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.

Ranjeet Kumar Pathak | Machine Learning | Excellence in Scientific Research Award

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Dr. Ranjeet Kumar Pathak | Machine Learning | Excellence in Scientific Research Award

Sandip Institute of Technology & Research Centre, Nashik, Maharashtra-India

Author Profile

🌱 Early Academic Pursuits

Dr. Ranjeet Pathak’s academic journey is a testament to his dedication and perseverance. Starting from a humble background, he displayed an early inclination towards science and technology. Completing his High School from National Inter College, Fatehpur, with an impressive 73.50%, and Intermediate from R.R. Inter College Hardoi with 63.40%, Dr. Pathak laid a solid foundation for his future endeavors.

He pursued a B.Tech in Electronics and Instrumentation at Skyline Institute of Engineering & Technology, affiliated with UPTU, Lucknow. Graduating in 2008 with 65.72%, he cultivated a keen interest in electronics and instrumentation systems. His thirst for advanced knowledge led him to pursue an M.Tech in Power Electronics & ASIC Design at the prestigious MNNIT, Allahabad, where he excelled with a 7.2 CPI.

Crowning his academic achievements, Dr. Pathak completed his Ph.D. in Electronics and Communication Engineering at Amity University, Lucknow, in 2024 with an impressive 8.00 SGPA. His doctoral work exemplifies his passion for innovative research in cutting-edge fields of engineering.

💼 Professional Endeavors

Dr. Pathak’s professional journey reflects his commitment to nurturing future engineers and advancing technological research.

  • He began his career as an Assistant Professor in the ECE Department at United Institute of Technology, Prayagraj, where he served from February 2010 to September 2022. During this tenure, he contributed to the academic growth of students, focusing on core electronics subjects.
  • Transitioning to the CSE Department at United College of Engineering and Research, Prayagraj, in 2022, he diversified his expertise by teaching advanced computing subjects. His tenure here lasted until July 2024.
  • Currently, Dr. Pathak is imparting knowledge and conducting research as an Assistant Professor in the E&TC Department at Sandip Institute of Technology and Research Center, Nashik, Maharashtra, where he has been serving since October 2024.

🔬 Contributions and Research Focus

Dr. Pathak’s research interests span a wide array of interdisciplinary topics, including:

  • Deep Learning for Medical Data: His training with Finland Labs highlights his commitment to leveraging AI for healthcare.
  • Machine Learning with Python: Completing a course from IBM enhanced his skills in computational modeling, enabling him to contribute to AI-driven solutions in engineering.
  • Power Electronics & ASIC Design: His M.Tech specialization underscores his expertise in developing energy-efficient systems and specialized hardware designs.

His innovative research during his Ph.D. has paved the way for practical applications in electronics and communication, contributing to advancements in fields such as IoT, robotics, and signal processing.

🏆 Accolades and Recognition

Dr. Pathak’s dedication has earned him recognition as a versatile academic and researcher:

  • Successfully trained in Deep Learning for Medical Data, positioning him at the forefront of healthcare innovation.
  • Certification in Machine Learning with Python from IBM, showcasing his ability to implement AI-driven methodologies in solving complex problems.
  • His extensive teaching career spanning over a decade has earned him accolades from students and peers for his impactful mentorship.

🌟 Impact and Influence

Dr. Pathak’s teaching and research have influenced countless students, fostering their understanding of both theoretical and applied aspects of engineering. His ability to integrate emerging technologies into traditional engineering curricula ensures students are well-equipped to meet industry demands.

As a passionate educator, he has emphasized the importance of interdisciplinary learning, motivating students to explore fields such as artificial intelligence, renewable energy, and embedded systems.

🛠️ Legacy and Future Contributions

Looking ahead, Dr. Pathak envisions further expanding his contributions to academia and industry:

  • Pioneering Research: He aims to delve deeper into AI applications in electronics and renewable energy systems, addressing global challenges like sustainability and efficient energy utilization.
  • Mentorship: Dr. Pathak plans to mentor budding researchers, guiding them to make meaningful contributions in engineering and technology.
  • Collaborations: Establishing collaborations with international universities and research organizations, he seeks to create impactful projects that blend innovation with practical applications.

