Sathiyataj Thambiayya | Mathematical Physics | Best Researcher Award

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Assist. Prof. Dr. Sathiyataj Thambiayya | Mathematical Physics | Best Researcher Award

Assistant Professor, UCSI University, Malaysia

Dr. Sathiyaraj Thambiayya is an Assistant Professor in the Institute of Actuarial Science and Data Analytics at UCSI University, Kuala Lumpur, Malaysia. He holds a Ph.D. in Mathematics from The Gandhigram Rural Institute, India. With over six years of teaching and research experience, Dr. Sathiyaraj specializes in control systems, fractional calculus, stochastic processes, and artificial intelligence applications in dynamic systems. He has worked as a Post-Doctoral Research Fellow at Guizhou University, China, and has been selected for the prestigious National Post-Doctoral Fellowship by the Science and Engineering Research Board (SERB), Government of India. Dr. Sathiyaraj’s research contributions have been recognized globally, with a total research impact factor of 67.10 and a focus on applying advanced mathematics to real-world challenges such as healthcare and AI systems. He is currently leading several funded research projects and is actively involved in postgraduate supervision.

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Education

Dr. Sathiyaraj Thambiayya completed his Ph.D. in Mathematics from the Department of Mathematics at The Gandhigram Rural Institute, India (2015–2017). Before that, he earned a Master of Philosophy in Mathematics from St. Joseph’s College, Trichy, India (2011–2012) and a Master of Science in Mathematics from the same institution (2009–2011). He holds a Bachelor of Education in Mathematics from Tamil Nadu Teachers Education, Chennai, India (2008–2009), and a Bachelor of Science in Mathematics from AVVM Sri Pushpam College, Thanjavur, India (2005–2008). Additionally, he completed his Higher Secondary School at Govt. High School, Thanjavur, India (2003–2005). His academic journey highlights his consistent focus on mathematics and its application to real-world problems, particularly in control systems, stochastic processes, and fractional calculus.

Experience

Dr. Sathiyaraj Thambiayya has extensive academic experience in teaching and research. He currently serves as an Assistant Professor at the Institute of Actuarial Science and Data Analytics at UCSI University, Malaysia, where he has been employed since January 2024. Previously, he worked as a Lecturer in the same institute (2021–2023). His earlier academic experience includes a role as a Guest Faculty at The Gandhigram Rural Institute, India (2017–2018), and as an Assistant Professor in Mathematics at Oxford Engineering College, Trichy, India (2012–2013). Dr. Sathiyaraj has contributed significantly to research during his Post-Doctoral Fellowship at Guizhou University, China (2018–2021), and under the SERB Fellowship at IIT Kanpur, India (2021). His teaching and research have revolved around advanced mathematics, stochastic systems, AI, and control theory, with a particular emphasis on healthcare applications and machine learning.

Awards and Honors

Dr. Sathiyaraj Thambiayya has received several prestigious awards throughout his career. In December 2021, he was selected for the National Post-Doctoral Fellowship (NPDF) by the Science and Engineering Research Board (SERB), Government of India, which he carried out under the mentorship of Prof. Dhirendra Bahuguna at the Indian Institute of Technology Kanpur. This fellowship recognizes his excellence in mathematical research. In December 2013, Dr. Sathiyaraj was awarded the Senior Research Fellow by the Council of Scientific and Industrial Research (CSIR), New Delhi, India, which facilitated the completion of his Ph.D. degree. These honors reflect his exceptional academic and research contributions, particularly in the areas of stochastic processes, fractional calculus, and dynamic systems, positioning him as a leading researcher in applied mathematics and control theory.

