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).

Aqil K H | Artificial intelligence | Best Researcher Award

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Mr. Aqil K H | Artificial intelligence | Best Researcher Award

Indian institute of technology Madras-India

Author Profile

Early Academic Pursuits 📚

Dr. Aqil K H’s passion for electrical engineering and innovation began at a young age in Kerala, India. His academic journey started at the Model Technical Higher Secondary School in Ernakulam, where he excelled in the state board exams, securing an impressive 98.33% in 2012 for his X standard and 95.58% in 2014 for his XII standard. These early achievements underscored his commitment to learning and laid the foundation for his future success. After completing his pre-university education, he pursued a Bachelor of Technology (B.Tech) degree in Electronics and Communication Engineering (ECE) from the prestigious Government Model Engineering College in Ernakulam, Kerala, where he graduated with a commendable CGPA of 8.36 in 2018. His strong academic foundation and technical skills positioned him for higher studies and research.

Professional Endeavors 🌍

Dr. Aqil’s career began as a Software Engineer at Kimball Electronics (India) Pvt. Ltd., where he contributed to various projects within the image processing domain. His role involved the development of computer vision frameworks and algorithm optimization for improving image quality. Working closely with clients in Vietnam, he demonstrated his adaptability and ability to manage real-world challenges, marking his early years of professional growth.In 2020, Dr. Aqil transitioned into research, joining the Healthcare Technology Innovation Centre (HTIC) at IIT Madras, one of the country’s leading research institutes. As a Research Associate, he worked on several impactful projects. One notable project was the X-ray angiography image enhancement initiative, where he collaborated with industry partners to enhance imaging technology. His work on precision medicine for chronic diseases, particularly Alzheimer’s, further expanded his contributions to healthcare innovations. This multi-modal time series forecasting system, aimed at predicting disease progression, utilized cutting-edge techniques like graph representation learning.Additionally, Dr. Aqil became associated with the Sudha Gopalakrishnan BRAIN Centre at IIT-M, where he contributed to groundbreaking research in fetal brain MRI segmentation and histopathology image segmentation. These projects highlighted his ability to apply machine learning and image processing techniques to critical medical fields.

Contributions and Research Focus 🔬

Dr. Aqil’s research primarily focuses on deep learning, machine learning, and image processing, with a particular interest in healthcare applications. His expertise lies in creating sophisticated algorithms and frameworks for medical imaging, including MRI segmentation, dental panoramic X-ray analysis, and time-series forecasting for clinical outcomes.

Some of his key projects include:

  • Learning to Atlas Register for Rapid Segmentation of Brain Structures in Fetal MRI: This innovative project addressed challenges in brain segmentation, focusing on multilabel atlas-based segmentation. By using the VoxelMorph’s CNN architecture, Dr. Aqil formulated registration as a deformation field that aligned neurotypical brain images for better diagnosis.
  • Time Series Forecasting of Clinical Factors and Outcomes: This project was geared toward Alzheimer’s disease prediction, using a graph representation learning approach. Dr. Aqil proposed a novel framework that operated on dynamic graphs, translating medical data into actionable insights for clinicians.
  • Accelerated MRI with Untrained Neural Networks: Addressing the problem of MRI reconstruction, this project leveraged untrained neural networks to solve issues related to undersampling, using innovative techniques like ConvDecoder.

His work on dental panoramic X-ray segmentation utilized deep learning techniques to enable the early diagnosis of dental disorders. Dr. Aqil’s fascination with machine learning also extended into areas of face recognition technology, where he developed a door access control system based on K-L transform for face recognition.

Accolades and Recognition 🏅

Throughout his career, Dr. Aqil has earned widespread recognition for his contributions to both research and industry. His academic achievements, such as a CGPA of 9.00 in his Master’s program at IIT-Madras, reflect his dedication to excellence. His research endeavors at IIT-Madras’s HTIC and BRAIN Centre have led to publications that have earned citations, indicating his growing influence in the field of medical image processing and machine learning.

Impact and Influence 🌟

Dr. Aqil’s research has had a profound impact on the field of medical imaging. His work on X-ray angiography and fetal brain MRI segmentation has improved diagnostic capabilities, helping doctors make more informed decisions. The time series forecasting systems he developed for Alzheimer’s disease prediction are poised to revolutionize how chronic diseases are managed and treated. His contributions to precision medicine are critical in an era where personalized treatment plans are becoming the norm.His research contributions extend beyond academic circles, as his image processing frameworks are being implemented in real-world medical settings, influencing the future of healthcare technology.

Legacy and Future Contributions 🚀

Dr. Aqil K H is set to leave a lasting legacy in the intersection of electrical engineering and healthcare technology. His groundbreaking work in image processing and deep learning promises to continue shaping the future of medical diagnostics. As a researcher, his contributions to accelerated MRI reconstruction and graph-based time-series forecasting have set new standards in medical imaging research. His passion for education, research, and technological advancement ensures that his work will inspire future engineers and researchers.In the coming years, Dr. Aqil aims to expand his research to include multi-modal medical data integration and AI-driven healthcare solutions, further pushing the boundaries of how technology can improve human health. His dedication to innovation, collaboration, and continuous learning will undoubtedly leave an enduring mark on the fields of deep learning and medical imaging.

Notable Publications 

  • Predictive Modeling of Alzheimer’s Disease Progression: Integrating Temporal Clinical Factors and Outcomes in Time Series Forecasting
    Authors: Aqil, K.H., Dumpuri, P., Ram, K., Sivaprakasam, M.
    Journal: Intelligence-Based Medicine, 2024.
  • Confounding Factors Mitigation in Brain Age Prediction Using MRI with Deformation Fields
    Authors: Aqil, K.H., Kulkarni, T., Jayakumar, J., Ram, K., Sivaprakasam, M.
    Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023.
  • Learning to Atlas Register for Rapid Segmentation of Brain Structures in Fetal MRI
    Authors: Kulkarni, T., Aqil, K.H., Jayakumar, J., Ram, K., Sivaprakasam, M.
    Journal: Progress in Biomedical Optics and Imaging – Proceedings of SPIE, 2023.