Sakthivel Ramalingam | Computer Science | Editorial Board Member

Published on by Young Scientists Awards

Assist. Prof. Dr. Sakthivel Ramalingam | Computer Science | Editorial Board Member

Vellore Institute of Technology Chennai | India

Assist. Prof. Dr. Sakthivel Ramalingamthe researcher’s work spans advanced control theory, nonlinear systems, and complex dynamical networks with a strong emphasis on cyber-physical security, resilient control design, and intelligent fuzzy systems. Their contributions focus on developing robust, finite-time, and event-triggered control and filtering strategies for Takagi–Sugeno fuzzy models, Markovian jump systems, networked control systems, and multi-agent networks subjected to uncertainties, delays, cyber attacks, actuator faults, and communication constraints. Their research advances include designing synchronization mechanisms for fractional-order systems, creating hybrid-triggered and observer-based state estimation methods, and proposing fault-tolerant and non-fragile control algorithms for large-scale intelligent systems. With more than thirty-eight SCIE-indexed publications in high-impact journals such as IEEE Transactions on Fuzzy Systems, Neural Networks, Communications in Nonlinear Science and Numerical Simulation, Applied Mathematics and Computation, Nonlinear Dynamics, and the Journal of the Franklin Institute, their work significantly contributes to resilient autonomous systems, intelligent vehicles, stochastic complex networks, and distributed optimization. Their research extends to sampled-data control, interval type-2 fuzzy systems, polynomial fuzzy models, semi-Markovian jump systems, and fractional-order complex networks. They also engage in experimental validation, synchronization analysis, and stability theory, aiming to enhance the reliability, safety, and robustness of modern intelligent systems in uncertain and adversarial environments.

Featured Publications

Sakthivel, R., Sakthivel, R., Kaviarasan, B., & Alzahrani, F. (2018). Leader-following exponential consensus of input saturated stochastic multi-agent systems with Markov jump parameters. Neurocomputing, 287, 84–92.

Sakthivel, R., Sakthivel, R., Kaviarasan, B., Lee, H., & Lim, Y. (2019). Finite-time leaderless consensus of uncertain multi-agent systems against time-varying actuator faults. Neurocomputing, 325, 159–171.

Sakthivel, R., Sakthivel, R., Nithya, V., Selvaraj, P., & Kwon, O. M. (2018). Fuzzy sliding mode control design of Markovian jump systems with time-varying delay. Journal of the Franklin Institute, 1–15.

Sakthivel, R., Kwon, O. M., Park, M. J., Choi, S. G., & Sakthivel, R. (2021). Robust asynchronous filtering for discrete-time T–S fuzzy complex dynamical networks against deception attacks. IEEE Transactions on Fuzzy Systems, 30(8), 3257–3269.

Mehdi Saadallah | Computer Science | Best Researcher Award

Published on by Young Scientists Awards

Mr. Mehdi Saadallah | Computer Science
| Best Researcher Award

Vrije Universiteit Amsterdam | Netherlands

Mr. Mehdi Saadallah research focuses on advancing the integration of artificial intelligence (AI) and automation in cybersecurity operations, emphasizing the intersection between technology, human behavior, and organizational structures. It investigates how AI-driven tools influence professional identity, decision-making, and collaboration within Security Operations Centers (SOCs), where analysts and algorithms coexist in dynamic threat environments. By applying frameworks such as Paradox Theory, Organizational Routine Theory, and Identity Work Theory, the work uncovers the tensions, adaptations, and emergent practices that arise when automation transforms traditional cybersecurity routines. Empirical insights are drawn from multinational enterprises across diverse sectors, revealing how organizations balance efficiency, control, and trust in AI-augmented defense systems. The research also develops conceptual and operational models for AI-assisted vulnerability management and SOC modernization, providing a blueprint for improving detection, response, and resilience in complex digital ecosystems. Beyond theory, it delivers applied innovations that enhance cybersecurity governance, human–AI trust calibration, and automation ethics. Through interdisciplinary methods combining qualitative inquiry, computational analysis, and organizational modeling, the work contributes to redefining cybersecurity as a socio-technical discipline—bridging academic rigor and industrial application to guide the future of intelligent, adaptive, and human-centered cyber defense frameworks.

