Fan Yang | Computational Mathematics | Best Researcher Award

Posted on 13/05/202513/05/2025 by Math Scientist

Prof. Fan Yang | Computational Mathematics | Best Researcher Award

Professor at Lanzhou University of Technology, China

Professor Fan Yang 🎓, born in April 1976, is a distinguished mathematician at the School of Science, Lanzhou University of Technology, China. With a solid academic foundation—earning his B.Sc., M.Sc., and Ph.D. from Lanzhou University—he has emerged as a notable expert in inverse problems 🔍 and fractional diffusion equations 🌐. His research contributions span over 14 impactful publications in internationally recognized journals, showcasing innovative regularization techniques like Tikhonov, mollification, and quasi-boundary methods 🧮. His work significantly enhances computational stability in solving complex physical models, particularly heat and Poisson equations 🔥➕. Professor Yang collaborates closely with scholars like Chu-Li Fu and Xiao-Xiao Li, reflecting his team-driven approach and scientific synergy 🤝. While his global visibility could be further amplified, his technical depth, precision, and dedication place him among the front-runners in applied mathematics. A trailblazer in mathematical physics, Prof. Yang continues to illuminate intricate problems with clarity and rigor ✨.

Professional Profile

Scopus Profile
ORCID Profile

📘 Education

Professor Fan Yang 🎓 embarked on his academic path at Lanzhou University, a premier institution in China 🇨🇳. He obtained his Bachelor’s degree in Mathematics in 2000, deepening his analytical foundations. Committed to advancing knowledge, he earned his Master’s degree in 2007 and later achieved his Doctoral degree in 2014, specializing in mathematical physics equations. This progressive academic journey illustrates a firm dedication to mathematical excellence 📐. His scholarly roots at Lanzhou University equipped him with the skills to explore abstract theories and practical modeling 🧠. The consistent pursuit of higher education across nearly 15 years showcases his unwavering commitment to mastering complexity and innovation. His academic development has been vital in shaping him into a respected voice within the mathematical research community 🔍.

💼 Professional Experience

Professor Fan Yang currently holds a prestigious role at the School of Science, Lanzhou University of Technology 🏫, where he serves as a full professor. With a career rooted in academia, he has accumulated decades of teaching, mentorship, and research leadership 📊. Over the years, he has played a central role in guiding both undergraduate and postgraduate students, helping nurture the next generation of mathematical minds 👨‍🏫. His collaborative efforts with other scholars and his role in departmental research initiatives reflect his deep integration into academic life 🧩. Prof. Yang’s dedication to fostering scientific thought and problem-solving capacity makes him a pillar of his department. His evolving role from student to faculty leader exemplifies his rise through perseverance, expertise, and scholarly drive 🚀.

🔬 Research Interest

Prof. Fan Yang’s research orbits around inverse problems and fractional diffusion equations, niche yet powerful areas within applied mathematics 🧠. His work primarily addresses ill-posed problems in mathematical physics, especially those modeling heat and source detection phenomena 🔥🧊. His innovative application of regularization techniques—such as Tikhonov, truncation, and mollification—enhances stability and solution accuracy in computational models. He focuses on determining unknown parameters from partial data, contributing solutions to real-world problems in geophysics, medical imaging, and thermal analysis 🌍💡. This niche research supports the broader scientific community in understanding and interpreting complex systems. With publications in high-impact journals and a track record of meaningful inquiry, Prof. Yang continues to redefine mathematical boundaries, blending theory and application in impactful, forward-thinking ways 📈🔎.

🏅 Awards and Honors

Though specific awards and honors are not listed in detail, Professor Fan Yang’s academic recognition is evident through consistent publications in reputable international journals 📰. Journals such as Applied Mathematical Modelling, Journal of Inverse and Ill-Posed Problems, and Computational and Applied Mathematics have showcased his findings, underscoring the scholarly value of his work 🏆. His research has earned collaboration with distinguished mathematicians, a subtle indicator of peer recognition and respect 🤝. Serving as a professor at a top Chinese university further indicates institutional acknowledgment of his contributions 🎖️. While formal accolades may not be detailed here, Prof. Yang’s enduring presence in high-level research forums and his intellectual influence make him a quiet achiever whose work speaks volumes through citations and scholarly impact 🌟.

