Srinidhi Arulselvan | Mathematics | Editorial Board Member

Ms. Srinidhi Arulselvan | Mathematics | Editorial Board Member

Research Scholar | Alagappa University | India

Ms. Srinidhi Arulselvan is an emerging researcher in control systems and applied mathematics, with notable contributions to non-fragile reliable control, sampled-data and memory-based control, multi-agent systems, and vehicle suspension systems affected by actuator faults, delays, and disturbances. Her research interests focus on Lyapunov-based stability analysis, improved and looped Lyapunov–Krasovskii functionals, fault-tolerant and disturbance-rejection control, descriptor systems, and robust nonlinear dynamics with strong engineering applications. She demonstrates solid research skills in mathematical modeling, admissibility analysis, delay-dependent stability criteria, controller synthesis, and simulation-based validation. Ms. Srinidhi has authored 6 Scopus-indexed documents, published in reputable journals including Nonlinear Dynamics, Journal of the Franklin Institute, and International Journal of Robust and Nonlinear Control. Her work has received 12 Scopus citations, with an h-index of 2, reflecting consistent scholarly impact at an early career stage. She has gained academic recognition through high-quality peer-reviewed publications and international collaborations. Overall, her research profile highlights strong theoretical depth, growing visibility, and promising potential for sustained impact in advanced control engineering and nonlinear systems research.

 

Citation Metrics (Scopus Preview)

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Kristina Pestaria Sinaga | Mathematics | Research Excellence Award

Dr. Kristina Pestaria Sinaga | Mathematics | Research Excellence Award

Independent Researcher | Indonesia

Dr. Kristina Pestaria Sinaga is an independent researcher recognized for influential contributions to machine learning and computational intelligence, particularly in clustering and multi-view learning. Her research interests span multi-view learning, federated learning, unsupervised and fuzzy clustering, pattern recognition, and Edge AI, with strong emphasis on scalable, privacy-preserving, and feature-efficient algorithms. Her research skills include advanced algorithm design, K-means and fuzzy C-means variants, feature reduction, entropy-based learning, federated analytics, and real-world data modeling across marketing, telecommunications, and socio-economic domains. She has received notable academic recognition through high-impact publications in leading journals such as IEEE Access, Pattern Recognition, and IEEE TPAMI, reflecting sustained scholarly excellence. Dr. Sinaga’s work demonstrates global collaboration and practical relevance, shaping modern unsupervised learning paradigms. According to Scopus-linked metrics, she has over 3,174 citations, 20 research documents, an h-index of 7, and an i10-index of 6, underscoring her growing international research impact and consistency in high-quality scientific output.

Citation Metrics (Scopus / Google Scholar)

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