Featured Publications

Saadallah, M. (2025). Harmonizing paradoxical tensions in SOCs: A strategic model for integrating AI, automation, and human expertise in cyber defense and incident response. In Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS-58). https://doi.org/10.24251/HICSS.2025.723

Saadallah, M., Shahim, A., & Khapova, S. (2025). Reconciling tensions in Security Operations Centers: A Paradox Theory approach. Big Data and Cognitive Computing, 9(11), 278. https://doi.org/10.3390/bdcc9110278

Saadallah, M., Shahim, A., & Khapova, S. (2025). Optimizing AI and human expertise integration in cybersecurity: Enhancing operational efficiency and collaborative decision-making. PriMera Scientific Engineering, 6(1), 177. https://doi.org/10.56831/psen-06-177

Saadallah, M., Shahim, A., & Khapova, S. (2024). Multi-method approach to human expertise, automation, and artificial intelligence for vulnerability management. In Advances in Intelligent Systems and Computing (pp. xxx–xxx). Springer. https://doi.org/10.1007/978-3-031-65175-5_29

 Saadallah, M., Shahim, A., & Khapova, S. (2024). Synergizing human expertise, automation, and artificial intelligence for vulnerability management. PriMera Scientific Engineering, 5(10), 160. https://doi.org/10.56831/psen-05-160

Dharini N | Computer Science | Young Scientist Award

Published on by Young Scientists Awards

Dr. Dharini N | Computer Science | Young Scientist Award

Associate Professor at R.M.K College of Engineering and Technology, India

Dr. Dharini N is an accomplished academic and researcher in the field of Computer Science Engineering with a specialization in Cyber Security. She is an Associate Professor at R.M.K. College of Engineering and Technology and a recognized research supervisor at Anna University. With a Ph.D. in Wireless Sensor Networks (WSN) from Anna University, she has made significant contributions to trust establishment under multiple attacks in WSN. Dr. Dharini has an impressive academic record, earning a Gold Medal during her M.E. at Velammal Engineering College and consistently achieving top ranks throughout her studies. Her research work includes over 10 SCI and Scopus-indexed publications, focusing on topics like intrusion detection, IoT security, and machine learning. She has actively contributed to academic growth through roles like coordinator for NAAC and NBA accreditations and has organized DST-SERB-sponsored seminars. Her dedication to education, research, and cybersecurity innovation marks her as an inspiring young scientist.

Professional Profile

Education

Dr. Dharini N has an exemplary academic background in Computer Science and Engineering. She earned her Ph.D. from Anna University, specializing in Wireless Sensor Networks, with a focus on trust establishment under multiple attacks. Her commitment to excellence was evident during her M.E. in Computer Science and Engineering at Velammal Engineering College, where she graduated with a Gold Medal and ranked among the top achievers. Dr. Dharini also holds a B.E. degree in Computer Science and Engineering from Velammal Engineering College, where she consistently demonstrated academic distinction. Her educational journey reflects a strong foundation in computer science principles, coupled with advanced expertise in cybersecurity and wireless communication. This robust academic preparation has fueled her impactful research contributions in intrusion detection, IoT security, and machine learning, establishing her as a leading figure in her field.

Professional Experience

Dr. Dharini N brings a wealth of professional experience in academia and research. She currently serves as an Associate Professor in the Department of Computer Science and Engineering at Velammal Engineering College, where she has been a dedicated faculty member since 2010. Over the years, she has excelled in teaching, research, and mentoring, fostering the academic growth of students and guiding them in cutting-edge research projects. Her expertise lies in Wireless Sensor Networks, IoT security, and Machine Learning, areas where she has made significant contributions through publications in high-impact journals and conferences. Dr. Dharini is actively involved in curriculum development and has played a key role in enhancing the quality of education within her institution. She collaborates extensively with industry and academic peers, bridging the gap between theoretical knowledge and practical applications, making her an influential educator and researcher in the field of computer science.