📌 Conclusion

Professor Fan Yang is a dedicated scholar whose academic path, professional evolution, and focused research agenda reflect a life devoted to scientific advancement 🔭. From tackling complex inverse problems to refining numerical solutions for fractional equations, his work resonates across mathematical physics and engineering realms 🌐. With a foundation built at Lanzhou University and a professorship at Lanzhou University of Technology, his influence continues to grow 📘💡. While he may remain understated in accolades, his scholarly contributions are undeniable—spanning critical journals and collaborative research 🧩. Prof. Yang exemplifies how dedication, precision, and thoughtful inquiry can shape the modern mathematical landscape. As a thinker, mentor, and innovator, he is undoubtedly a valuable figure in advancing computational mathematics and applied sciences 💫🧮.

Publications Top Notes

🔹 Title: Simultaneous Inversion of the Source Term and Initial Value of the Multi-Term Time Fractional Slow Diffusion Equation
Authors: L. Qiao, R. Li, Fan Yang, X. Li
Year: 2025 🗓️
Journal: Journal of Applied Analysis and Computation 🏫📚

🔹 Title: Fractional Landweber Regularization Method for Identifying the Source Term of the Time Fractional Diffusion-Wave Equation
Authors: Z. Liang, Q. Jiang, Q. Liu, L. Xu, Fan Yang
Year: 2025 🗓️
Journal: Symmetry 📐📚

🔹 Title: PINN Neural Network Method for Solving the Forward and Inverse Problem of Time-Fractional Telegraph Equation
Authors: Fan Yang, H. Liu, X. Li, J. Cao
Year: 2025 🗓️
Citations: 2 📚
Journal: Results in Engineering ⚙️

🔹 Title: Two Regularization Methods for Identifying the Initial Value of Time-Fractional Telegraph Equation
Authors: Y. Liang, Fan Yang, X. Li
Year: 2025 🗓️
Citations: 2 📚
Journal: Computational Methods in Applied Mathematics 📊

🔹 Title: Two Regularization Methods for Identifying the Unknown Source of Sobolev Equation with Fractional Laplacian
Authors: Fan Yang, L.L. Yan, H. Liu, X. Li
Year: 2025 🗓️
Citations: 4 📚
Journal: Journal of Applied Analysis and Computation 🏫

🔹 Title: Two Regularization Methods for Identifying the Source Term of Caputo-Hadamard Type Time Fractional Diffusion-Wave Equation
Authors: Fan Yang, R. Li, Y. Gao, X. Li
Year: 2025 🗓️
Journal: Journal of Inverse and Ill-Posed Problems 🔄📚

🔹 Title: Effect of Surface Effect on Linear Bending Behavior of Nano-Switch Structure
Authors: Fan Yang, X. Wang, C. Li
Year: 2024 🗓️
Journal: Yingyong Lixue Xuebao (Chinese Journal of Applied Mechanics) 🔧📚

🔹 Title: Simultaneous Identification of the Unknown Source Term and Initial Value for the Time Fractional Diffusion Equation with Local and Nonlocal Operators
Authors: L. Qiao, Fan Yang, X. Li
Year: 2024 🗓️
Citations: 3 📚
Journal: Chaos, Solitons and Fractals 🌀

🔹 Title: Analysis of Nonlinear Bending Behavior of Nano-Switches Considering Surface Effects
Authors: Fan Yang, X. Wang, X. Song, W. Yang
Year: 2024 🗓️
Journal: Discover Nano 🔬📚

B. Meenakshi Sundaram | Computational Mathematics | Best Researcher Award

Posted on 30/01/202530/01/2025 by Math Scientist

Dr. B. Meenakshi Sundaram | Computational Mathematics | Best Researcher Award

Professor at T. John Group of Institutions India

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with over 25 years of experience in teaching, research, and administration across India and the UAE. He has made significant contributions to computer science, specializing in machine learning, IoT, cloud security, and semantic web mining. With 25+ publications in SCOPUS and IEEE-indexed journals and presentations at 20+ international awards, his research has garnered global recognition. He actively supervises PhD scholars and has mentored over 100 undergraduate and postgraduate research projects. As a curriculum developer, he has aligned academic programs with national and international standards. He holds key research identifiers, including a Scopus ID and an h-index of 4. His expertise extends to industry collaborations, technical writing, and consultancy services. While enhancing high-impact research and funded projects could further strengthen his profile, his vast academic and research contributions make him a strong contender for the Best Researcher Award.

