Sakthivel Ramalingam | Computer Science | Editorial Board Member

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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

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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

Rounak Raman | Information Technology | Young Scientist Award

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Mr. Rounak Raman | Information Technology | Young Scientist Award

Netaji Subhas University of Technology | India

Mr. Rounak Raman research journey reflects a diverse and impactful engagement across multidisciplinary domains including Artificial Intelligence, Wireless Sensor Networks, IoT Security, and Neuroinformatics. At the forefront of innovation, multiple projects demonstrate a strong alignment with real-world challenges and technical excellence. The development of the EEG Data Analysis System and multimodal neurofeedback loop underlines expertise in biomedical signal processing and applied AI for cognitive enhancement, contributing to measurable improvements in attentiveness and engagement. In IoT and network optimization, the implementation of the Energy Aware Hybrid Clustering Protocol (EAHCP) showcased advancements in energy-efficient communication, achieving notable performance gains in scalability and mobility management. Research on secure IoT frameworks, such as the Hierarchical Key Rotation and Isolation Protocol (HKRISRP), reinforced resilience in wireless networks through lightweight cryptography and dynamic key rotation, enhancing both security and energy performance. Additional contributions in opportunistic networks introduced context-aware, trust-based, and collision-avoidant models that optimized data aggregation and reliability through intelligent decision mechanisms and trajectory optimization. The pursuit of Generative AI culminated in the development of SyntheX, a document analysis system integrating semantic search and transcription models to streamline enterprise knowledge management. Collectively, these works exemplify a strong commitment to advancing applied research in AI, cybersecurity, and intelligent network systems

Featured Publication

Raman, R., Yadav, A., Kukreja, D., & Sharma, D. K. (2025). CONTEXT-NET: A context-aware nexus-based aggregation protocol for opportunistic networks. Internet of Things, 25, 101809. https://doi.org/10.1016/j.iot.2025.101809

Lei Ren | Electronic Devices | Best Researcher Award

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Dr. Lei Ren | Electronic Devices | Best Researcher Award

Lecturer at Nantong university, China

Lei Ren  was born in Jiangsu Province, China, in 1991. He earned his B.S. and Ph.D. in Electrical Engineering from Nanjing University of Aeronautics and Astronautics (NUAA) in 2013 and 2019. Currently, he serves as a Lecturer at the School of Electrical and Automation, Nantong University . His research focuses on static inverters  and condition monitoring of power electronic converters . With multiple publications in top IEEE journals , his work contributes to advancements in power electronics and energy efficiency. His expertise in converter design and health monitoring continues to impact the field of electrical engineering. 🚀

Publication Profile

Orcid

Academic Background

Lei Ren embarked on his academic journey in Electrical Engineering  at Nanjing University of Aeronautics and Astronautics (NUAA) 🏫, Nanjing, China. He earned his Bachelor of Science (B.S.) degree in 2013 , laying a strong foundation in the field. Driven by a passion for innovation and research, he pursued a Ph.D. at the same university, successfully completing it in 2019 . His academic achievements reflect his dedication to advancing power electronics  and electrical engineering. Through rigorous studies and research, he continues to contribute to technological advancements in the field. 🚀

Professional Background

Lei Ren is a dedicated Lecturer at the School of Electrical and Automation, Nantong University , where he imparts knowledge and inspires future engineers. His research focuses on static inverters  and the condition monitoring of power electronic converters , aiming to enhance efficiency and reliability in power systems. Passionate about innovation, he explores advanced techniques to improve energy conversion and system diagnostics . Through his academic and research contributions , he plays a vital role in shaping the future of electrical engineering, fostering technological advancements, and mentoring the next generation of engineers. 🚀

Research Focus

Lei Ren is actively engaged in research on static inverters  and condition monitoring of power electronic converters . His work focuses on improving energy efficiency and system reliability. He has published several high-impact papers in prestigious journals, including the IEEE Transactions on Power Electronics and IET Power Electronics 📖. His studies cover topics such as transformerless high-gain converters, capacitor voltage regulation, and health monitoring of power transistors. Through his innovative research, Lei Ren contributes to advancements in power electronics, enhancing the performance and sustainability of modern electrical systems. 🚀

Publication Top Notes

 

1️⃣ Capacitor Voltage Regulation Strategy for 7-Level Single DC Source Hybrid Cascaded Inverter ⚡📖
Year: 2022 | IEEE Journal of Emerging and Selected Topics in Power Electronics

2️⃣ Self-Adaption Dead-Time Setting for the SiC MOSFET Boost Circuit in the Synchronous Working Mode 🔧🔋
Year: 2022 | IEEE Access

3️⃣ Transformer-Less High Gain Three-Port Converter With Low Voltage Stress and Reduced Switches for Standalone PV Systems ☀️⚙️
Year: 2022 |  IEEE Transactions on Power Electronics

4️⃣ A Series Incremental Inductance Detection Based Sensorless Startup Method for DSEM ⚙️🔍
Year: 2021 |  IEEE Transactions on Industrial Electronics

5️⃣ Parameter Identification Based on Linear Model for Buck Converters ⚡📊
Year: 2021 |  Electrical Engineering

Conclusion

Lei Ren is a highly qualified researcher in power electronics with strong technical expertise and impactful publications. His work on inverters and power monitoring systems is significant for modern energy applications. To further strengthen his eligibility for the Best Researcher Award, he could expand collaborations, increase research citations, and take on leadership roles in funded projects. Given his current contributions, he is a strong candidate for the award.