Tajunisha N | Computer Science | Best Faculty Award

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Dr. Tajunisha N | Computer Science | Best Faculty Award

Dr. Tajunisha N, Sri Ramakrishna College of Arts & Science for Women, India

Dr. N. Tajunisha is a distinguished academician and researcher in Computer Science, currently serving as Professor and Head of the Department at Sri Ramakrishna College of Arts & Science for Women. With over 27 years of academic experience and 23 years of research expertise, she specializes in Data Mining, Machine Learning, Big Data Analytics, and Networks. She earned her Ph.D. from Mother Teresa Women’s University, Kodaikanal, and has been an influential figure in research and development. As a leader, she has held key positions such as Research Coordinator, IQAC Coordinator, and Institution Innovation Cell (IIC) President. Her contributions to academia include publishing research papers in prestigious journals, securing research funding, and mentoring Ph.D. scholars. Recognized with the Senior Educator and Scholar Award, she actively collaborates with institutions like IBM, Rently, and L&T EDUTECH. Her work continues to shape the future of Computer Science education and research.

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Suitability of Dr. N. Tajunisha for the Research for Best Faculty Award

Dr. N. Tajunisha is a distinguished academic leader with a strong record of excellence in teaching, research, and institutional development. With 27 years of academic experience and 23 years of research expertise, she has significantly contributed to the fields of Data Mining, Machine Learning, Big Data Analytics, and Networks. As a Professor and Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has played a crucial role in shaping the institution’s academic and research landscape.

Her research contributions are noteworthy, with 34 journal publications, 25 conference papers, and 9 SCOPUS-indexed papers, along with securing Rs. 3.17 lakhs from UGC for a Minor Research Project and Rs. 76 lakhs for a DST-FIST project. Dr. Tajunisha’s role as a Ph.D. guide, having successfully mentored three doctoral scholars and currently supervising five more, reflects her dedication to research mentorship. Her collaborations with IBM, Rently, L&T EDUTECH, Easy Design System, and VConnect highlight her industry engagement, while her participation in Doctoral Committees, Board of Studies (BOS), and Programme Advisory Committees showcases her leadership in academic governance.

🎓 Education

Dr. N. Tajunisha has an extensive educational background in Computer Science and Mathematics. She earned her Ph.D. in Computer Science from Mother Teresa Women’s University, Kodaikanal, in 2013, focusing on advanced research methodologies. Before that, she completed her M.Phil. in Computer Science from Bharathiar University, where she developed expertise in data analysis and computational techniques. Her academic journey began with a Master of Computer Applications (MCA) and a Bachelor’s degree in Mathematics from Madurai Kamaraj University, providing her with a strong mathematical foundation essential for algorithm development and computational problem-solving. Her diverse academic background has equipped her with critical analytical skills, enabling her to contribute significantly to the fields of Data Mining and Machine Learning. Her education and continuous professional development have played a crucial role in her ability to drive research innovations and mentor future scholars in Computer Science.

💼 Professional Experience

Dr. N. Tajunisha has over 27 years of academic experience and 23 years in research, significantly shaping Computer Science education. As the Professor & Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has spearheaded numerous academic and research initiatives. From 2013 to 2018, she served as the Research Coordinator, facilitating advanced research projects and securing substantial funding, including a Rs. 76 lakh DST-FIST grant. She has also played a pivotal role as the IQAC Coordinator (2018-2022), ensuring institutional excellence. Additionally, she has served as the Institution Innovation Cell (IIC) President, fostering entrepreneurship and innovation. Her industry collaborations with IBM, Rently, and L&T EDUTECH have enriched student learning experiences. She has contributed as a Board of Studies member in multiple colleges and played an active role in doctoral committees and inspection commissions under Bharathiar University.

🏅 Awards and Recognition

Dr. N. Tajunisha’s contributions to academia have been widely recognized through numerous awards and honors. She received the prestigious Senior Educator and Scholar Award from NFED in 2017 for her outstanding contributions to Computer Science education. She has also been honored with the Best Paper Award at the IEEE International Conference held at Satyabhama University in 2010. Her research excellence is reflected in her extensive publication record, including nine Scopus-indexed journal papers. Her leadership in institutional development led to Sri Ramakrishna College of Arts & Science for Women achieving an A+ grade in NAAC Cycle II under her tenure as IQAC Coordinator. Additionally, she has been an invited session chair at international conferences and serves as a reviewer for top-tier journals. Her commitment to fostering innovation and research has positioned her as a thought leader in Data Mining, Machine Learning, and Big Data Analytics.

