Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

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Dr. Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

Dr. Chaima Aouiche is a dedicated academic and researcher in computer science with expertise in artificial intelligence, machine learning, cybersecurity, and bioinformatics. Born on October 24, 1990, in Tebessa, Algeria, she began her academic journey at Larbi Tebessi University and pursued her Ph.D. at Northwestern Polytechnical University (NPU), China. With international exposure, Dr. Aouiche has authored impactful publications on cancer gene prediction, data integration, and AI-based energy systems. She has collaborated across disciplines and countries, contributing to international conferences and peer-reviewed journals. Currently serving as a university teacher in Algeria, she is also a multilingual educator with teaching experience in China and Algeria. Dr. Aouiche combines technical knowledge with strong interpersonal skills and a passion for teaching, traveling, and community service, making her a well-rounded and globally competent scholar committed to innovation and education.

Profile

🎓 Education

Dr. Chaima Aouiche holds a strong academic foundation in computer science. She earned her Bachelor’s degree (2008–2011) and Master’s degree (2011–2013) in Computer Science from Larbi Tebessi University, Algeria, where she was recognized with the “Outstanding Student Award” in 2013. She expanded her horizons by studying the Chinese language for a year (2013–2014) at Northwestern Polytechnical University (NPU) in Xi’an, China. She then pursued a Ph.D. in Computer Science and Technology at NPU (2014–2021), focusing on stage-specific gene prediction, big data integration, and artificial intelligence. Throughout her academic journey, she acquired various global certifications, including Artificial Intelligence Foundations, Advanced Machine Learning, and Deep Learning, further enriching her qualifications. With multilingual skills in Arabic, French, English, and Chinese, she integrates global perspectives into her research and teaching. Her academic path reflects both depth and international breadth.

🧪 Experience

Dr. Chaima Aouiche has a diverse background in academia, industry, and cross-cultural teaching. She began her professional career in project management at MPE-MPI Investments, Tebessa (2011–2013), where she gained hands-on technical and administrative skills. In 2017, she taught English and Arabic in Xi’an, China, enhancing her intercultural communication and educational outreach. Currently, she works as a university teacher in Algeria, engaging in teaching, research supervision, and publication. Her training includes courses in project management, AI, and big data, complemented by technical expertise in programming (Python, Java, R), MATLAB, web technologies, and networking. Her ability to communicate in four languages (Arabic, French, English, Chinese) and her volunteering and mentoring activities reflect her commitment to holistic professional development. Dr. Aouiche’s career is defined by interdisciplinary collaboration, international exposure, and a passion for applied technological solutions, making her an asset in both academia and industry.

🏅 Awards and Honors

Dr. Aouiche’s academic and professional excellence has been recognized through multiple awards and certificates. She was awarded the Outstanding Student Award by Larbi Tebessi University in 2013. Her further accolades include numerous international certifications, such as the HSK 4 Chinese Proficiency Certificate, Artificial Intelligence and Big Data Training (Xi’an Jiaotong University), AI Foundations Masterclass (2023), and Advanced Machine Learning and Deep Learning Certificates (2024). She has also been recognized for her participation in global academic initiatives, such as the International Winter Camp (2017) and the Silk Road Engineering Science Program (2020). In addition to formal honors, her significant co-authorship on high-impact publications in BMC Bioinformatics, Frontiers in Genetics, and IEEE conferences speaks to her professional standing. These accolades collectively highlight her dedication to academic distinction, global engagement, and technological innovation.

🔬 Research Focus

Dr. Aouiche’s research intersects bioinformatics, artificial intelligence, machine learning, and cybersecurity. Her work has emphasized integrating multiple datasets to predict stage-specific cancer-related genes, mapping copy number variations, and modeling aberrant genomic events. She co-authored key studies published in BMC Bioinformatics, Frontiers in Genetics, and Quantitative Biology, which propose dynamic gene modules and data-driven cancer diagnostics. Recent work explores ensemble learning and AI approaches to detect cyberattacks using integrated datasets, showing a pivot toward cybersecurity and smart systems. Additionally, her research extends into renewable energy, specifically applying AI models to optimize photovoltaic systems and MPPT (Maximum Power Point Tracking) control. Her interdisciplinary approach bridges computational biology and engineering, reflecting her adaptability and innovative vision. Dr. Aouiche is particularly interested in applied AI that addresses real-world challenges in medicine, energy, and security, with a growing focus on industry 4.0 applications.

✅ Conclusion

Dr. Chaima Aouiche is an innovative computer scientist and academic whose international education, multidisciplinary research in AI and bioinformatics, commitment to teaching, and dynamic professional experiences make her a valuable contributor to global science and technology.

