Pritpal Singh | Ambiguous set theory | Best Researcher Award

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Dr. Pritpal Singh | Ambiguous set theory | Best Researcher Award

Pritpal Singh is an Assistant Professor at the Department of Data Science and Analytics, Central University of Rajasthan, India. He earned his Ph.D. in Computer Science and Engineering from Tezpur (Central) University in 2015 and has held various academic and research positions in India, Taiwan, and Poland. His expertise includes soft computing, optimization algorithms, time series forecasting, image analysis, and machine learning. He has published extensively in high-impact journals like IEEE Transactions, Elsevier, and Springer. His research focuses on advanced computational techniques, including quantum-based optimization and fMRI data analysis. Dr. Singh has received prestigious research fellowships, including a Postdoctoral Fellowship from Taiwan’s Ministry of Science and Technology and an International Visiting Research Fellowship from Poland’s Foundation for Polish Science. His work significantly contributes to artificial intelligence, data science, and computational modeling, making him a key figure in these fields. 🚀📊📚

Profile

Education 🎓

Dr. Pritpal Singh obtained his Ph.D. in Computer Science and Engineering from Tezpur (Central) University, Assam, India, in 2015, specializing in soft computing applications for time series forecasting. He completed his Master in Computer Applications (MCA) from Dibrugarh University, Assam, in 2008, following a B.Sc. in Physics, Chemistry, and Mathematics from the same university in 2005. His academic journey began with Higher Secondary (2002) from the Assam Higher Secondary Education Council and HSLC (1999) from the Secondary Education Board of Assam. His doctoral dissertation focused on improving fuzzy time series forecasting models through hybridization with neural networks and optimization techniques like particle swarm optimization. His strong foundation in computational sciences, mathematics, and engineering has shaped his research in AI-driven predictive modeling, optimization, and data analytics. 🎓📚🔬

Experience 👨‍🏫

Dr. Singh has extensive academic and research experience. He is currently an Assistant Professor at the Central University of Rajasthan (since June 2022). Previously, he was an Assistant Professor at CHARUSAT University, Gujarat (2015-2019), and a Lecturer at Thapar University, Punjab (2013-2015). His research experience includes serving as an Adjunct Professor (Research) at Jagiellonian University, Poland (2020-2022) and a Postdoctoral Research Fellow at National Taipei University of Technology, Taiwan (2019-2020). Throughout his career, he has mentored students, led research projects, and contributed significantly to data science, artificial intelligence, and computational modeling. His global exposure has enriched his expertise in optimization, machine learning, and interdisciplinary AI applications. 🌍📊

Research Interests 🔬

Dr. Singh’s research revolves around ambiguous set theory, optimization algorithms, time series forecasting, image analysis, and machine learning. He specializes in hybrid computational techniques, particularly quantum-based optimization and soft computing applications. His work extends to fMRI data analysis, mathematical modeling, and simulation. His research has been published in leading journals such as IEEE Transactions on Systems, Elsevier’s Information Sciences, and Artificial Intelligence in Medicine. His focus on interdisciplinary AI applications, particularly in healthcare and data science, has positioned him as a key contributor to advancing machine learning methodologies. 🧠📊🤖Awards & Recognitions 🏅

Dr. Singh has received multiple prestigious fellowships and recognitions. In 2019, he was awarded a Postdoctoral Research Fellowship by the Ministry of Science and Technology, Taiwan. In 2020, he received the International Visiting Research Fellowship from the Foundation for Polish Science, Poland. His contributions to artificial intelligence, optimization, and data science have been recognized globally through research grants, invited talks, and publications in top-tier journals. His work in soft computing and AI-driven predictive modeling continues to impact both academic and industrial research. 🏅🎖️📜

Publications 📚

  • Scopus 1-2023: P. Singh, An investigation of ambiguous sets and their application to
    decision-making from partial order to lattice ambiguous sets. Decision Analytics
    Journal (Elsevier), 08, 100286, 2023.
  • Scopus 2-2023: P. Singh, A general model of ambiguous sets to a single-valued ambiguous numberswith aggregation operators. Decision Analytics Journal (Elsevier), 08,
    100260, 2023.
  • Scopus 3-2023: P. Singh, Ambiguous set theory: A new approach to deal with unconsciousness and ambiguousness of human perception. Journal of Neutrosophic and
    Fuzzy Systems (American Scientific Publishing Group), 05(01), 52–58, 2023.
  • Scopus 4-2022: P. Singh, Marcin W ˛atorek, Anna Ceglarek, Magdalena F ˛afrowicz, and
    Paweł O´swi˛ecimka, Analysis of fMRI Time Series: Neutrosophic-Entropy Based
    Clustering Algorithm. Journal of Advances in Information Technology, 13(3), 224–
    229, 2022.

Rakesh Meena | Applied Mathematics | Best Researcher Award

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Mr. Rakesh Meena | Applied Mathematics | Best Researcher Award

Research Scholar at Sardar Vallabhbhai National Institute of Technology, India

Mr. Rakesh Meena is a promising researcher and Ph.D. candidate at the Department of Mathematics, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India. His academic journey is characterized by a focus on advanced mathematical modeling, fractional calculus, and differential equations. With a blend of theoretical and computational expertise, Mr. Meena is dedicated to contributing to innovative solutions in applied mathematics, particularly in areas like epidemic modeling and dynamic systems. He is driven by the desire to combine research with teaching to foster academic growth and knowledge sharing. Throughout his career, he has earned recognition through prestigious scholarships and fellowships, such as the Junior Research Fellowship (JRF) and Senior Research Fellowship (SRF) from CSIR-UGC. His research contributions, including numerous journal publications and conference presentations, reflect his deep commitment to advancing mathematical sciences. Mr. Meena’s aspirations align with the goal of bringing meaningful change to both the academic community and society through his research and teaching.