🌍 Research Skills On Computer Science

Dr. N. Tajunisha’s research expertise spans Data Mining, Machine Learning, Big Data Analytics, and Networks. She has successfully guided three Ph.D. scholars and is currently mentoring five more, contributing to advancements in computational intelligence and predictive analytics. Her research has secured substantial funding, including a Rs. 3.17 lakh UGC Minor Research Project and Rs. 76 lakh for a DST-FIST project. With 34 journal papers, 25 conference papers, and two books to her credit, she has made significant contributions to her field. She actively collaborates with industry leaders like IBM, Rently, and L&T EDUTECH, ensuring practical applications of her research. Her ability to integrate academic knowledge with real-world solutions makes her a leading researcher in her domain. She has also been a reviewer for international journals and a committee member in doctoral research evaluations, further enhancing her impact in the field.

📖 Publication Top Notes

  • Performance analysis of k-means with different initialization methods for high-dimensional data
    Author(s): VSN Tajunisha
    Journal: International Journal of Artificial Intelligence and Applications
    Citations: 35
    Year: 2010

  • An efficient method to improve the clustering performance for high dimensional data by principal component analysis and modified K-means
    Author(s): N Tajunisha, V Saravanan
    Journal: International Journal of Database Management Systems
    Citations: 20
    Year: 2011

  • An increased performance of clustering high dimensional data using Principal Component Analysis
    Author(s): N Tajunisha, V Saravanan
    Conference: 2010 First International Conference on Integrated Intelligent Computing
    Citations: 19
    Year: 2010

  • A study on evolution of data analytics to big data analytics and its research scope
    Author(s): S Sruthika, N Tajunisha
    Conference: 2015 International Conference on Innovations in Information, Embedded and …
    Citations: 14
    Year: 2015

  • Predicting Student Performance Using MapReduce
    Author(s): N Tajunisha, M Anjali
    Journal: International Journal of Emerging and Computer Science
    Citations: 14
    Year: 2015

  • A new approach to improve the clustering accuracy using informative genes for unsupervised microarray data sets
    Author(s): N Tajunisha, V Saravanan
    Journal: International Journal of Advanced Science and Technology
    Citations: 10
    Year: 2011

  • Automatic classification of ovarian cancer types from CT images using deep semi-supervised generative learning and convolutional neural network
    Author(s): N Nagarajan, P.H. Tajunisha
    Journal: Revue d’Intelligence Artificielle
    Citations: 9
    Year: 2021

  • Classification of cancer datasets using artificial bee colony and deep feed-forward neural networks
    Author(s): M Karunyalakshmi, N Tajunisha
    Journal: International Journal of Advanced Research in Computer and Communication …
    Citations: 8
    Year: 2017

  • Concept and Term-Based Similarity Measure for Text Classification and Clustering
    Author(s): B Sindhiya, N Tajunisha
    Journal: IJERST
    Citations: 7
    Year: 2014

  • Optimal Parameter Selection-Based Deep Semi-Supervised Generative Learning and CNN for Ovarian Cancer Classification
    Author(s): PH Nagarajan, N Tajunisha
    Journal: ICTACT Journal on Soft Computing
    Citations: 5
    Year: 2023

Lin Chen | Computer Science | Best Researcher Award

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Prof. Lin Chen | Computer Science | Best Researcher Award

Prof. Lin Chen, Macao Polytechnic University, Macau

Lin Chen, a distinguished scholar and innovator in Computer Science, serves as a full professor at Macao Polytechnic University since 2025. He obtained his B.Sc. in Electrical Engineering from Southeast University (2002), an M.Sc. in Networking from the University of Paris 6 (2005), and an Engineer Diploma and Ph.D. in Computer Science from Telecom ParisTech (2005, 2008). Dr. Chen further achieved his Habilitation thesis at the University of Paris-Sud in 2017. His illustrious career spans academia and research, including tenures as an associate professor at the University of Paris-Sud and a full professor at Sun Yat-sen University. Renowned for contributions to distributed algorithms, energy-efficient systems, and network security, he has published over 100 papers, with several receiving accolades. He is a Junior Member of the Institut Universitaire de France (IUF) and an editor for IEEE Systems Journals, demonstrating leadership in advancing the field of networked systems.

