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.

Kshitish Kumar Mohanta | Decision Sciences | Best Researcher Award

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Mr. Kshitish Kumar Mohanta | Decision Sciences | Best Researcher Award

Indira Gandhi National Tribal University, Amarkantpak, India

Author Profile

Early Academic Pursuits 📚

Kshitish Kumar Mohanta’s academic journey began with a strong foundation in science during his schooling. He completed his 10th-grade education at Govt. High School, Kendumundi, Odisha, in 2011, where he excelled with an impressive score of 82.83%. His exceptional performance continued in 12th grade at M.P.C. Junior College, Baripada, where he focused on science and secured a commendable 70.83% in 2013. This solid background in mathematics and science set the stage for his future academic achievements.Kshitish pursued his undergraduate degree in Mathematics at Udala College, under North Orissa University, Baripada. Graduating in 2016 with 69.72%, he demonstrated a clear aptitude for the subject. His love for numbers and mathematical theories continued to grow, driving him to further his studies with an M.Sc. in Mathematics from Sambalpur University, Jyoti Vihar. In 2018, he completed his master’s with a notable 69.70%, a testament to his dedication and academic prowess.To deepen his understanding and research in the field of mathematics, Kshitish enrolled in an M.Phil. program at G.M. University, Sambalpur, where he completed his degree in 2020 with 63.30%. His academic journey culminated with a Ph.D. from Indira Gandhi National Tribal University (IGNTU), Amarkantak, Madhya Pradesh, where he submitted his thesis in May 2024, marking a significant milestone in his academic career. His Ph.D. thesis, titled “Design and Application of Data Envelopment Analysis under the Extended Fuzzy Environment”, reflects his specialized focus on advanced mathematical applications.

Professional Endeavors and Contributions 💼

Kshitish’s professional experience includes a teaching role as a Guest Lecturer in the Department of Mathematics at Janata College, Boinda, Angul, Odisha, from 2018 to 2020. His ability to impart complex mathematical concepts to students showcased his passion for education and teaching. As a teacher, he focused on nurturing young minds in various mathematical disciplines, laying a foundation for their future academic growth.In addition to his teaching experience, Kshitish is highly skilled in several mathematical software tools and programming languages, including MATLAB, Wolfram Mathematica, SciLab, Sage Math, and C & C++. His expertise in these tools, along with Microsoft Office and LaTeX, enabled him to approach mathematical research and problem-solving in innovative ways.

Research Focus and Areas of Expertise 🔬

Kshitish Kumar Mohanta’s research revolves around Operation Research, Data Envelopment Analysis (DEA), Fuzzy Optimization, Neutrosophic Theory, Decision Support Systems, Efficiency and Productivity Analysis, Performance Measurement, and Inventory Management. These fields align closely with his Ph.D. thesis on DEA under fuzzy environments, illustrating his commitment to exploring new dimensions in decision-making and optimization under uncertain conditions.His research has also touched on various mathematical subjects, including Linear Algebra, Differential Equations, Partial Differential Equations, Real Analysis, Discrete Mathematics, Number Theory, Graph Theory, and Cryptography. These areas of expertise showcase Kshitish’s deep understanding of both theoretical and applied mathematics, with a particular emphasis on solving real-world problems through mathematical frameworks.

Accolades and Recognition 🏆

Throughout his academic and professional career, Kshitish has garnered several prestigious awards and recognitions. Notably, he received the I.M.A. Scholarship for the period of 2016 to 2018, which helped him pursue his passion for mathematics at a higher level. His scholarly excellence was further highlighted when he secured the top rank in the IGNTU RET 2020 examination in the field of mathematics.One of his proudest accomplishments was being awarded Best Paper Presentation at the International Conference on Multidisciplinary Research (ICMR-2022). This recognition solidified his position as a leading researcher in his field and demonstrated the practical and impactful nature of his work in applied mathematics.

Impact and Influence 🌍

Kshitish’s research has had a significant impact on the field of mathematics, particularly in Fuzzy Optimization and Data Envelopment Analysis. His work on performance measurement and decision-making under uncertainty has practical implications for industries and organizations that rely on optimization and productivity analysis. By applying his research in real-world scenarios, Kshitish has contributed to advancements in both academic and industrial sectors, influencing a new generation of researchers and practitioners in these fields.His expertise in Neutrosophic Theory and Decision Support Systems has also added a novel dimension to the study of efficiency and productivity. These contributions are not only theoretical but also hold potential for real-world applications in various domains, including economics, logistics, and management science.

Legacy and Future Contributions 🌟

Looking forward, Kshitish Kumar Mohanta’s future contributions are likely to leave a lasting legacy in the field of mathematics and operations research. As he continues to explore the realms of Fuzzy Optimization and DEA, his work promises to break new ground in understanding and solving complex mathematical problems. His ability to blend theoretical knowledge with practical applications positions him as a key player in both academic circles and industries that rely on advanced mathematical models for decision-making.With his diverse skill set and a strong foundation in research, Kshitish is poised to make significant strides in the field, offering new solutions to age-old mathematical challenges. His legacy will not only be defined by his academic contributions but also by the students and researchers he inspires along the way. As a teacher, researcher, and mathematician, Kshitish Kumar Mohanta continues to shape the future of mathematics with passion and dedication, leaving an indelible mark on the field.