Research Interest

Dr. Dharini N’s research interests are deeply rooted in advancing technology and addressing contemporary challenges in the field of computer science. Her primary focus lies in Wireless Sensor Networks, where she explores innovative solutions to optimize energy efficiency, scalability, and reliability in communication systems. She is equally passionate about IoT security, working on robust frameworks to safeguard data integrity and privacy in the ever-expanding Internet of Things ecosystem. Additionally, Dr. Dharini has a keen interest in Machine Learning, leveraging data-driven models to solve complex problems in diverse domains. Her research integrates theoretical rigor with practical applications, addressing real-world issues and contributing to technological advancements. By collaborating with academia and industry, she ensures her work remains relevant and impactful. Dr. Dharini’s commitment to pushing boundaries in these areas has resulted in numerous publications, underlining her contribution to cutting-edge research and innovation in computer science.

Award and Honor

Dr. Dharini N has been recognized with numerous awards and honors that highlight her exceptional contributions to academia and research. Her innovative work in computer science has earned her accolades from prestigious institutions, showcasing her dedication and expertise. She has received awards for excellence in research, acknowledging her significant advancements in Wireless Sensor Networks, IoT security, and Machine Learning. Dr. Dharini’s commitment to fostering knowledge and innovation has also been celebrated through teaching awards and commendations for mentoring students in their academic pursuits. Her papers, presented at renowned international conferences and published in leading journals, have garnered widespread acclaim, further solidifying her reputation as a thought leader in her field. These honors not only reflect her scholarly impact but also inspire her to continue pursuing excellence, contributing to cutting-edge research, and advancing the frontiers of technology.

Conclusion

Dr. Dharini N exhibits strong qualifications and achievements that align well with the criteria for a Young Scientist Award. Her consistent academic excellence, research contributions, and leadership in cybersecurity make her a strong contender. Focusing on increasing her research impact, securing major funding, and expanding interdisciplinary work will further solidify her candidacy for prestigious recognitions.

Publications Top Noted

  • Title: Distributed detection of flooding and gray hole attacks in Wireless Sensor Network
    Authors: N Dharini, R Balakrishnan, AP Renold
    Year: 2015
    Citation: 32
  • Title: Towards a novel privacy-preserving distributed multiparty data outsourcing scheme for cloud computing with quantum key distribution
    Authors: D Dhinakaran, D Selvaraj, N Dharini, SE Raja, C Priya
    Year: 2024
    Citation: 23
  • Title: ELPC-trust framework for wireless sensor networks
    Authors: N Dharini, N Duraipandian, J Katiravan
    Year: 2020
    Citation: 15
  • Title: Intrusion Detection in Novel WSN-Leach Dos Attack Dataset using Machine Learning based Boosting Algorithms
    Authors: N Dharini, J Katiravan, SP DM, SS VA
    Year: 2023
    Citation: 8
  • Title: A Two level Detection of Routing layer attacks in Hierarchical Wireless Sensor Networks using learning-based energy prediction
    Authors: J Katiravan
    Year: 2015
    Citation: 8
  • Title: Wireless Sensor Network-based Detection of Poisonous Gases Using Principal Component Analysis
    Authors: USSM Dharini N, Jeevaa Katriavan
    Year: 2022
    Citation: 3
  • Title: A novel IDS to detect multiple DoS attacks with network lifetime estimation based on learning-based energy prediction algorithm for hierarchical WSN
    Authors: N Dharini, N Duraipandian, J Katiravan
    Year: 2019
    Citation: 2
  • Title: Botnet Attack Detection in IoT-Based Security Camera Device Using Principal Component Analysis with Various Machine Learning Algorithms
    Authors: N Dharini, SP Shakthi, SS Shruthi
    Year: 2022
    Citation: 1
  • Title: Intrusion Detection in Wireless Sensor Networks using Optics Algorithm
    Authors: N Dharini, J Sowndharya, P Sudha
    Year: 2022
    Citation: 1
  • Title: Botnet Attack Detection in IoT Devices using Ensemble Classifiers with Reduced Feature Space
    Authors: N Dharini, J Katiravan, SP Shakthi
    Year: 2024
    Citation: 0
  • Title: Regression Analysis-Based Predictive Model for E-Commerce Application
    Authors: G Sudev, M Shyam, N Dharini
    Year: 2023
    Citation: 0
  • Title: Big Data analysis based intrusion detection in WSN with reduced features
    Authors: D N, SP D. M, SS V. A
    Year: 2023
    Citation: 0
  • Title: Handwritten Character Recognition Based on Adabelief Optimized Convolutional Neural Network
    Authors: SK Sahani, SR Kk, N Dharini
    Year: 2023
    Citation: 0