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Suitability for the “Research for Best Researcher Award” – Lin Chen

Lin Chen’s qualifications and achievements make him an outstanding candidate for the “Research for Best Researcher Award.” As a full professor of Computer Science at Macao Polytechnic University, his distinguished academic and research background places him among the leading experts in his field. His educational journey, which spans multiple prestigious institutions, reflects a profound commitment to advancing knowledge in Computer Science and Networking. Holding a Ph.D. in Computer Science and Networking from Telecom ParisTech (ENST), along with a Habilitation thesis from the University of Paris-Sud, Lin’s academic credentials are both comprehensive and prestigious.

Lin Chen’s research contributions, particularly in the realm of distributed algorithms and protocols for emerging networked systems, are exemplary. His work on energy efficiency, resilience, and security is highly relevant to current and future technological advancements. Having published over 100 journal and conference papers, with several highly cited works, Lin’s research is not only influential but recognized as a major contribution to the field. His three ESI Highly Cited Papers and multiple Best Paper and Best Student Paper awards underline his impact in the academic community.

🎓 Education 

Lin Chen’s academic journey reflects a steadfast commitment to excellence and interdisciplinary learning. He earned his B.Sc. in Electrical Engineering from Southeast University in 2002, laying a strong foundation in technical problem-solving and system design. Driven by his passion for innovation, he pursued an M.Sc. in Networking at the University of Paris 6 in 2005, where he developed expertise in network protocols and optimization. His quest for advanced knowledge led him to Telecom ParisTech (ENST), where he received an Engineer Diploma and a Ph.D. in Computer Science and Networking in 2005 and 2008, respectively, focusing on distributed systems and secure network architecture. Further solidifying his credentials, he achieved his Habilitation thesis at the University of Paris-Sud in 2017, showcasing his authority in energy-efficient and resilient systems. This educational foundation underscores Dr. Chen’s expertise in bridging theoretical innovation with practical applications in emerging technologies.

💼 Professional Experience 

Lin Chen boasts a remarkable professional trajectory spanning prestigious institutions and transformative research. He began his academic career as an associate professor in the Department of Computer Science at the University of Paris-Sud (2009–2019), where he spearheaded groundbreaking projects on distributed algorithms and energy-efficient systems. In 2019, he advanced to a full professorship at Sun Yat-sen University, focusing on secure and resilient networked systems, before joining Macao Polytechnic University in 2025. Dr. Chen’s leadership extends beyond academia, serving as the Chair of the IEEE TCGCC SIG on Green and Sustainable Networking. He has significantly influenced the field through editorial roles in IEEE Systems Journals and guest editing for top-tier publications. His prolific contributions include organizing international conferences, such as ICCCN and INFOCOM workshops, underscoring his commitment to fostering innovation in computer science. His work remains a testament to his dedication to advancing next-generation networking technologies.

🏅 Awards and Recognition 

Lin Chen’s exceptional contributions have garnered numerous accolades, reflecting his influence in computer science and networking. He received the 2018 CNRS Bronze Medal, a prestigious recognition reserved for exemplary researchers, being one of only two awardees in ICT that year. His research has produced over 100 impactful publications, including three journal papers recognized as ESI Highly Cited Papers and three conference papers awarded Best Paper or Best Student Paper honors. Dr. Chen’s leadership and expertise have earned him the distinction of Junior Member of the Institut Universitaire de France (IUF). His editorial roles with IEEE Systems Journals and guest editorships in leading publications like IEEE Wireless Communications Magazine further underscore his contributions. As a driving force behind initiatives such as the IEEE TCGCC SIG on Green Networking, he continues to shape the future of secure, energy-efficient, and sustainable networked systems, inspiring researchers worldwide.