Profile

Scopus

Google Scholar

Orcid

 

Education 🎓

Mr. Rakesh Meena’s educational background forms a solid foundation for his research career. He began his academic journey at Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, where he completed his Five-Year Integrated M.Sc. in Mathematics with first division in 2020. Following this, he embarked on his Ph.D. in Mathematics, with a focus on linear and nonlinear fractional differential equations. Under the guidance of Dr. Sushil Kumar, he has made notable progress in mathematical modeling, particularly through the semi-analytical approach. His cumulative performance during his Ph.D. coursework reflects dedication, maintaining a CGPA of 7.25. Throughout his education, Mr. Meena has demonstrated a continuous pursuit of knowledge, aiming to contribute to the vast field of mathematical sciences. His educational path has not only provided him with strong analytical skills but also a deep understanding of both theoretical and computational methods. This educational experience, combined with his passion for research, serves as a solid launchpad for his future contributions to the scientific community.

Work Experience 💼

Mr. Rakesh Meena’s professional experience includes extensive academic research at the Department of Mathematics, SVNIT, Surat. Currently pursuing his Ph.D., Mr. Meena has contributed to a range of mathematical research, particularly in fractional calculus, epidemic modeling, and nonlinear differential equations. His expertise in using semi-analytical methods, such as the Residual Power Series (RPS) method and Homotopy Analysis Method, allows him to solve complex mathematical equations, which are pivotal in the fields of mathematical modeling and computational mathematics. As a junior and senior research fellow (JRF/SRF), he has been involved in multiple research projects that align with his goal of applying mathematical theory to real-world problems. Additionally, Mr. Meena has shared his research findings through several journal articles and conference papers, expanding his influence in academic circles. Beyond research, his role in mentoring and teaching aligns with his long-term goal of working in an institution where teaching and research go hand-in-hand. His participation in both national and international conferences further strengthens his professional experience, offering him a platform to engage with global research communities.

Awards and Honors

Mr. Rakesh Meena has been the recipient of several prestigious awards and fellowships, recognizing his academic excellence and research potential. In 2020, he was awarded the Junior Research Fellowship (JRF) by CSIR-UGC, which was followed by the Senior Research Fellowship (SRF) in 2022. These fellowships are granted to outstanding researchers in the field of mathematical sciences and are a testament to his proficiency and dedication to research. Additionally, Mr. Meena qualified for GATE (Graduate Aptitude Test in Engineering) in both 2022 and 2023, further cementing his academic credentials. His work, particularly in mathematical modeling and fractional calculus, has earned him recognition in the academic community. His achievements also include being a recipient of certification from CSIR-HRDG, highlighting his commitment to continuous learning and development. These awards and honors reflect Mr. Meena’s dedication to pushing the boundaries of mathematical research, and they serve as a foundation for his continued contributions to the scientific community.

Research Interests

Mr. Rakesh Meena’s primary research interests lie in mathematical modeling, fractional differential equations, and dynamic systems. His doctoral research specifically focuses on linear and nonlinear fractional differential equations, employing semi-analytical methods for their solutions. He aims to explore these equations’ applications in real-world phenomena, such as epidemic modeling, fluid dynamics, and wave propagation. His work in fractional calculus offers new insights into the mathematical descriptions of complex systems, which are often difficult to model using traditional integer-order differential equations. Through his research, Mr. Meena is particularly interested in understanding the behavior of systems with memory and hereditary properties, common in biological and physical systems. In addition to his work on differential equations, he is exploring the application of the Residual Power Series (RPS) method and other numerical techniques, such as the Euler and Runge-Kutta methods, to obtain approximate solutions to these complex models. His interdisciplinary approach to mathematical modeling promises to contribute to both the advancement of mathematical theory and its practical applications in fields like epidemiology, physics, and engineering.

Research Skills

Mr. Rakesh Meena’s research skills are diverse, encompassing both theoretical and computational techniques. His proficiency in mathematical modeling, especially in the context of fractional differential equations, stands out as a major strength. He is well-versed in various semi-analytical methods, notably the Residual Power Series (RPS) and Homotopy Analysis Method, to solve complex differential equations. These techniques are especially useful in capturing the dynamics of systems governed by fractional order equations, which are prevalent in many natural and social systems. Mr. Meena also possesses strong numerical skills, applying methods like the Euler method, Runge-Kutta method, and finite difference methods for computational analysis. He is skilled in using computational tools, including MATLAB, Maple, Mathematica, and LaTeX, to model, analyze, and visualize mathematical problems. His ability to integrate both analytical and numerical methods enables him to approach research challenges from a comprehensive perspective. Moreover, his academic rigor and attention to detail contribute to his systematic approach to research, making his work both reliable and impactful.

📚 Publications

Conclusion 

Mr. Rakesh Meena is a strong contender for the Best Researcher Award due to his excellent academic record, innovative research in fractional differential equations, and contribution to mathematical modeling. His expertise in semi-analytical and numerical methods provides significant value to his field. With a broader impact focus and increased public engagement, he has the potential to make transformative contributions to both academia and society. This will further cement his position as a leader in his field. 🌟