Research Focus

Dr. Sathiyaraj Thambiayya’s research focuses on several advanced topics in applied mathematics, with particular emphasis on control systems, stochastic processes, fractional calculus, and machine learning applications for dynamic systems. His research interests include approximate controllability, optimal control, and the development of AI-based solutions for complex systems. His expertise lies in analyzing the qualitative behavior of dynamical systems, including fractional-order systems and stochastic differential equations. He has applied these methods to real-world problems, including the use of AI for the automated detection of diabetic retinopathy and the modeling of complex stochastic systems. His ongoing research explores the intersection of AI, control theory, and fractional calculus, particularly in dynamic and uncertain environments. Through these efforts, Dr. Sathiyaraj aims to develop innovative mathematical tools and techniques for tackling complex problems in engineering, healthcare, and other fields.

Publication Top Notes

  1. Controllability and optimal control for a class of time-delayed fractional stochastic integro-differential systems 📝🔧
  2. Ulam’s stability of Hilfer fractional stochastic differential systems 🧮🔍
  3. Controllability of stochastic nonlinear oscillating delay systems driven by the Rosenblatt distribution 🔄🌐
  4. ABC Fractional Derivative for the Alcohol Drinking Model using Two‐Scale Fractal Dimension 🍻📊
  5. Controllability of fractional higher order stochastic integrodifferential systems with fractional Brownian motion 🏗️🔢
  6. Null controllability results for stochastic delay systems with delayed perturbation of matrices 🕒📉
  7. Relative controllability of a stochastic system using fractional delayed sine and cosine matrices 🔢📏
  8. The controllability of fractional damped stochastic integrodifferential systems ⚙️📉
  9. Synchronization of butterfly fractional order chaotic system 🦋🌀
  10. Controllability of Hilfer fractional stochastic system with multiple delays and Poisson jumps 🔄🧮

 

 

Dr. Mohammed Elghandouri | Applied Mathematics |

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Dr. Mohammed Elghandouri | Applied Mathematics | Best Researcher Award

Postdoctoral position , Inria de Lyon, France.

Dr. Mohammed Elghandouri is a Moroccan-born researcher specializing in applied mathematics and computer science. He holds a Ph.D. from a joint doctoral program between Cadi Ayyad University (Morocco) and Sorbonne University (France), focusing on controllability and dynamic systems. Passionate about mathematical modeling, his work spans across various disciplines including epidemiology, optimal control, and integrodifferential equations. Currently, Dr. Elghandouri is a postdoctoral researcher at the Centre INRIA de Lyon, France, contributing to mathematical modeling of vector-borne diseases. With a deep commitment to research and education, he actively participates in conferences, training programs, and scientific communities globally.

Profile 

Education 🎓

Dr. Elghandouri completed his Ph.D. in applied mathematics and computer science through a joint doctoral program between Cadi Ayyad University in Morocco and Sorbonne University in France, where his thesis focused on controllability for nonlocal integrodifferential equations. Prior to his Ph.D., he obtained a Master’s degree in Mathematical Modeling and Dynamic Systems Analysis from Cadi Ayyad University. He also holds an International Master’s degree in Mathematics and Applications from Côte d’Azur University, France. His academic journey began with a Bachelor’s degree in Mathematical Sciences and Applications at Cadi Ayyad University. He has also attended numerous training courses and participated in workshops worldwide to refine his research and teaching skills.

Experience 💼

Dr. Elghandouri has extensive research experience, particularly in the areas of mathematical modeling, dynamic systems, and optimal control. He is currently a postdoctoral researcher at the Centre INRIA de Lyon, where he works on mathematical models for vector-borne diseases. Throughout his career, Dr. Elghandouri has collaborated with prestigious institutions, including Sorbonne University and Cadi Ayyad University, and has contributed to international conferences, workshops, and seminars in the fields of applied mathematics, epidemiology, and control theory. His research stay in France allowed him to enhance his expertise in complex systems modeling. Additionally, he has participated in various scientific and training activities, building strong interdisciplinary research connections.