🌍 Research Skills On Computer Science

Lin Chen is a leading researcher specializing in distributed algorithms, energy efficiency, resilience, and network security. His work is characterized by a multidisciplinary approach, seamlessly integrating theoretical insights with practical solutions. He has developed innovative protocols for emerging networked systems, addressing critical challenges in energy efficiency and sustainable computing. Dr. Chen’s expertise extends to secure network architecture, ensuring robust communication frameworks for dynamic and large-scale systems. His research leverages advanced methodologies, including machine learning and artificial intelligence, to optimize network performance and enhance resilience. With a focus on green networking, he has pioneered strategies for reducing energy consumption in ultra-dense networks. His technical acumen is complemented by his extensive experience in project leadership and collaboration, as demonstrated by his active participation in international conferences and editorial roles. Dr. Chen’s research continues to influence the development of scalable, secure, and sustainable next-generation technologies.

📖 Publication Top Notes

  • Routing metrics of cognitive radio networks: A survey
    Authors: M Youssef, M Ibrahim, M Abdelatif, L Chen, AV Vasilakos
    Journal: IEEE Communications Surveys & Tutorials
    Citation: 388
    Year: 2013
  • A game theoretical framework on intrusion detection in heterogeneous networks
    Authors: L Chen, J Leneutre
    Journal: Information Forensics and Security, IEEE Transactions on
    Citation: 190
    Year: 2009
  • An auction framework for spectrum allocation with interference constraint in cognitive radio networks
    Authors: L Chen, S Iellamo, M Coupechoux, P Godlewski
    Journal: INFOCOM, 2010 Proceedings IEEE
    Citation: 124
    Year: 2010
  • Joint multiuser DNN partitioning and computational resource allocation for collaborative edge intelligence
    Authors: X Tang, X Chen, L Zeng, S Yu, L Chen
    Journal: IEEE Internet of Things Journal
    Citation: 110
    Year: 2020
  • Energy-efficiency maximization for cooperative spectrum sensing in cognitive sensor networks
    Authors: M Zheng, L Chen, W Liang, H Yu, J Wu
    Journal: IEEE Transactions on Green Communications and Networking
    Citation: 101
    Year: 2016
  • A distributed demand-side management framework for the smart grid
    Authors: A Barbato, A Capone, L Chen, F Martignon, S Paris
    Journal: Computer Communications
    Citation: 98
    Year: 2015
  • On oblivious neighbor discovery in distributed wireless networks with directional antennas: Theoretical foundation and algorithm design
    Authors: L Chen, Y Li, AV Vasilakos
    Journal: IEEE/ACM Transactions on Networking
    Citation: 88*
    Year: 2017
  • Secure cooperative spectrum sensing and access against intelligent malicious behaviors
    Authors: W Wang, L Chen, KG Shin, L Duan
    Journal: INFOCOM, 2014 Proceedings IEEE
    Citation: 86*
    Year: 2014
  • On heterogeneous neighbor discovery in wireless sensor networks
    Authors: L Chen, R Fan, K Bian, M Gerla, T Wang, X Li
    Journal: 2015 IEEE Conference on Computer Communications (INFOCOM)
    Citation: 80
    Year: 2015
  • An efficient auction-based mechanism for mobile data offloading
    Authors: S Paris, F Martignon, I Filippini, L Chen
    Journal: IEEE Transactions on Mobile Computing
    Citation: 75
    Year: 2015

Sheeja Rani S | Computer Science Award | Best Researcher Award

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Dr. Sheeja Rani S | Computer Science Award | Best Researcher Award

👤 Dr. Sheeja Rani S, American University of Sharjah, United Arab Emirates

Dr. Sheeja Rani S is a visionary researcher and academician specializing in Computer Science and Engineering, with a strong focus on Wireless Sensor Networks, IoT, and Smart Grids. She earned her Ph.D. from Noorul Islam Centre for Higher Education in 2023, where her thesis emphasized energy-efficient clustering algorithms for wireless sensor networks. Her academic journey is complemented by over a decade of teaching and research experience, where she worked on innovative solutions in cybersecurity, cloud computing, and machine learning. Currently serving as a Postdoctoral Research Assistant at the American University of Sharjah, Dr. Sheeja collaborates with leading experts on cutting-edge projects. With over 20 journal papers, numerous conference contributions, and a passion for impactful research, she strives to advance technology and foster intellectual growth. Her mission is to combine her expertise and mentorship skills to inspire future innovators while contributing to meaningful explorations in academia and beyond.