Publications

Yun Kang | Mathematical Biology | Best Researcher Award

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Dr. Yun Kang | Mathematical Biology | Best Researcher Award

Yun Kang is a distinguished Professor of Applied Mathematics at Arizona State University 🏫, specializing in mathematical biology, complex adaptive systems, and nonlinear dynamical systems 🔬📊; with over 70 publications in high-impact journals 📝, Kang’s work bridges theory and modeling to solve biological, ecological, and social questions 🌍; a leader in mathematical research, she also champions women in STEM through mentoring and advocacy 🤝💡; her cutting-edge research, funded by the NSF 💰, explores multiscale modeling in social insects 🐜 and trust dynamics in human-automation interaction 🤖; as a dedicated educator and core faculty member at the Simon A. Levin Mathematical, Computational & Modeling Sciences Center 🧠, she has shaped both academic programs and future researchers 🌱📈.

Profile

Education 🎓

Yun Kang earned her Ph.D. in Mathematics from Arizona State University in 2008 🎓, focusing on mathematical biology 🧪; she completed an M.S. in Pure Mathematics at the University of Arizona in 2004 📐, with special research in random graphs 🔗; her academic journey began with a B.S. in Applied Mathematics from Shanghai Jiaotong University, China 🇨🇳, in 2002, where she concentrated on financial and computational mathematics 💹💻; this academic foundation provided a solid platform for her research into nonlinear systems and biological applications 🌿📊; Kang’s education path reflects global excellence 🌍, interdisciplinary rigor 🧠, and a passion for bridging mathematics with real-world complexity 🌐✨.

Experience 👨‍🏫

Yun Kang’s academic career began as an Assistant Professor at ASU in 2008 🧑‍🏫, after completing her doctorate 🎓; she advanced to Associate Professor in 2014 and became a full Professor in 2019 🌟; from 2016 to 2019, she served as Acting Director/Co-Director of the Simon A. Levin Mathematical, Computational & Modeling Sciences Center 🧠, promoting interdisciplinary collaborations 💡; beyond teaching, Kang holds roles as Core Faculty and Affiliated Faculty at ASU’s School of Mathematical and Statistical Sciences 📚; her career spans leadership, research, mentorship, and advocacy for diversity in mathematical sciences 💪🌸; each role reflects her commitment to both academic excellence and community empowerment 🏅📢.

Awards & Recognitions 🏅

Yun Kang’s excellence is reflected in her NSF-funded research grants 💰, numerous high-impact publications 📝, and her leadership in mathematical biology 🔬; she’s a proud and active member of top organizations: Association for Women in Mathematics 👩‍🔬, American Mathematical Society 📘, Society for Industrial and Applied Mathematics 🧠, and Society for Mathematical Biology 🌿; since 2009, she’s mentored young female mathematicians via the AWM mentor network 🤝💡; her recognition stems from both groundbreaking research and her role as a diversity advocate in STEM 🌸🌍; her distinguished honors underscore her dual commitment to advancing math and empowering future scholars 🌟👩‍🏫.

Research Interests 🔬

Yun Kang’s research bridges nonlinear dynamical systems ⚙️, stochastic models 🎲, and mathematical biology 🧬; she explores complex adaptive systems — from population dynamics 🦌, food webs 🌾, eco-epidemiology 🦠, to social insect colonies 🐜; her NSF-funded work dissects multiscale division of labor in insect societies 🐝; she also models trust dynamics in human-automation interactions 🤖, blending theoretical rigor with real-world relevance 🌎; her contributions illuminate evolutionary processes 🔄, ecological interactions 🌱, and behavioral modeling 🧠; Kang’s approach merges deep mathematical theory with empirical validation 📊, offering new tools for biological, ecological, and social system analysis 🚀📘.

Publications 

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.

Mai Anh Bui | Plastic Surgeon in Developing countries | Best Researcher Award

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Prof Dr. Mai Anh Bui | Plastic Surgeon in Developing countries | Best Researcher Award

 

Profile

Education

Dr. Mai Anh Bui is a consultant Plastic Surgeon and Vice Chief of Scientific Research Department at Viet Duc University Hospital from Vietnam. She is also Assist. Professor at Hanoi Medical University and University of Medicine and Pharmacy, Vietnam National University. She completed a plastic surgery residency in 2006. Her specialty is to contribute to restoring the patients’ peripheral nerve injury and reconstruction of the patients with craniomaxillofacial surgery and head & neck reconstructions. In particular, she also specializes in facial paralysis with over 200 patients. Her Ph.D. is on the Using Masseteric nerve in Facial Reanimation. She has published over 60 articles in domestic and international journals.She refined her microsurgical skills by visiting several prestigious Institutions: Royal North Shore Hospital, Sydney University, Australia, Asan Hospital, Seoul, Korea, SickKids Hospital, Toronto, Canada, and craniofacial skills in Chang Gung Memorial Hospital, Taiwan.

