Mr. Rajesh Yadav | Food Engineering | Best Researcher Award
Mr. Rajesh Yadav at Indian Institute of Technology Kharagpur, India
Rajesh Yadav is a dedicated researcher in Farm Machinery and Power Engineering, currently pursuing his Ph.D. at IIT Kharagpur. With expertise in traction engineering, machine learning, and deep learning, he has developed innovative models for predicting tyre-soil interactions. His research focuses on designing AI-driven solutions for agricultural machinery. He has contributed to prestigious journals, delivered conference presentations, and holds multiple software copyrights. An active academic community member, he has served as a reviewer for various international conferences and journals. Passionate about technology-driven agriculture, Rajesh continues to explore AI applications in mechanized farming.
Publication Profile
Academic Background🎓
Rajesh Yadav is currently pursuing a Ph.D. in Farm Machinery and Power Engineering at IIT Kharagpur, with a tentative thesis submission in May 2025. His research explores traction potential analysis of tubeless tractor tyres using machine learning. He earned his M.Tech. from IIT Kharagpur in 2021, focusing on designing a solar-powered paddy thresher and winnower. Before that, he completed his B.Tech. in Agricultural Engineering from Junagadh Agricultural University in 2019. His academic journey started with secondary education from the Rajasthan Board, achieving excellent grades. His education integrates engineering principles with AI-driven agricultural solutions.
Professional Background 💼
Rajesh has extensive experience in agricultural engineering, specializing in machine learning applications for traction studies. As a Teaching Assistant at IIT Kharagpur, he contributed to developing NPTEL courses. His research involved instrument setup, data acquisition, and ML model development for tyre performance prediction. He supervised undergraduate and postgraduate students, actively participated in instrument procurement, and published in leading journals. Additionally, he has interned with organizations like Northern Region Farm Machinery Training Institute, Jain Irrigation Systems, and Saras Dairy, gaining hands-on experience in farm machinery, irrigation, and dairy processing. He also developed user-friendly software for AI-driven agricultural applications.
Awards and Honors🏆
Rajesh secured AIR 27 in GATE 2019 and AIR 369 in ICAR AIEEA UG 2015. He was awarded the MHRD Scholarship during his M.Tech. and the National Talent Scholarship during his B.Tech. He qualified for NET 2023 (ASRB) in Farm Machinery and Power Engineering and has received the Institute Research Assistantship at IIT Kharagpur since 2021. His contributions in AI-driven agricultural machinery have earned him multiple software copyrights. He is a recognized member of prestigious academic societies like ASABE and ISAE, actively engaging in research, peer review, and international academic conferences.
Research Focus🔬
Rajesh’s research integrates AI, ML, and deep learning into traction engineering and farm machinery optimization. His work includes developing models for tyre-soil interaction, soil compaction, and tractive efficiency predictions. He has created machine learning-based Streamlit and Tkinter applications for agricultural applications. His studies involve evaluating tyre traction potential under controlled conditions, working with leading tyre manufacturers like Yokohama, Apollo, and CEAT. His research aims to enhance agricultural efficiency through AI-driven predictive modeling, focusing on reducing energy losses, improving traction performance, and minimizing soil compaction to promote sustainable farming practices.
Publication Top Notes
1️⃣ Development of an artificial neural network model with graphical user interface for predicting contact area of bias-ply tractor tyres on firm surface 🛞
Year: 2023 | Journal: Journal of Terramechanics | Cited by: 26
2️⃣ Graphene based two-port MIMO yagi-uda antenna for THz applications 📡
Year: 2023 | Journal: Micro and Nanostructures | Cited by: 17
3️⃣ RBF based some implicit–explicit finite difference schemes for pricing option under extended jump-diffusion model 📈
Year: 2023 | Journal: Engineering Analysis with Boundary Elements | Cited by: 6
4️⃣ A machine learning-based approach for estimation of deflection and contact area characteristics of tubeless and tube-type agricultural tyres 🤖🛞
Year: 2024 | Journal: Engineering Applications of Artificial Intelligence | Cited by: 5
Conclusion
Rajesh Yadav is a highly accomplished researcher in Farm Machinery and Power Engineering, currently pursuing a Ph.D. at IIT Kharagpur. His work focuses on traction potential analysis of tubeless tractor tyres using machine learning, contributing significantly to agricultural technology. With multiple publications in reputed journals, software copyrights, and international conference presentations, his research has both academic and real-world impact. He has developed ML/DL models, web applications, and sustainable agricultural machinery. His leadership as a teaching assistant, research scholar representative, and mentor further highlights his contributions. Recognized through prestigious scholarships, GATE AIR 27, and NET qualification, he is a deserving candidate for the Best Researcher Award.