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🌟 Evaluation of Dr. Sheeja Rani S for the Research for Best Researcher Award

Summary of Suitability

Dr. Sheeja Rani S stands out as a highly qualified candidate for the “Research for Best Researcher Award,” showcasing an exceptional academic trajectory, prolific research output, and impactful contributions to multiple interdisciplinary domains. With a Ph.D. in Computer Science and Engineering focusing on improving energy efficiency in wireless sensor networks (WSNs), her research has addressed critical challenges in IoT, cloud computing, and smart grid technologies. These fields are not only contemporary but also pivotal for sustainable and secure technological advancements.

🎓 Education 

  • Ph.D. in Computer Science and Engineering (2023)
    Noorul Islam Centre for Higher Education
    Thesis: Improving Energy Efficiency Based on Clustering Algorithms for Wireless Sensor Networks.
  • M.E. in Computer Science and Engineering (2012)
    Noorul Islam Centre for Higher Education
  • M.Sc. Integrated Software Engineering (2009)
    Anna University, Chennai

Dr. Sheeja’s academic pursuits are rooted in innovation, particularly in optimizing computational techniques for energy efficiency and data security. Her Ph.D. research laid a foundation for creating advanced clustering mechanisms in wireless sensor networks, while her postgraduate and undergraduate studies focused on mastering computer science fundamentals and software engineering. She remains committed to lifelong learning and applying her knowledge to address emerging technological challenges.

💼  Professional Experience 

  • Postdoctoral Research Assistant (2023-Present)
    American University of Sharjah

    • Research on cybersecurity, smart grids, and cloud computing.
    • Published 12 journal papers in high-impact areas like IoT and machine learning.
  • Research Assistant (2022-2023)
    University of Sharjah

    • Focused on IoT, WSNs, and cloud computing.
    • Published 11 journal papers on financial distress prediction and IoT advancements.
  • Assistant Professor (2012-2021)
    John Cox Memorial CSI Institute of Technology

    • Taught advanced programming and database systems.
    • Managed academic coordination and examination processes.

Dr. Sheeja’s professional journey showcases a blend of teaching, research, and academic leadership, reflecting her dedication to advancing the field of computer science.

🏅 Awards and Recognitions 

  • Best Researcher Award (2023) – Recognized for impactful research in IoT and WSN.
  • Academic Excellence Award (2021) – Awarded for outstanding teaching and mentorship.
  • Research Grant Award (2022) – Funded for innovative studies on machine learning and cybersecurity.
  • Publication Excellence Award (2023) – Honored for prolific contributions to reputed journals.

Dr. Sheeja has consistently received accolades for her exceptional academic and research contributions. Her achievements reflect her dedication to excellence and her ability to produce innovative solutions that address global challenges.

🌍  Research Skills On Computer Science Award 

Dr. Sheeja’s research expertise spans:

  • Wireless Sensor Networks (WSN): Energy-efficient routing and clustering.
  • IoT: Developing secure and scalable architectures for smart environments.
  • Machine Learning: Applying predictive models for financial and cybersecurity domains.
  • Smart Grids: Integration of AI for optimal energy distribution.
  • Cloud Computing: Enhancing reliability and fault tolerance in virtualized environments.

📖 Publication Top Notes

Improved buffalo optimized deep feed forward neural learning based multipath routing for energy-efficient data aggregation in WSN
    • Authors: SS Rani, KS Sankar
    • Citation: Measurement: Sensors 27, 100662
    • Cited by: 8
    • Year: 2023
Optimized deep learning for Congestion-Aware continuous target tracking and boundary detection in IoT-Assisted WSN
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: IEEE Sensors Journal 23 (7), 7938-7948
    • Cited by: 8
    • Year: 2023
Enhancing Supply Chain Management with Deep Learning and Machine Learning Techniques: A Review
    • Authors: SSR Khedr, Ahmed M
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity, 100379
    • Cited by: 5
    • Year: 2024
Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: The Journal of Supercomputing 79 (15), 16940-16962
    • Cited by: 4
    • Year: 2023
Enhancing financial distress prediction through integrated Chinese Whisper clustering and federated learning
    • Authors: AI Al Ali, AM S S Rani Khedr
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity 10 (3), 100344
    • Cited by: 2
    • Year: 2024