Research Focus 🔬

Dr. Elghandouri’s research is focused on the controllability of dynamic systems, with special attention to integrodifferential equations and their applications in mathematical and computer modeling. His work encompasses topics like optimal control, epidemiological modeling, and the modeling of complex systems, particularly for public health applications such as vector-borne diseases. He is interested in the theoretical aspects of well-posedness, asymptotic behavior, and approximate controllability in infinite-dimensional systems, including those with nonlocal conditions. His work is interdisciplinary, bridging applied mathematics with epidemiology, environmental sciences, and computational modeling. Dr. Elghandouri is dedicated to exploring new mathematical models that can solve real-world problems in public health and beyond.

Publications 📚

  • Approximation of Mild Solutions of Delay Integro-Differential Equations on Banach Spaces
  • Approximate Controllability for Some Integrodifferential Evolution Equations with Nonlocal Conditions
  • Well-Posedness and Approximate Controllability for Some Integrodifferential Evolution Systems with Multi-Valued Nonlocal Conditions
  • Exploring Well-Posedness and Asymptotic Behavior in an Advection-Diffusion-Reaction (ADR) Model
  • Optimal Control of General Impulsive VS-EIAR Epidemic Models with Application to COVID-19
  • Approximate Controllability for Nonautonomous Integrodifferential Equations with State-Dependent Delay
  • On The Approximate Controllability for Fractional Neutral Inclusion Systems With Nonlocal Conditions
  • Regional Control Strategies for a Spatiotemporal SQEIAR Epidemic Model: Application to COVID-19
  • Approximate Controllability for Some Nonlocal Integrodifferential Equations in Banach Spaces
  • Dynamical Analysis and Numerical Simulation of a Reaction-Diffusion Model for Microbial Decomposition of Organic Matter in 3D Soil Structure

Yang Xia | Mathematics Award | Best Researcher Award

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Dr Yang Xia | Mathematics Award | Best Researcher Award

Dr Yang Xia, Xinjiang University, China

Yang Xia is a doctoral student at Xinjiang University, China, specializing in complex network information dissemination. His research focuses on understanding and controlling rumor diffusion using advanced theories like complex network theory, differential equations, and modern control theory. Yang has authored seven high-impact papers, with one highly cited, and has led projects at both provincial and university levels. His work integrates theoretical models with practical applications to address the challenges of rumor propagation in the digital age, demonstrating a commitment to advancing knowledge in network dynamics and collective behavior.

Publication Profile

Strengths for the Award

  1. Significant Research Contributions: Yang Xia has made notable contributions in the field of complex network information dissemination and rumor diffusion models. The work covers advanced topics such as stochastic models, higher-order interactions, and multilingual environments, demonstrating a deep engagement with cutting-edge research.
  2. Impressive Publication Record: With seven high-level papers published in reputable journals like Chaos, Solitons & Fractals and Communications in Nonlinear Science and Numerical Simulation, Yang Xia has shown a strong publication track record. The presence of a highly cited paper indicates a significant impact within the academic community.
  3. Leadership in Research Projects: Yang Xia has led several research projects, including those funded by the Excellent Doctoral Innovation Program of Xinjiang University and the Excellent Master Innovation Program of Xinjiang Uyghur Autonomous Region. This leadership role underscores a capacity for managing and driving research initiatives effectively.
  4. Interdisciplinary Approach: The integration of complex network theory, differential equation theory, and modern control theory in Yang Xia’s research indicates a multidisciplinary approach that could lead to innovative solutions for controlling rumor spreading and understanding social behavior dynamics.
  5. Strong Academic Network: Collaborative work with notable researchers like Haijun Jiang and Zhiyong Yu highlights Yang Xia’s ability to work within a strong academic network, which often leads to high-quality and impactful research outputs.