🌍 A Legacy of Excellence

Dr. Ranjeet Pathak’s journey from a determined student to a respected educator and researcher is an inspiration for aspiring engineers. His unwavering commitment to advancing knowledge and empowering students ensures his legacy will continue to inspire future generations. With his unique blend of expertise, passion, and vision, Dr. Pathak stands as a beacon of excellence in the field of engineering education.

🌟 “Engineering is not just a profession but a mission to innovate, educate, and transform lives.” 🌟

Citations

A total of 06 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations        06
  • h-index          06
  • i10-index       02

Notable Publications 

  • Title: A Two-Stage Detection Methodology for Thyroid Cancer Using Photonic Crystal: Logistic Regression and Artificial Neural Networks
    Authors: Pathak, R.K., Mishra, S., Roy, S.K., Sharan, P.
    Journal: Optik, 2025.
  • Title: Design of Optical Sensor for Cancer Prognosis Prediction Using Artificial Intelligence
    Authors: Pathak, R.K., Mishra, S., Sharan, P.
    Journal: Journal of Optics (India), 2024.
  • Title: Bragg Reflector One-Dimensional Multi-Layer Structure Sensor for the Detection of Thyroid Cancer Cells
    Authors: Pathak, R.K., Mishra, S., Sharan, P.
    Journal: Telkomnika (Telecommunication Computing Electronics and Control), 2023.
  • Title: Investigation of a Superior Thermal Sensitivity FBG-Based Temperature Sensor with Metallic and Polymeric Coatings
    Authors: Deepa, N., Sharma, S., Sharan, P., Pathak, R.K.
    Conference: 2023 IEEE Workshop on Recent Advances in Photonics (WRAP 2023), 2023.
  • Title: Thyroid Cancer Detection Using Artificial Neural Network and Photonic Sensor
    Authors: Pathak, R.K., Mishra, S., Sharan, P.
    Conference: 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON 2023), 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).

Akhil Kumar Das | Machine Learning | Innovation Award

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Mr. Akhil Kumar Das | Machine Learning | Innovation Award

Gour Mahavidyalaya- India

Author Profile

🎓Early Academic Pursuits

Dr. Akhil Kumar Das began his academic journey with a focus on Computer Science and Engineering, laying a strong foundation for his future career. He pursued a B.Tech in Computer Science from a renowned institution, followed by an M.Tech, demonstrating his commitment to advancing his knowledge and skills in the field. Dr. Das further enhanced his academic credentials by passing the GATE and UGC-NET exams, which are crucial for pursuing higher education and academic positions in India. His early academic pursuits set the stage for a distinguished career in both teaching and research.

💼Professional Endeavors

Dr. Das’s professional career began at IMPS College of Engineering & Technology, where he served as an Assistant Professor in the Department of Computer Science and Engineering from 2007 to 2014. During this period, he was responsible for imparting knowledge to undergraduate students and contributing to various academic activities. His tenure at Uttar Banga Krishi Viswavidyalaya in Cooch Behar from 2014 to 2016 further solidified his role as an educator. There, he continued to shape the future of students while also engaging in research and development.In 2016, Dr. Das transitioned to Gour Mahavidyalaya, where he continues to work as an Assistant Professor in Computer Science. His role involves not only teaching but also mentoring students and contributing to the academic environment through various initiatives.

