbon Prediction,” IEEE ARIIA, 2024.
9. Jain, A. & Jain, S., “A Novel Hybrid Model for Efficient Prediction of Diabetes Using Machine Learning,” IEEE IDICAIEI, 2024.
10. Jain, S., Sethia, D., & Tiwari, K. C., “CNViS-Net: A Self-Attention Framework for Predicting Soil Nutrients from Hyperspectral Data,” IEEE ICFTS, 2025.
11. Sangwan, A., Sethia, D., & Jain, S., “Multi-Strategy Fused Transformer-CNN with PSO-Driven Optimization for Soil Properties Estimation,” IEEE CIC, 2025 (Accepted).