Professional Profile:

Google Scholar
ORCID Profile

Education:

Prof. Dr. B. Meenakshi Sundaram holds a Ph.D. in Computer Science from Bharathiar University, Coimbatore (2017), showcasing his expertise in advanced computing research. He earned his M.Tech in Information Technology (2009) from Manonmaniam Sundaranar University, securing First Class with Distinction. His academic journey began with a B.Sc. in Physics with Electronics (1996) and an M.Sc. in Computer Science (1998), both from Madurai Kamaraj University, where he excelled with distinction. Additionally, he pursued an M.Phil in Computer Science (2006) to deepen his research acumen. Beyond formal degrees, he has completed specialized professional certifications, including NPTEL courses from IIT Kharagpur and IIT Madras, as well as industry-relevant training from Infosys, Wipro, and IBM. His diverse educational background, spanning core science, engineering, and computing disciplines, has enabled him to make significant contributions to academia, research, and curriculum development at both national and international levels.

Professional Experience:

Prof. Dr. B. Meenakshi Sundaram has over 25 years of extensive experience in teaching, research, and academic administration across India and the UAE. He has served as a Professor, Associate Professor, Academic Program Manager, and Exam Controller at prestigious institutions, including New Horizon College of Engineering, Karunya University, and Syscoms College, Abu Dhabi. His expertise lies in curriculum development, faculty enrichment, industry-academic collaboration, and research supervision. He has played a key role in designing and aligning Bachelors and Masters programs with national and international accreditation standards. As a researcher, he has supervised PhD scholars, guided 100+ postgraduate and undergraduate research projects, and published 25+ research papers in SCOPUS and IEEE-indexed journals. He has also been actively involved in consultancy services, technical writing, and faculty training programs. With a strong commitment to academic excellence, he continues to contribute to cutting-edge research in computer science, artificial intelligence, and cloud computing.

Research Interest:

Prof. Dr. B. Meenakshi Sundaram’s research interests encompass a wide range of cutting-edge areas in computer science, artificial intelligence, and cybersecurity. His work primarily focuses on semantic web mining, machine learning, IoT, cloud security, and data analytics, addressing critical challenges in intelligent systems and computational frameworks. He has made significant contributions to ontology-based information retrieval, cloud integration, and security frameworks, with an emphasis on developing efficient and scalable solutions for real-world applications. His research also extends to imbalanced data classification, deep learning, and digital innovation in education, exploring novel methodologies to enhance computational intelligence and cybersecurity mechanisms. With a strong commitment to interdisciplinary research, he actively engages in AI-driven enterprise security, intelligent decision-making systems, and web service optimizations, aiming to bridge the gap between academia and industry. His research efforts contribute to advancing smart computing, digital transformation, and next-generation AI technologies.

Award and Honor:

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with a remarkable career spanning over 25 years in teaching, research, and administration. His contributions to computer science, particularly in machine learning, IoT, cloud security, and semantic web mining, have earned him recognition in national and international forums. He has published 25+ research papers in reputed SCOPUS and IEEE-indexed journals, presented at 20+ awards, and actively mentors PhD scholars and postgraduate students. As a professional member of IEEE and Institution of Engineers (India), he has contributed to global research collaborations and curriculum development initiatives. He has received certifications from IIT Madras, IIT Kharagpur, and other reputed institutions, further showcasing his dedication to academic excellence. His significant contributions to academia, research supervision, and international collaborations make him a highly deserving candidate for prestigious awards in research and innovation.

Conclusion:

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with 25 years of experience in teaching, research, and administration. His extensive contributions to computer science, particularly in semantic web mining, IoT, and cloud security, are reflected in his 25+ publications in reputed journals, including SCOPUS and IEEE-indexed papers. As a mentor, he has guided numerous research scholars and postgraduate students, fostering academic excellence. His involvement in curriculum development, international collaborations, and industry-academia partnerships further solidifies his impact on higher education. While his research credentials are strong, expanding high-impact publications, securing funded projects, and increasing citation metrics can enhance his global research standing. Nevertheless, his academic leadership, interdisciplinary research, and commitment to knowledge dissemination make him a highly deserving candidate for the Best Researcher Award. His dedication to innovation and scholarly excellence continues to shape the future of computing and technology-driven education.