Work experience

She has successfully completed [X] research projects and is currently working on [Y] ongoing projects. Her contributions to research are reflected in her citation index in reputed databases such as SCI and Scopus. She has been actively involved in [X] consultancy and industry-sponsored projects, demonstrating her expertise in applying research to real-world challenges. Additionally, she has authored [X] books with ISBN numbers and has contributed to intellectual property development with [X] patents published or under process. With [X] research articles published in indexed journals, she has made a significant impact in her field. She also holds editorial positions in [journals/conferences], further showcasing her leadership in scholarly publishing. Throughout her career, she has collaborated with esteemed national and international institutions, contributing to groundbreaking advancements in her research domain.

Publication

  • Outcome of using the spinal accessory nerve for functional muscle innervation in facial paralysis reconstruction: The first two cases in Vietnam and literature review

    Vietnam Journal of Endolaparoscopic Surgey
    2022-10-25 | Journal article | Author
    DOI: 10.51199/vjsel.2022.4.3
    Part ofISSN: 1859-4506
    CONTRIBUTORS: Mai Anh Bui; Trung Trực Vũ

  • Outcome of repairing posterior interosseous nerve (PIN) injury

    Vietnam Journal of Endolaparoscopic Surgey
    2022-08-15 | Journal article
    DOI: 10.51199/vjsel.2022.3.8
    Part ofISSN: 1859-4506
    CONTRIBUTORS: Mai Anh Bui; Tran Xuan Thach, Vu Trung Truc

  • Reconstruction of upper extremity defect by using Superficial circumflex iliac artery perforator (SCIP) free flap: 03 cases and literature review

    Vietnam Journal of Endolaparoscopic Surgey
    2022-03-15 | Journal article
    DOI: 10.51199/vjsel.2022.1.9
    Part of ISSN: 1859-4506

Longqing Cui | Operations research | Best Researcher Award

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Dr. Longqing Cui | Operations research | Best Researcher Award

 

Profile

Education

He pursued a Doctorate in Management Science and Engineering at Hefei University of Technology. Additionally, from November 2021 to November 2022, he was a jointly-supervised doctoral student in Operations and Business Analytics at The Ohio State University. Prior to his doctoral studies, he completed a Bachelor’s degree in Mathematics and Applied Mathematics at Hefei University of Technology from September 2013 to June 2017.

Work experience

He has been serving as a Lecturer at Alibaba Business School, Hangzhou Normal University. His research focuses on high-end equipment development and collaborative decision-making in manufacturing. He is the Principal Investigator (PI) for two ongoing projects. The first, funded by the Ministry of Education of the People’s Republic of China under the Youth Fund Project of Humanities and Social Sciences Research (Project No. 24YJC630030), explores collaborative decision-making for high-end equipment development resources in real-time production planning, running from January 2025 to December 2027 with a budget of 80,000 yuan. The second project, supported by the Zhejiang Provincial Natural Science Foundation Committee under the Youth Fund Project (Project No. LQN25G010007), investigates collaborative scheduling for high-end equipment development in distributed manufacturing enterprises within dynamic environments. This project runs from January 2025 to December 2026, with a funding of 60,000 yuan.

Publication

  • 1] Longqing Cui; Xinbao Liu; Shaojun Lu; Zhaoli Jia. A variable neighborhood
    search approach for the resource – constrained multi – project collaborative
    scheduling problem. Applied Soft Computing, 2021, 107:107480. (Journal Article)
    (Q1, First Author)
  • 2] Weijie Wang; Zhehang Xu; Shijia Hua; Longqing Cui; Jianlin Zhang; Fanyuan
    Meng. Threshold – initiated spatial public goods games. Chaos, Solitons & Fractals,
    2024, 184:115003. (Q1, Corresponding Author)
  • Zhehang Xu; Xu Liu; Hainan Wang; Longqing Cui; Xiao – Pu Han; Fanyuan Meng.
    Free – rider or contributor: A dilemma in spatial threshold public goods games.
    Chaos, Solitons & Fractals, 2024, 187:115455. (Q1, Corresponding Author)
  • Lei Chen; Yanpeng Zhu; Jiadong Zhu; Longqing Cui; Zhongyuan Ruan; Michael
    Small; Kim Christensen; Run – Ran Liu; Fanyuan Meng. A simple model of global
    cascades on random hypergraphs. Chaos, Solitons and Fractals, 2025, 193(116081).
    (Q1, Corresponding Author)
  • Che Xu; Yingming Zhu; Peng Zhu; Longqing Cui. Meta – learning – based sample
    discrimination framework for improving dynamic selection of classifiers under
    label noise. Knowledge – Based Systems, 2024, 295:111811. (Q1)

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. 🌟