Thiru Nirai Senthil | Computer Science | Best Academic Researcher Award

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Dr. S. Thiru Nirai Senthil | Computer Science | Best Academic Researcher Award

Jawahar Science College | India

Author Profile

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Early Academic Pursuits

Dr. S. Thiru Nirai Senthil began his academic journey with a strong foundation in computer science and engineering, developing expertise that would later encompass diverse domains such as bioinformatics, artificial intelligence, network security, and data mining. His early exposure to both computational technologies and biological systems enabled him to adopt an interdisciplinary approach to research. Over the years, he built a rich portfolio of technical skills, contributing to areas from molecular modeling and protein analysis to large-scale network optimization and machine learning applications.

Professional Endeavors

With an extensive career in academia, Dr. Senthil has served in pivotal roles, including Head of the Department of Computer Science and Engineering at PRIST University, overseeing curriculum design, departmental administration, and faculty development. His professional experience extends to acting as Chief Superintendent and Additional Chief Superintendent for examination processes, member of various academic boards, and leader in event organization. He has consistently bridged the gap between theoretical research and practical application, guiding students, designing academic programs, and managing university-level technological systems such as ERP CAMU for admissions and data management.

Contributions and Research Focus

Dr. Senthil’s research spans multiple high-impact areas, notably artificial intelligence, machine learning, data mining, cloud computing, IoT, wireless sensor networks, bioinformatics, and cybersecurity. His contributions include the development of algorithms for optimized clustering, secure cloud storage auditing, intelligent e-learning systems, and AI-driven healthcare solutions. His interdisciplinary publications address both technological and societal challenges, such as AI-assisted medical devices, data-driven pandemic analysis, and sentiment analysis for social media monitoring. He has presented papers at prestigious national and international conferences, including ICICACS, ASCIS, ICRTSM, and the Asian Mycological Congress, demonstrating global engagement in research dissemination.

Impact and Influence

Dr. Senthil’s work has had a significant influence on both academic and applied technology communities. His AI-based patents in healthcare, autonomous navigation, and social media analytics showcase his commitment to impactful innovation. He has authored books on core computing subjects-Artificial Intelligence, Machine Learning, Data Mining and Warehousing, and Client-Server Computing-providing valuable academic resources for students and professionals alike. His leadership in faculty development programs, organization of technical workshops, and delivery of expert lectures has shaped the learning environment for countless students and educators.

Academic Citations and Recognition

His research publications have been widely cited, particularly in areas involving AI for agriculture, healthcare, and network optimization. Recognition of his scholarly contributions includes prestigious honors such as the Researcher Excellence Award (2025) and the Global Eminent Academician Award (2021), acknowledging both his research impact and his dedication to teaching excellence.

Legacy and Future Contributions

Dr. Senthil’s academic legacy lies in his ability to integrate multidisciplinary domains, creating solutions that address real-world problems while advancing theoretical frameworks. His role as a research guide and doctoral committee member ensures the training of future scholars, while his patents lay the groundwork for continued innovation. Moving forward, his work is poised to expand into emerging areas of generative AI, advanced machine learning models, and AI-driven biomedical devices, promising further contributions to science, technology, and society.

Conclusion

Dr. S. Thiru Nirai Senthil exemplifies the modern academician—innovative, interdisciplinary, and dedicated to the advancement of knowledge. His career reflects a rare combination of research excellence, pedagogical commitment, and visionary leadership. With an impressive record of publications, patents, and academic service, he continues to influence the trajectory of research in computer science and its allied fields, leaving a lasting mark on both academia and industry.

Notable Publications

"LCNFN: LeNet‐Cascade Neuro‐Fuzzy Network for Grape Leaf Disease Segmentation and Multi‐Classification" 

  • Author: G Selvaraj, SV Puthenkaleelkal, P Alaguchamy, STN Senthil
  • Journal: Journal of Phytopathology
  • Year: 2025

"COVID-19 Adaptive E-Learning: Data-Driven Student Engagement Analysis" 

  • Author: LL Rani, ST Senthil
  • Journal: International Conference on Integrated Circuits
  • Year: 2024

"Text Classification with Automatic Detection of COVID-19 Symptoms from Twitter Posts Using Natural Language Programming (NLP)" 

  • Author: N Manikandan, S Thirunirai Senthil
  • Journal: International Conference on Advancements in Smart Computing
  • Year: 2023

"Efficient College Students Higher Education Prediction Using Machine Learning Approaches" 

  • Author: L Lalli Rani, S Thirunirai Senthil
  • Journal: International Conference on Advancements in Smart Computing
  • Year: 2023

"Improved Genetic Algorithm Based k-means Cluster for Optimized Clustering" 

  • Author: FM Ilyas, ST Senthil
  • Journal: International Conference on Advancements in Smart Computing
  • Year: 2023

 

Fahimeh Dabaghi Zarandi | Community Detection | Women Researcher Award

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Assist. Prof. Dr. Fahimeh Dabaghi Zarandi | Community Detection | Women Researcher Award

Assistant Professor, at Vali-e-Asr University of Rafsanjan, Iran📖

Dr. Fahimeh Dabaghi-Zarandi is an accomplished researcher and academic in software engineering, specializing in data mining, green communication, and IoT. With a Ph.D. from the Iran University of Science and Technology, she brings a rich academic background and a passion for leveraging technology to address complex problems. As an Assistant Professor at Vali-e-Asr University, she continues to inspire students and contribute to the field through innovative research and collaboration.

