Yan Liu | Mathematics | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Yan Liu
North Minzu University, China

                           Yan Liu
Affiliation North Minzu University
Country China
Scopus ID 57206823708
Documents 12
Citations 94
h-index 7
Subject Area Mathematics
Event Global Innovation Technologist Awards

Yan Liu is a researcher affiliated with North Minzu University, China, whose documented scholarly profile includes contributions to mathematics and control-related research. The available bibliometric information records 12 documents, 94 citations and an h-index of 7. These indicators provide a quantitative overview of publication activity and citation visibility, while the researcher’s reported 2025 publication on iterative learning control offers a specific example of work connecting algebraic methods with discrete-time system analysis. [1]

Abstract

This article presents a research-profile overview of Yan Liu in the context of the Best Researcher Award associated with the Global Innovation Technologist Awards. The supplied record identifies a mathematics research profile and bibliometric indicators comprising 12 documents, 94 citations and an h-index of 7. A highlighted publication, “An Algebraic Approach to Robust Iterative Learning Control for Linear Discrete-Time Singular System With Initial State Shifting,” appeared in 2025 in IEEE Transactions on Systems, Man, and Cybernetics: Systems. The article summarizes its stated research focus and outlines considerations relevant to scholarly recognition without treating publication metrics alone as proof of research quality. [1]

Keywords

Yan Liu; mathematics; iterative learning control; discrete-time systems; singular systems; robust control; algebraic methods; bibliometrics; research impact; Best Researcher Award.

Introduction

Research recognition commonly considers the relevance, originality, rigor and influence of scholarly work. In mathematics and control systems, research may address theoretical methods as well as the analysis of systems with practical engineering implications. Liu’s reported publication on robust iterative learning control situates the research profile within this interdisciplinary area. The award context provides an opportunity to present the available academic record while distinguishing verified bibliographic information from broader assessments requiring independent review. [1]

Research Profile

The supplied profile associates Yan Liu with North Minzu University in China and identifies mathematics as the subject area. The listed Scopus author identifier is 57206823708. The profile reports 12 documents and 94 citations, with an h-index of 7. These values should be interpreted in relation to database coverage, publication dates, authorship attribution and the citation practices of the relevant discipline. [2]

Research Contributions

The highlighted study addresses robust iterative learning control for linear discrete-time singular systems under initial-state shifting. Its title indicates an algebraic approach to a control problem involving repeated system operation and changes in initial conditions. Iterative learning control generally uses information from previous executions to improve performance in subsequent executions. Singular systems, meanwhile, require methods that account for their particular mathematical structure. The paper’s specific theoretical results and experimental validation should be assessed from the published article itself. [1]

Publications

The supplied bibliographic record identifies the following publication as a relevant example of Liu’s research activity:

  • An Algebraic Approach to Robust Iterative Learning Control for Linear Discrete-Time Singular System With Initial State Shifting. Authors listed in the supplied record include Ruan Xiao’e, Hussain Ijaz, Liu Chen, Liu Yan and Li Bingqiang. Published in IEEE Transactions on Systems, Man, and Cybernetics: Systems in 2025. The record reports five citations for this publication. [1]

Full-text access and DOI details were not included in the supplied bibliographic information. The journal record should therefore be consulted to verify the complete author metadata and persistent publication identifier.

Research Impact

The reported 94 citations indicate that the indexed documents have received scholarly references, while the h-index of 7 summarizes a combination of publication productivity and citation influence. Neither measure independently establishes methodological quality, originality or broader societal impact. A balanced evaluation would examine the contribution of individual papers, citation context, collaboration patterns and the significance of results within mathematics and control engineering. [2]

Award Suitability

The Best Researcher Award profile highlights a documented publication record, measurable citation activity and research relevant to mathematical and control-system methods. A fair assessment by the Global Innovation Technologist Awards would also consider originality, contribution to the field, publication quality, research integrity and independent expert evaluation. The available information supports a structured profile, but does not establish an award decision or independently verify eligibility.

Conclusion

Yan Liu’s supplied academic profile records research activity in mathematics and a 2025 publication addressing robust iterative learning control in linear discrete-time singular systems. The available bibliometric figures offer a concise view of scholarly visibility. Further assessment of the researcher’s overall contribution requires examination of the complete publication record and independent evaluation of the work’s originality, rigor and influence.