Areas for Improvement

  1. Expanded Citation Index and Visibility: While Yang Xia has a robust publication record, increasing citation numbers and enhancing the visibility of their work could further solidify their position in the field. Engaging in more interdisciplinary collaborations or high-impact projects could also boost citation rates.
  2. Broader Impact Beyond Academia: There is limited information on how Yang Xia’s research has been applied or recognized outside of academia. Developing industry collaborations or practical applications of their research could demonstrate the real-world impact and relevance of their work.
  3. Patents and Books: Currently, there are no patents or books listed, which are often considered significant indicators of innovation and broader dissemination of research findings. Pursuing patents or publishing a book could provide additional evidence of pioneering contributions.
  4. Professional Memberships and Editorial Roles: Including more details about memberships in professional organizations or editorial roles could provide a fuller picture of Yang Xia’s engagement with the research community and their contributions to the field beyond their publications.

Education 

Yang Xia is currently pursuing a doctoral degree at Xinjiang University, China, where he focuses on complex network information dissemination. His academic journey includes a comprehensive study of rumor diffusion mechanisms through the application of complex network theory, differential equations, and modern control theory. Yang’s educational background is marked by a robust engagement with theoretical and practical aspects of network dynamics, underpinned by his substantial contributions to research projects funded by the Excellent Doctoral Innovation Program and the Excellent Master Innovation Program. His education has provided him with a strong foundation in advanced mathematical and computational techniques relevant to his field.

Experience

Yang Xia has substantial experience in the field of complex network information dissemination. As a doctoral student, he has led and completed research projects funded by prestigious programs like the Excellent Doctoral Innovation Program of Xinjiang University and the Excellent Master Innovation Program of Xinjiang Uyghur Autonomous Region. His experience includes publishing seven high-level papers in prominent journals, demonstrating a deep understanding of rumor diffusion models and network dynamics. Yang’s role in these projects involved extensive theoretical modeling and practical application, reflecting his capability to manage and contribute to significant research endeavors. His collaborative work with esteemed researchers further highlights his experience and expertise in the field.

Awards and Honors 

Yang Xia’s achievements include leading research projects funded by the Excellent Doctoral Innovation Program of Xinjiang University and the Excellent Master Innovation Program of Xinjiang Uyghur Autonomous Region. Although specific awards are not listed, his research contributions have been recognized through high-level publications and significant project completions. Notably, one of his papers has achieved high citation rates, underscoring the impact of his work in the field of rumor diffusion and complex networks. Yang’s recognition comes through the academic and research communities, reflecting his dedication and contributions to advancing knowledge in network information dissemination.

Research Focus 

Yang Xia’s research centers on complex network information dissemination, particularly the dynamics of rumor diffusion. His work leverages complex network theory, differential equations, and modern control theory to model and control rumor propagation. Yang explores the impact of these dynamics on collective social behavior in the digital age, addressing challenges associated with multilingual environments and network structures. His research includes developing and analyzing theoretical models to understand and mitigate the effects of rumor spreading, aiming to provide practical solutions for network security and information management. The integration of these advanced theories highlights Yang’s focus on advancing the understanding of information propagation in complex networks.

Publication Top Notes

Dynamical analysis of a stochastic Hyper-INPR competitive information propagation model 📈 – Chaos, Solitons & Fractals (2024)

The dynamic analysis of the rumor spreading and behavior diffusion model with higher-order interactions 🔄 – Communications in Nonlinear Science and Numerical Simulation (2024)

Dynamic analysis of the IEASWR information propagation model with Holling-type II functional response 🌐 – International Journal of Wavelets, Multiresolution and Information Processing (2024)

Modeling and controlling delayed rumor propagation with general incidence in heterogeneous networks 🔍 – International Journal of Modern Physics C (2024)

Dynamical analysis of Hyper-SIR rumor spreading model 🧩 – Applied Mathematics and Computation (2023)

Conclusion

Yang Xia appears to be a strong candidate for the Best Researcher Award based on their research contributions, publication record, and leadership in key projects. The research is both innovative and relevant to current challenges in information dissemination and rumor control. To further strengthen their application, Yang Xia could focus on increasing the citation impact of their work, expanding their contributions beyond academia, and engaging in activities such as patents or books. Addressing these areas could enhance their profile as a leading researcher and further support their candidacy for the award.