RAJEASHWARI. S | Deep Learning | Best Researcher Award

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Mrs. RAJEASHWARI. S | Deep Learning | Best Researcher Award

SRI S. RAMASAMY NAIDU MEMORIAL COLLEGE, India

Author Profile

Early Academic Pursuits 🎓📖

Rajeswari S. has consistently demonstrated a deep passion for the field of Computer Science, as evident in her academic journey that began with her undergraduate studies in 2004. She earned a degree in Computer Science from a Deemed University, securing an impressive 75.6% and setting the foundation for her career in technology and education. Her dedication continued through her postgraduate studies at Anna University, where she achieved a commendable 73% in Computer Science in 2007.

Her academic curiosity led her to pursue an M.Phil. in Computer Science at Vinayaka Missions University in 2009, attaining a respectable 61.75%. Her dissertation, titled “Analysis of Medical Image Segmentation Using Fuzzy Hopfield Neural Network and Competitive Hopfield Neural Network,” reflects her interest in innovative computational methodologies. Currently, she is pursuing a Ph.D. in Computer Science from Madurai Kamaraj University, furthering her expertise and research capabilities in this ever-evolving field.

Professional Endeavors 💼👩‍🏫

Rajeswari has built a robust teaching career, marked by impactful roles at esteemed institutions. She began her professional journey as an Assistant Professor at K.R. College of Arts & Science, Kovilpatti, from June 2008 to June 2010. During this period, she nurtured budding technologists with her insightful teaching and dedication.

In 2016, she joined Sri Krishnasamy Arts and Science College, Sattur, where she served until April 2021. Her tenure was characterized by her ability to blend theoretical concepts with practical applications, making complex topics accessible to her students. Her teaching not only enriched the academic environment but also inspired many to explore advanced areas of Computer Science.

Contributions and Research Focus 🧠🔬

Rajeswari’s research interests are deeply rooted in computational intelligence and its applications. Her M.Phil. dissertation delves into advanced image processing techniques, specifically medical image segmentation. By employing Fuzzy Hopfield Neural Network and Competitive Hopfield Neural Network, she contributed to the development of more accurate and efficient methods for medical diagnostics, showcasing her commitment to impactful research.

Her ongoing Ph.D. studies aim to expand this work, likely exploring cutting-edge technologies such as Artificial Intelligence (AI), Machine Learning (ML), and their intersections with image processing. Her research holds the potential to contribute to the fields of healthcare, diagnostics, and data analysis, addressing critical challenges with innovative solutions.

Accolades and Recognition 🏆🌟

Throughout her academic and professional career, Rajeswari has earned recognition for her dedication and contributions. While specific accolades are not listed, her ability to consistently secure teaching positions and handle complex research topics speaks volumes about her reputation in the academic community. She is undoubtedly appreciated for her commitment to quality education and her efforts to advance knowledge in her field.

Impact and Influence 🌍✨

Rajeswari’s influence extends beyond the classroom. As an educator, she has empowered countless students with the skills and knowledge necessary to thrive in the tech industry. Her research work, particularly in medical image segmentation, has the potential to make significant contributions to healthcare by improving diagnostic accuracy and efficiency.

Her dual role as a teacher and researcher positions her as a bridge between theoretical knowledge and practical applications, fostering a deeper understanding of computer science’s capabilities and limitations.

Legacy and Future Contributions 🌟🔮

Looking forward, Rajeswari is poised to leave a lasting legacy in both academia and research. Her ongoing Ph.D. studies and prior achievements suggest a future filled with innovative contributions to technology and education. As she continues to explore the realms of AI and neural networks, her work will likely influence emerging technologies and inspire new generations of researchers.

In the classroom, her commitment to nurturing talent ensures that her influence will echo through the achievements of her students. Meanwhile, her research endeavors promise to address pressing challenges, particularly in healthcare and data processing, cementing her position as a thought leader in her field.

Notable Publications 

  • Title: An Enhanced Learning Model Based on an Improved Random Forest Classifier and an Integrated Attribute Selector for Healthcare Datasets
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Communications in Computer and Information Science
    Year: 2025.
  • Title: Enhancing pneumonia diagnosis with ensemble-modified classifier and transfer learning in deep-CNN based classification of chest radiographs
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Biomedical Signal Processing and Control
    Year: 2024.
  • Title: Chronic disease prediction with deep convolution based modified extreme-random forest classifier
    Authors: Rajeswari, S., Arunesh, K.
    Journal: Biomedical Signal Processing and Control
    Year: 2024.
  • Title: Chronic disease diagnosis and classification using data mining approaches – a comprehensive review
    Authors: Rajeswari, S., Arunesh, K.
    Conference Proceedings: AIP Conference Proceedings
    Year: 2023.
  • Title: Highly Correlated Linear Discriminant Analysis for Dimensionality Reduction and Classification in Healthcare Datasets
    Authors: Rajeswari, S., Arunesh, K.
    Conference Proceedings: Lecture Notes in Networks and Systems
    Year: 2023.

Bhuvaneswari.S | Deep learning | Best Researcher Award

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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).