Citations

A total of 64 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         64
  • h-index           12
  • i10-index         4

Notable Publications 

  • Title: A Malmquist Fuzzy Data Envelopment Analysis Model for Performance Evaluation of Rural Healthcare Systems
    Authors: Chaubey, V., Sharanappa, D.S., Mohanta, K.K., Verma, R.
    Journal: Healthcare Analytics
    Year: 2024.
  • Title: The Spherical Fuzzy Data Envelopment Analysis (SF-DEA): A Novel Approach for Efficiency Analysis
    Authors: Mohanta, K.K., Sharanappa, D.S.
    Journal: AIP Conference Proceedings
    Year: 2024.
  • Title: A Novel Method for Solving Neutrosophic Data Envelopment Analysis Models Based on Single-Valued Trapezoidal Neutrosophic Numbers
    Authors: Mohanta, K.K., Sharanappa, D.S.
    Journal: Soft Computing
    Year: 2023.
  • Title: A Novel Modified Khatter’s Approach for Solving Neutrosophic Data Envelopment Analysis
    Authors: Mohanta, K.K., Sharanappa, D.S., Aggarwal, A.
    Journal: Croatian Operational Research Review
    Year: 2023.
  • Title: Enhancing the Security of Public Key Cryptographic Model Based on Integrated ElGamal-Elliptic Curve Diffie Hellman (EG-ECDH) Key Exchange Technique
    Authors: Mohanta, K.K., Sharanappa, D.S., Mishra, V.N.
    Book: Advanced Mathematical Techniques in Computational and Intelligent Systems
    Year: 2023.

Shalini Sharma | Wastewater treatment | Best Researcher Award

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Ms. Shalini Sharma - Queueing modelling - Best Researcher Award 🏆 

Central University of Jammu - India

Professional Profiles

Early Academic Pursuits

She embarked on her academic journey with a strong foundation laid during her schooling years. Completing her Class 10th and 12th from CBSE, she exhibited a keen interest in mathematics and its applications. This interest led her to pursue her undergraduate studies at DAV (PG) College, where she obtained her Bachelor's degree in 2012. Building upon this, she furthered her academic pursuits and earned her Master's degree from the same institution in 2014.

Professional Endeavors

Her academic prowess and dedication led her to qualify for the prestigious National Eligibility Test (NET). Her exceptional performance also earned her the Junior Research Fellowship (JRF) and subsequently the Senior Research Fellowship (SRF) under the CSIR-UGC joint venture program. These accomplishments underscore her commitment to academic excellence and research endeavors. Queueing modeling finds applications in a wide range of fields, including telecommunications, healthcare, transportation, and manufacturing.

Contributions and Research Focus in Wastewater treatment

Currently enrolled in a Ph.D. program at the Central University of Jammu since 2019, Her research is centered on queueing modeling of machine repair problems. Her work delves into maintenance scheduling and service systems, addressing critical challenges in optimizing machine repair processes. By employing queueing models, she seeks to enhance the efficiency and effectiveness of maintenance operations, contributing significantly to the field of operations research and industrial engineering.

Queueing modelling of machine repair problems involves the application of mathematical and computational techniques to analyze and optimize the repair processes of industrial machinery. This interdisciplinary field combines concepts from operations research, industrial engineering, and stochastic processes to improve maintenance scheduling and service efficiency. In queueing modeling, systems are represented using mathematical models that capture the behavior of entities as they move through the system. These models typically include parameters such as arrival rates, service rates, and the number of servers or resources available. By manipulating these parameters and applying various analytical techniques, researchers can gain insights into the behavior of the system and identify opportunities for improvement.

Accolades and Recognition

Her contributions to the field have not gone unnoticed. Her exceptional research work has garnered acclaim, evident from her selection for the Best Researcher Award in Queueing Modeling. This recognition underscores her proficiency and expertise in tackling complex problems related to machine repair and maintenance scheduling.

Queueing theory serves as a fundamental framework for understanding the flow of tasks and resources within repair systems, enabling the identification of bottlenecks and the design of effective maintenance strategies. Through simulation modeling and performance evaluation, queueing models help organizations streamline their repair operations, reduce costs, and enhance overall equipment reliability.

Impact and Influence

Through her research endeavors, She aims to make a meaningful impact on real-world applications, particularly in the realm of industrial operations and service systems. By developing robust queueing models, she envisions optimizing maintenance processes, reducing downtime, and enhancing overall productivity in various industrial settings. Her work has the potential to revolutionize maintenance practices, leading to cost savings and improved operational efficiency.

Legacy and Future Contributions

Her dedication to advancing the field of queueing modeling sets a precedent for future researchers. Her innovative approach and commitment to excellence serve as inspiration for aspiring scholars in the field of operations research and industrial engineering. As she continues her academic journey, She endeavors to push the boundaries of knowledge in queueing modeling and machine repair optimization, leaving a lasting legacy in the realm of service systems and maintenance scheduling.

Notable Publications