References

  1. Ruan, X. E., Hussain, I., Liu, C., Liu, Y., & Li, B. (2025). An Algebraic Approach to Robust Iterative Learning Control for Linear Discrete-Time Singular System With Initial State Shifting.
    https://www.scopus.com/authid/detail.uri?authorId=57206823708
  2. Elsevier. (n.d.). Scopus author details: Yan Liu, Author ID 57206823708. Scopus. Bibliometric figures in this article reflect the supplied profile data and may change as the database is updated.
    https://www.scopus.com/authid/detail.uri?authorId=57206823708
  3. Global Innovation Technologist Awards. (n.d.). Official website. Information about the awards and their program should be verified through the official website.
    innovationtechnologist.com

Raghavendran Prabakaran | Mathematics | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Raghavendran Prabakaran
Easwari Engineering College, India

Raghavendran Prabakaran
Affiliation Easwari Engineering College
Country India
Scopus ID 58670546100
Documents 56
Citations 325
h-index 11
Subject Area Mathematics
Event Global Innovation Technologist Awards
ORCID 0009-0001-7333-6555

Raghavendran Prabakaran is a mathematics researcher affiliated with Easwari Engineering College, India. The documented research profile comprises 56 Scopus-indexed documents, 325 citations and an h-index of 11. His recent publication activity connects mathematical analysis with fractional calculus, integral equations, machine learning, physics-informed neural networks and computational modeling. These themes illustrate an interdisciplinary research direction in which mathematical methods are applied to complex analytical and predictive problems.[1]

Abstract

The research profile represented by the available publication record centers on contemporary mathematical techniques for modeling, approximation and prediction. Recent work addresses random fractional functional Volterra–Fredholm integro-differential equations, physics-informed learning, mathematical transformations, complex systems and fractional drug-release models. The publications indicate an application-oriented research trajectory combining established mathematical frameworks with computational and machine-learning approaches.[2]

Keywords

Mathematics; fractional calculus; integro-differential equations; machine learning; physics-informed neural networks; computational modeling; mathematical transformations; predictive analysis.

Introduction

Mathematical research increasingly incorporates computational intelligence to address nonlinear, fractional and otherwise complex systems. In this context, hybrid methods can combine analytical formulations with data-driven approximation and prediction. The listed publications associated with Prabakaran’s research demonstrate this intersection through applications involving artificial neural networks, transformers, physics-informed methods and fractional differential models.[3]

Research Profile

The supplied bibliometric profile records 56 documents, 325 citations and an h-index of 11 in Scopus. These indicators provide quantitative measures of indexed publication output and citation activity, while the publication record provides additional context regarding subject breadth and methodological development.[1]

Research Contributions

  • Development and analysis of fractional and integro-differential mathematical models.
  • Application of machine-learning and neural-network methods to mathematical prediction and approximation.
  • Integration of physics-informed computational approaches with mathematical modeling.
  • Application of mathematical models to interdisciplinary problems, including nanomaterials and drug-release systems.

Publications

Recent publications include studies on nanomaterial selection and PINN-based prediction, random fractional functional Volterra–Fredholm integro-differential equations with ANN approximation, physics-informed transformer frameworks for EEG forecasting, Upadhyaya transforms with machine learning, and fractional integro-differential equations for paracetamol drug-release modeling.[4][5]

Research Impact

The reported citation count and h-index provide measurable evidence of scholarly visibility within the indexed record. The recent publications further show a research program extending mathematical techniques toward computational prediction and interdisciplinary applications. Such evidence should be interpreted alongside publication quality, authorship contribution, journal characteristics and independent citation context when evaluating research impact.

Award Suitability

For the Innovative Research Award category, the documented profile provides evidence relevant to consideration, particularly through its combination of mathematical research, computational methods and interdisciplinary applications. The available bibliometric indicators and recent publications can form part of an evidence-based recognition assessment within the Global Innovation Technologist Awards framework.[1]

Conclusion

Raghavendran Prabakaran’s documented research profile combines mathematical analysis with emerging computational approaches. The available Scopus indicators and recent publications demonstrate sustained scholarly activity across fractional mathematics, integro-differential equations, machine learning and interdisciplinary modeling. These records provide a structured basis for academic recognition and further evaluation of research contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Raghavendran Prabakaran, Author ID 58670546100. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58670546100
  2. MDPI. (2026). Analysis of Random Fractional Functional Volterra–Fredholm Integro-Differential Equations with Infinite Delay and ANN-Based Approximation. Fractal and Fractional.
    DOI: 10.3390/fractalfract10090646
  3. International Journal of Neuroscience and Neuroinformatics. (2026). A Physics-Informed Transformer Framework With a Four-Compartment NRSF Brain-State Model for EEG Forecasting.
    DOI: 10.4018/IJNN.419364
  4. Next Materials. (2026). Application of nanomaterial selection and PINN-based prediction using neutrosophic over soft complex locally closed sets and locally continuous functions.
    DOI: 10.1016/j.nxmate.2026.103274
  5. Transactions on Computational Modeling and Intelligent Systems. (2026). Application of Upadhyaya transforms with machine learning for predictive and analytical solutions in complex systems.
    DOI: 10.65112/tcmis.10023
  6. Oriental Journal Of Chemistry. (2026). Application of Fractional Integro-Differential Equations in Paracetamol Drug Release Modeling.
    DOI: 10.13005/ojc/420208

Latha Maheswari M | Mathematics | Best Researcher Award

Published on by Innovation Technologist

Dr. Latha Maheswari M | Mathematics | Best Researcher Award

Associate Professor & Dean at PSG College of Arts & Science, India

Dr. M. Latha Maheswari is an Associate Professor & Dean at the School of Computational Mathematics, PSG College of Arts & Science, Coimbatore. She specializes in fractional differential equations, impulsive differential equations, delay differential equations, and stochastic differential equations. With over two decades of academic experience, she has guided Ph.D. and M.Phil. scholars, undertaken funded research projects, and contributed significantly to applied mathematics research.