Profile

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Google Scholar Profile

Education Background🎓

Dr. Fahimeh Dabaghi-Zarandi holds a Ph.D. in Software Engineering from the Iran University of Science and Technology, Tehran, Iran, which she completed in September 2018. She earned her Master’s degree in Software Engineering from the prestigious Sharif University of Technology, Tehran, Iran, in August 2010, and her Bachelor’s degree in the same field from Ferdowsi University of Mashhad, Iran, in August 2008. Her academic journey reflects a consistent focus on software engineering, laying a strong foundation for her expertise in data mining, graph processing, and Internet of Things applications.

Professional Experience🌱

Dr. Fahimeh Dabaghi-Zarandi is an Assistant Professor at the Department of Engineering, Vali-e-Asr University of Rafsanjan, where she contributes to the advancement of computer engineering through teaching and research. She has actively participated in several national conferences on topics such as data mining and computational geometry, including the 16th CSI Computer Conference in Tehran (2011) and the Winter School on Computational Geometry at Amirkabir University (2009). Her involvement in these events reflects her commitment to staying at the forefront of developments in computer science and engineering.

Research Interests🔬

Dr. Dabaghi-Zarandi’s research focuses on:

  • Green Communication: Enhancing energy efficiency in communication systems.
  • Community Detection: Identifying clusters and patterns in large networks.
  • Data Mining: Extracting meaningful insights from large datasets.
  • Graph Processing: Algorithms and applications for analyzing graph structures.
  • Internet of Things (IoT): Developing intelligent solutions for interconnected systems.

Author Metrics 

Dr. Dabaghi-Zarandi’s publications have made significant contributions to her fields of interest, with her work cited by researchers worldwide. Her expertise in graph processing and community detection has been recognized in peer-reviewed journals and conferences, where she has shared her findings on the applications of data mining and IoT in sustainable technology

Publications Top Notes 📄

1. A survey on green routing protocols using sleep-scheduling in wired networks

  • Authors: F. Dabaghi, Z. Movahedi, R. Langar
  • Journal: Journal of Network and Computer Applications
  • Volume: 77
  • Pages: 106-122
  • Year: 2017
  • Citations: 47
  • Abstract: This paper provides a detailed survey of green routing protocols in wired networks, focusing on energy-saving methods achieved through sleep-scheduling mechanisms. The study reviews various techniques and evaluates their effectiveness, contributing valuable insights to the field of green networking.

2. Community detection in complex networks based on an improved random algorithm using local and global network information

  • Authors: F. Dabaghi-Zarandi, P. KamaliPour
  • Journal: Journal of Network and Computer Applications
  • Volume: 206
  • Article: 103492
  • Year: 2022
  • Citations: 11
  • Abstract: This work presents an enhanced random algorithm for community detection in complex networks. By integrating both local and global network information, the proposed method achieves higher accuracy and robustness compared to traditional approaches.

3. An energy‐efficient algorithm based on sleep‐scheduling in IP backbone networks

  • Authors: F. Dabaghi-Zarandi, Z. Movahedi
  • Journal: International Journal of Communication Systems
  • Volume: 30, Issue 13
  • Article: e3276
  • Year: 2017
  • Citations: 11
  • Abstract: This paper introduces an energy-efficient algorithm for IP backbone networks leveraging sleep-scheduling techniques. The algorithm optimizes energy consumption while maintaining network performance.

4. A dynamic traffic-aware energy-efficient algorithm based on sleep-scheduling for autonomous systems

  • Authors: F. Dabaghi-Zarandi, Z. Movahedi
  • Journal: Computing
  • Volume: 100, Issue 6
  • Pages: 645-665
  • Year: 2018
  • Citations: 7
  • Abstract: The study proposes a dynamic traffic-aware algorithm that enhances energy efficiency in autonomous systems by incorporating adaptive sleep-scheduling.

5. Local traffic-aware green algorithm based on sleep-scheduling in autonomous networks

  • Authors: F. Dabaghi-Zarandi
  • Journal: Simulation Modelling Practice and Theory
  • Volume: 114
  • Article: 102418
  • Year: 2022
  • Citations: 2
  • Abstract: This paper introduces a localized green algorithm tailored for autonomous networks. By integrating sleep-scheduling and traffic awareness, the proposed approach reduces energy consumption without compromising network performance.

Conclusion

Dr. Fahimeh Dabaghi-Zarandi is a highly deserving nominee for the Women Researcher Award due to her pioneering research in green communication, community detection, and energy-efficient algorithms. Her contributions address global challenges such as energy conservation and sustainable technology, making her work both impactful and timely.

With a clear trajectory of excellence and continuous innovation, Dr. Dabaghi-Zarandi exemplifies the qualities of a distinguished researcher. Addressing the identified areas for improvement would further amplify her achievements, but her existing body of work strongly supports her candidacy for this award.