Dr. Bhuvaneswari.S | Deep learning | Best Researcher Award
SASTRA Deemed University- India
Author Profile
Early Academic Pursuits
Dr. S. Bhuvaneswari embarked on her academic journey with a passion for computer science and engineering, setting a solid foundation for her future endeavors. She pursued her doctoral studies at SASTRA Deemed University, Thanjavur, India, where she focused on developing innovative solutions to real-world challenges. Her thesis, titled “An Intelligent Data-driven Prediction Model for Sustainable Cropping System using Deep Learning Techniques,” reflects her dedication to leveraging technology for agricultural sustainability. This early focus on deep learning techniques and precision agriculture positioned her as a thought leader in the intersection of technology and agriculture. 🌾
Professional Endeavors
Dr. Bhuvaneswari’s professional journey is marked by diverse roles that encompass both industry and academia. She began her career as a Quality Engineering Transformation (QET) Engineer at TATA Consultancy Services (TCS) in Chennai from June 2018 to January 2020. During her tenure at TCS, she was part of the Center of Excellence team in performance testing, where she honed her skills in quality assurance and software engineering.In January 2020, she transitioned to academia as a Junior Research Fellow at the School of Computing, SASTRA Deemed University, supported by the Indian Council of Social Science Research (ICSSR) under the IMPRESS Scheme. She later served as a Teaching Assistant and then a Research Assistant, contributing significantly to various projects until February 2024, when she was appointed as an Assistant Professor Research in the Department of Computer Science and Engineering at SASTRA Deemed University. Her journey reflects a commitment to both teaching and research, combining practical experience with academic rigor. 📚
Contributions and Research Focus
Dr. Bhuvaneswari’s research interests primarily revolve around Deep Learning Techniques, Recommender Systems, and Precision Agriculture. Her work emphasizes the development of intelligent systems that can analyze complex data sets and provide actionable insights for sustainable agricultural practices. One of her notable projects, “Design and Development of Decision-making Tool for Crop Selection in Precision Agriculture,” aims to aid farmers in making informed decisions, thereby improving crop yields and resource management. Additionally, her investigation into prediction models for physical activity recommender systems highlights her versatility and ability to apply her expertise across various domains.Her proficiency in programming languages like Java and Python, combined with her experience in Computer Vision and Recommender Systems, positions her as a valuable asset in the fields of data science and machine learning. 🖥️
Accolades and Recognition
Throughout her career, Dr. Bhuvaneswari has received recognition for her contributions to academia and research. Her work has been funded by reputable organizations, showcasing her ability to secure grants and support for her innovative projects. She has participated in numerous conferences, presenting her research findings and engaging with other experts in her field. This active involvement not only enhances her professional profile but also contributes to the advancement of knowledge in her areas of expertise.
Impact and Influence
Dr. Bhuvaneswari’s influence extends beyond her immediate academic environment. By integrating advanced computational techniques into agriculture, she addresses critical issues related to food security and sustainable farming practices. Her research empowers farmers with data-driven insights, helping them optimize their operations and adapt to changing environmental conditions. Through her teaching, she inspires the next generation of computer scientists, instilling in them a passion for innovation and problem-solving. 🌍
Legacy and Future Contributions
As Dr. Bhuvaneswari continues her journey at SASTRA Deemed University, her legacy is already taking shape through her impactful research and dedication to education. She envisions expanding her work in deep learning and precision agriculture, potentially collaborating with industry partners to implement her models in real-world agricultural settings. Her commitment to developing sustainable solutions is likely to inspire future researchers and practitioners in the field.In conclusion, Dr. S. Bhuvaneswari exemplifies the integration of technology and agriculture, with a strong foundation in research and teaching. Her contributions are paving the way for a more sustainable future, making her a prominent figure in her field. For inquiries, she can be reached at her email: sbhuvi95@gmail.com. With a promising trajectory ahead, Dr. Bhuvaneswari is poised to make significant advancements that will benefit both academia and the agricultural sector. 🌟
Citations
A total of 110 citations for his publications, demonstrating the impact and recognition of his research within the academic community.
- Citations 110
- h-index 16
- i10-index 5
Notable Publications
- Bhuvaneswari, S. & Subramaniyaswamy, V.
“D2CNN: Double-staged Deep CNN for Stress Identification and Classification in Cropping System”
Agricultural Systems, (2024), Vol. 216, 103886 [IF: 6.6] - Bhuvaneswari, S., Jagadeesh, M. & Subramaniyaswamy, V.
“Multi-label Classification for Acoustic Bird Species Detection using Transfer Learning Approach”
Ecological Informatics, (2024), Vol. 80, pp. 1-12, 102471 [IF: 5.1] - Bhuvaneswari, S., Saravanan, P. & Subramaniyaswamy, V.
“Feature Fusion based Deep Neural Collaborative Filtering Model for Fertilizer Prediction”
Expert Systems with Applications, (2023), Vol. 216, pp. 1-12 [IF: 8.665] - Bhuvaneswari, S., Saravanan, P. & Subramaniyaswamy, V.
“Meta Learning-based Dynamic Ensemble Model for Crop Selection”
Applied Artificial Intelligence, (2022), Vol. 36, pp. 1-36 [IF: 2.777] - Bhuvaneswari, S., Saravanan, P., Kotecha, K., Kumar, V. & Subramaniyaswamy, V.
“IoT Driven Artificial Intelligence Technique for Fertilizer Recommendation Model”
IEEE Consumer Electronics Magazine, (2022).