Vesna Knights | Mathematics in Enginering | Mathematical Engineering Excellence Award

Prof. Vesna Knights | Mathematics in Enginering | Mathematical Engineering Excellence Award

Professor | St. Clement of Ohrid University of Bitola | Macedonia

Prof. Vesna Antoska Knights is a Full Professor at the Faculty of Technology and Technical Sciences – Veles, University “St. Kliment Ohridski” – Bitola, Republic of North Macedonia, specializing in applied mathematics, mathematical modelling, statistics, artificial intelligence, and optimization. She holds a Ph.D. in Technical Sciences from the Faculty of Electrical Engineering and Information Technologies, “Ss. Cyril and Methodius University” – Skopje, where her doctoral research focused on robotic system modelling and control. Her academic background includes a Master of Science in Technical Sciences with specialization in numerical simulation of flow and a Bachelor’s degree in Mechanical Engineering. With over two decades of university teaching and research experience, she has served in multiple leadership roles, including Vice Dean for Science and International Cooperation and Head of the Doctoral Studies Council. Dr. Knights has led and participated in numerous international and EU-funded projects, including FP7 ECCEROBOT, COST Action DE-PASS, and national research initiatives on smart agriculture and machine learning applications. Her interdisciplinary research bridges engineering, data science, nutrition, and IoT-based intelligent systems, resulting in 19 indexed publications and significant citations in international journals such as Applied Sciences, Nutrients, and Future Internet. She serves as an Editorial Board Member of Chemistry in Industry (KUI) and is actively engaged in European academic networks. Her recent contributions include advances in AI-based modeling for nutrition, robotic control, and optimization in smart systems. Professor Knights continues to contribute to the scientific community through mentorship, editorial work, and collaborative international research. 62 Citations, 19 Documents, h-index 5.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Knights, V., & Prchkovska, M. (2024). From equations to predictions: Understanding the mathematics and machine learning of multiple linear regression. Journal of Mathematical & Computer Applications, 3(2), 1–8. Citations: 11.

2. Knights, V., & Petrovska, O. (2024). Dynamic modeling and simulation of mobile robot under disturbances and obstacles in an environment. Journal of Applied Mathematics & Computation, 8(1), 59–67. Citations: 7.

3. Knights, V., Petrovska, O., & Gajdoš Kljusurić, J. (2024). Nonlinear dynamics and machine learning for robotic control systems in IoT applications. Future Internet, 16(12), 435. Citations: 7.

4. Knights, V., Kolak, M., Markovikj, G., & Gajdoš Kljusurić, J. (2023). Modeling and optimization with artificial intelligence in nutrition. Applied Sciences, 13(13), 7835. Citations: 27.

5. Antoska-Knights, V., Gacovski, Z., & Deskovski, S. (2017). Obstacles avoidance algorithm for mobile robots using the potential fields method. Universal Journal of Electrical and Electronic Engineering, 5, 75–84. Citations: 11.

Fan Yang | Computational Mathematics | Best Researcher Award

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 🔬📚