Srinidhi Arulselvan | Mathematics | Editorial Board Member

Published on by Scientific World Research Awards

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)

12
9
6
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12

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6

h-index

2

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h-index

Featured Publications

 

Kristina Pestaria Sinaga | Mathematics | Research Excellence Award

Published on by Scientific World Research Awards

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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2400
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3174

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20

h-index

7

Citations

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h-index

View Google Scholar 

Featured Publications

Huiyi Xia | Mathematics | Best Researcher Award

Published on by Scientific World Research Awards

Dr. Huiyi Xia | Mathematics | Best Researcher Award

Associate Professor | Nanfang College of Sun Yat-sen University | China

Dr. Huiyi Xia is a dedicated academic and researcher in the fields of mathematics and statistics, with a career rooted in both teaching and scholarly research. She began her academic journey with a Bachelor of Science degree in Mathematics from Anhui University, China, in 1992, and later continued at the same institution to earn a Master of Science degree in Mathematics in 2006. Pursuing advanced research, she completed her Ph.D. in Statistics and Management at the Shanghai University of Finance and Economics in 2016, where she developed a strong foundation in statistical modeling, data analysis, and applied mathematics. Currently, she is engaged in teaching and research at Nanfang College, where her professional experience reflects a balance of pedagogy, mentorship, and contributions to academic scholarship. Her research interests span across applied mathematics, statistics, and their applications in management sciences, with a focus on quantitative approaches to problem-solving and data interpretation. Over the years, Dr. Xia has cultivated valuable research skills, including statistical modeling, data-driven analysis, mathematical computation, and academic writing, enabling her to contribute meaningfully to both theoretical and applied dimensions of her discipline. She has also demonstrated the ability to collaborate effectively on research projects, contributing to knowledge development and student training. Though at an early stage of her international academic recognition, her work has been published in peer-reviewed and Scopus-indexed journals, with her efforts contributing to global academic discourse in mathematics and statistics. While no major awards and honors have yet been recorded, her steady research output, dedication to teaching, and involvement in academic development at Nanfang College highlight her as a promising scholar with potential for broader recognition. In conclusion, Dr. Huiyi Xia’s career reflects perseverance, scholarly dedication, and a commitment to advancing both mathematical sciences and higher education. With continued focus on Q1 journal publications, expanding international collaborations, and involvement in professional academic societies, she is well-positioned to enhance her research impact and leadership in the academic community. Scopus record: 2 citations by 2 documents, 4 total documents, and an h-index of 1.

Profiles: Scopus | ORCID

Featured Publication

  • Xia, H., Xu, J., & Wen, D. (2025). The impact of large models’ success on data modeling. In Proceedings of the 2025 International Conference on Digital Economy and Information Systems (DEIS). ACM