🔬Contributions and Research Focus

Dr. Das has made significant contributions to the field of Computer Science through his extensive research. His research interests are primarily centered around machine learning, artificial intelligence, and their applications in healthcare, specifically breast cancer prediction. Noteworthy publications include:

  1. “Hybrid Case Based Reasoning System by Cost Sensitive Neural Network for Classification” – This paper explores innovative approaches in hybrid case-based reasoning systems, published in Soft Computing (2017).
  2. “Machine Learning Based Intelligent System for Breast Cancer Prediction (MLISBCP)” – This recent work focuses on advanced machine learning techniques for predicting breast cancer, published in Expert Systems with Applications (2024).
  3. “BCPUML: Breast Cancer Prediction Using Machine Learning Approach—A Performance Analysis” – A comprehensive analysis of machine learning methods for breast cancer prediction, featured in SN Computer Science (2023).
  4. “Comprehensible and Transparent Rule Extraction Using Neural Network” – This publication addresses methods for improving the transparency of neural network models, published in Multimedia Tools and Applications (2024).
  5. “Development of a Problem Solving Support for an Intelligent Tutoring System” – A significant contribution to educational technology, published in International Journal of Innovations & Advancement in Computer Science (2015).

Dr. Das’s research has been pivotal in advancing the application of machine learning techniques to critical areas such as healthcare, thereby contributing to the broader scientific community.

🏆Accolades and Recognition

Dr. Das has been recognized for his contributions to both teaching and research. His work has been published in several high-impact journals, reflecting his commitment to advancing knowledge in computer science. Notably, his research on breast cancer prediction has been well-received, and he has been invited to present his findings at various international conferences.

🌍Impact and Influence

Dr. Das’s research and professional work have significantly impacted the field of computer science. His innovative approaches to machine learning and artificial intelligence have not only advanced academic understanding but also provided practical solutions for pressing issues such as breast cancer prediction. His contributions extend beyond academia, influencing both industry practices and healthcare advancements. By integrating cutting-edge technology with real-world applications, Dr. Das has demonstrated a profound ability to address complex challenges and improve quality of life.

🌟Legacy and Future Contributions

Dr. Akhil Kumar Das’s legacy is marked by his dedication to advancing the field of computer science through both teaching and research. His work has set a benchmark for integrating machine learning with healthcare solutions, paving the way for future innovations. As he continues to work at Gour Mahavidyalaya, his focus remains on furthering research in machine learning and its applications. Dr. Das’s future contributions are expected to drive new advancements in technology, potentially transforming various domains, particularly in healthcare. His commitment to education and research will continue to inspire and shape the future of computer science.Dr. Das’s career is a testament to the impact of dedicated research and teaching in the advancement of technology and science. His contributions will undoubtedly influence future generations of students and researchers, reinforcing the vital role of academic excellence in driving progress and innovation.

Citations

A total of 40 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         40
  • h-index           11
  • i10-index        3

Notable Publications 

  • Title: Hybrid Case Based Reasoning System by Cost Sensitive Neural Network for Classification
    Authors: Saroj Kr. Biswas, Manomita Chakraborty, Heisnam Rohen Singh, Debashree Devi, Biswajit Purkayastha, Akhil Kr. Das
    Journal: Soft Computing
    Volume: 21
    Year: 2017
  • Title: Machine Learning Based Intelligent System for Breast Cancer Prediction (MLISBCP)
    Authors: Akhil Kumar Das, Saroj Kr. Biswas, Ardhendu Mandal, Abhishek Bhattacharya, Suman Sanyal
    Journal: Expert Systems with Applications
    Year: 2024
  • Title: BCPUML: Breast Cancer Prediction Using Machine Learning Approach—A Performance Analysis
    Authors: Rahul Karmakar, Shibashis Chatterjee, Akhil Kumar Das, Ardhendu Mandal
    Journal: SN Computer Science
    Article ID: 377
    Year: 2023
  • Title: Comprehensible and Transparent Rule Extraction Using Neural Network
    Authors: Saroj Kr. Biswas, Abhishek Bhattacharya, Anirban Duttachoudhury, Manomita Chakraborty, Akhil Kumar Das
    Journal: Multimedia Tools and Applications
    Year: 2024
  • Title: Development of a Problem Solving Support for an Intelligent Tutoring System
    Authors: Akhil Kumar Das, Debasis Mandal
    Journal: International Journal of Innovations & Advancement in Computer Science
    Volume: 4
    Year: 2015.