Publication Profile 

Scopus

Orcid

Educational Background 🎓

  • Ph.D. (2014) – Bharathiar University, Coimbatore
  • M.Sc. (Yoga) (2020) – Bharathidasan University, Trichy
  • M.Phil. (1996) – Madurai Kamaraj University, Madurai
  • M.Sc. (1995) – Madurai Kamaraj University, Madurai
  • B.Sc. (1993) – Madurai Kamaraj University, Madurai
  • PGDCA (1997) – Madurai Kamaraj University, Madurai

Professional Experience 💼

  • Dean, School of Computational Mathematics (SF), PSG College of Arts & Science (Jan 2024 – Present)
  • Associate Professor & HoD, PSG College of Arts & Science (Dec 2016 – Dec 2023)
  • Assistant Professor, PSG College of Arts & Science (June 2005 – Nov 2016)
  • Lecturer, Sarojini Naidu Govt. Girls PG College, Bhopal (Jan 2002 – June 2004)
  • Teacher, Army Public School (Oct 1999 – Nov 2000)
  • Lecturer, Jayaraj Annapakiyam College for Women, Periyakulam (Jan 1998 – Apr 1998)

Research Interests 🔬

  • Fractional Differential Equations
  • Impulsive Differential Equations
  • Delay Differential Equations
  • Stochastic Differential Equations

She has guided 4 Ph.D. scholars (pursuing), 1 Ph.D. awarded, and 3 M.Phil. scholars graduated.

Awards and Honors🏆✨

  • University IV Rank in PG at Madurai Kamaraj University
  • Academic Excellence Award, PSG College of Arts & Science
  • PSG Best Teacher Award (2018), PSG College of Technology
  • Research Contribution Award (2022 & 2023), PSG College of Arts & Science

Memberships:

  • Indian Society of Industrial & Applied Mathematics
  • MathTech Thinking Foundation

Conclusion🌟

Dr. M. Latha Maheswari has made substantial contributions to applied mathematics, particularly in differential equations. Her leadership at PSG College of Arts & Science has been instrumental in research and academic development. Recognized with multiple awards, she remains dedicated to advancing knowledge in computational mathematics.

Publications 📚

1️⃣ A. Anguraj, M. Latha Maheswari – Existence of solution of Fractional Quasilinear Impulsive differential equations
📖 Advanced in Theoretical and Applied Mathematics, 2011 🏷️ ISSN: 0973-4554

2️⃣ A. Anguraj, M. Latha Maheswari – Existence of solutions for fractional impulsive neutral functional infinite delay integro differential equations with nonlocal conditions
📖 The Journal of Nonlinear Science and its Applications, 2012 🏷️ ISSN: 2008-1901

3️⃣ A. Anguraj, M. Latha Maheswari – Existence results for fractional differential equations with infinite delay and interval impulsive conditions
📖 Malaya Journal of Matematik, 2014 🏷️ ISSN: 2321-5666

4️⃣ A. Anguraj, M. Latha Maheswari – The Existence and Uniqueness of solutions for nonlocal fractional differential equations with interval impulses
📖 National Journal of Technology, 2015 🏷️ ISSN: 0973-1334

5️⃣ A. Anguraj, M. Latha Maheswari, Y.K. Chang – Solutions of a fractional functional integro differential equations with interval impulses and infinite delay
📖 Nonlinear Studies, 2015 🏷️ ISSN: 1359-8678

6️⃣ T. Tamil Selvan, M. Latha Maheswari – Existence of solutions of nonlinear fractional impulsive delay integro differential equation of Sobolev type
📖 International Journal of Scientific and Research Publications, 2017 🏷️ ISSN: 2250-3153

7️⃣ M. Latha Maheswari, K. Pandiyan – Uniqueness of solution for boundary value problems for fractional integro-differential equations
📖 European Journal of Molecular & Clinical Medicine, 2020 🏷️ ISSN: 2515-8260

8️⃣ M. Latha Maheswari, R. Nandhini – Existence Results for Nonlocal Impulsive Fractional Neutral Functional Integro-Differential Equations with Bounded Delay
📖 Mathematics and Computing, Springer Proceedings in Mathematics and Statistics, March 2023

9️⃣ M. Latha Maheswari, K. S. Keerthana Shri – On a class of non-local boundary value problem for a -Hilfer non-linear fractional integro-differential equation
📖 Acta Mathematica Universitatis Comenianae, June 2023

🔟 M. Latha Maheswari, K. S. Keerthana Shri – Stability analysis for the Ψ-Hilfer non-linear Boundary Value Problem
📖 Nonlinear Studies, Volume 30, Issue 3, July 2023