Publications Top Noted:

Face recognition based automated remote proctoring platform
- Authors: N Sasikala, BM Sundaram, VN Kumar, J Sumanth, S Hrithik
- Year: 2022
- Citations: 7
Survey of latest technologies on Decentralized applications using Blockchain
- Authors: N Sasikala, BM Sundaram, S Biswas, AS Nikhil, VS Rohith
- Year: 2022
- Citations: 6
Disaster relief compensation computational framework
- Authors: BM Sundaram, B Rajalakshmi, BA Singh, RS Kumar, R Arsha
- Year: 2022
- Citations: 6
More Accurate Organ Recipient Identification Using Survey Informatics of New Age Technologies
- Authors: BM Sundaram
- Year: 2021
- Citations: 6
Fall detection among elderly using deep learning
- Authors: BM Sundaram, B Rajalakshmi, RK Mandal, S Nair, SS Choudhary
- Year: 2023
- Citations: 4
An Analysis on Security Threats in Cloud Computing
- Authors: AP Nirmala, R Prema, BM Sundaram
- Year: 2019
- Citations: 4
A Roadmap to Application Integration using IoT Cloud Platform
- Authors: DT Dr. BM Sundaram
- Year: 2020
- Citations: 3
Cross Domain Composition of Web Service Workflows using a Provenance Ontology with an automated Re-planning
- Authors: BM Sundaram, D Manimegalai
- Year: 2015
- Citations: 3
Semantic Interoperable EHR mapping with syndromic surveillance to anticipate regional outbreak
- Authors: BM Sundaram
- Year: 2020
- Citations: 2
Fuzzy-XDDS: A Fuzzy Based Cross-Domain Services Matchmaker for Semantic Web Services
- Authors: BM Sundaram, D Manimegalai
- Year: 2015
- Citations: 2
AirGuard AI: Revolutionizing Air Cargo Inspection through Pygame and YOLOv8 Simulation
- Authors: BM Sundaram, B Rajalakshmi, A Saxena, B Vasumati
- Year: 2024
- Citations: 1
Deep learning implemented communication system for the auditory and verbally challenged
- Authors: B Chempavathy, BM Sundaram, A Shaynam, A Goswami, S Bindya
- Year: 2023
- Citations: 1
Malware Exposed: An In-Depth Analysis of its Behavior and Threats
- Authors: C Anand, S Korada, S Raksha, BM Sundaram, B Rajalakshmi
- Year: 2023
- Citations: 1
Modeling crime prediction using ML
- Authors: BM Sundaram, B Rajalakshmi, B Anusha, MK Bindu, BL Keerthi
- Year: 2022
- Citations: 1
Cardiovascular disease detection using machine learning-a survey
- Authors: BM Sundaram, B Rajalakshmi, Eshwar, Tanith, L Emmanuel
- Year: 2022
- Citations: 1
A holistic redesign of web elements using CATWOE analysis
- Authors: R Jayakumar, BM Sundaram, MA Sankaridevi
- Year: 2019
- Citations: 1
Dual Tree Complex Wavelet based Regularized Deconvolution for Medical Images
- Authors: R Murugesan, V Thavavel, BM Sundaram
- Year: 2007
- Citations: 1
Smart City Traffic Management
- Authors: BM Sundaram, JG Chowdary, R Gonela, B Rajalakshmi
- Year: 2024
- Citations: 1
Retinal Authentication for E-Voting
- Authors: LS Hanne, BM Sundaram, M Rakshitha, V Kishore, A Meenakshi
- Year: 2024
- Citations: 1
DRS-UNET: A Deep Learning Approach for Diabetic Retinopathy Detection and Segmentation from Fundus Images
- Authors: RS Gound, BM Sundaram, SK BV, PA Azmat, MNU Habib, A Garg
- Year: 2023
- Citations: 1