Ajay Kumar | Numerical Analysis | Indian Institute of Technology Kanpur

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Dr. Ajay Kumar | Numerical Analysis | Indian Institute of Technology Kanpur

Post Doctoral | Indian Institute of Technology Kanpur | India

Dr. Ajay Kumar is a Postdoctoral Fellow in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur, specializing in fractional calculus, nonlinear dynamics, numerical analysis, and mathematical modeling of disease and ecological systems. He earned his Ph.D. in Mathematics with a focus on fractional calculus from the National Institute of Technology Jamshedpur, following an M.Sc.-Tech in Mathematics and Computing from Jamia Millia Islamia and a B.Sc. in Physics, Chemistry, and Mathematics from CCS University, Meerut. Before joining IIT Kanpur, he served as an Assistant Professor at JECRC University, Jaipur, where he contributed to academic instruction and research mentorship. Dr. Kumar has an impressive publication record in high-impact journals such as Chaos, Solitons & Fractals, Results in Physics, Mathematics and Computers in Simulation, and Journal of Computational Science, reflecting his strong engagement in the study of fractional-order dynamical systems, eco-epidemiological modeling, and chaos theory. His research collaborations span internationally with scholars from Saudi Arabia, Egypt, and India, demonstrating a broad and interdisciplinary research network. He has also presented his work at multiple national and international conferences and participated in workshops and training programs that enhance computational and analytical expertise. Dr. Kumar’s academic excellence is supported by national-level qualifications such as GATE and IIT-JAM, alongside prestigious research fellowships including the Junior and Senior Research Fellowships from NIT Jamshedpur. With over 500 citations and an H-index of 10, his contributions significantly advance the application of fractional calculus in complex system modeling.

Profiles: ORCID | Google Scholar

Featured Publications

1. Kumar S., Kumar A., Samet B., Gómez-Aguilar J.F., Osman M.S., A chaos study of tumor and effector cells in fractional tumor-immune model for cancer treatment. Chaos, Solitons & Fractals, 2020, Citations: 222.

2. Kumar S., Kumar A., Samet B., Dutta H., A study on fractional host–parasitoid population dynamical model to describe insect species. Numerical Methods for Partial Differential Equations, 2021, Citations: 187.

3. Kumar A., Kumar S., A study on eco-epidemiological model with fractional operators. Chaos, Solitons & Fractals, 2022, Citations: 43.

4. Kumar S., Kumar A., Jleli M., A numerical analysis for fractional model of the spread of pests in tea plants. Numerical Methods for Partial Differential Equations, 2022, Citations: 27.

5. Alzaid S.S., Kumar A., Kumar S., Alkahtani B.S.T., Chaotic behavior of financial dynamical system with generalized fractional operator. Fractals, 2023, Citations: 18.

Vesna Knights | Mathematics in Enginering | Mathematical Engineering Excellence Award

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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.

Jun Liu | Mathematical Finance | Best Researcher Award

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Dr. Jun Liu | Mathematical Finance | Best Researcher Award

Shanghai Technical Institute of Electronics & Information, China

Dr. Jun Liu 🎓 is a dedicated researcher in mathematical finance, currently serving at the Shanghai Technical Institute of Electronics & Information 🏢. His research focuses on asset pricing, particularly in modeling uncertainty in electricity markets ⚡ using Geometric Brownian motions. He has introduced innovative pricing models for integrated energy systems (IESs), contributing significantly to the understanding of energy economics 🔍. His publications in reputable journals like Fractal and Fractional and Heliyon 📚 reflect a growing academic impact. Dr. Liu’s ongoing work on carbon options pricing aligns with global sustainability goals 🌍. With a keen interest in bridging theory and real-world application, he is advancing the field through practical, data-driven insights 💡. His contributions continue to support the evolution of pricing strategies in dynamic, energy-related financial systems 📈.

Professional Profile 

Scopus Profile
ORCID Profile

🎓 Education

Dr. Jun Liu holds a solid academic foundation in mathematics and finance, having pursued his higher education from reputable Chinese institutions 🏫. With a strong inclination toward applied mathematical models, particularly in asset pricing and energy economics, his academic journey reflects a consistent drive for theoretical depth and practical relevance 📘. His educational background equipped him with robust skills in quantitative analysis, probability theory, and stochastic processes 🔢. These form the bedrock of his research in modeling financial systems under uncertainty. His commitment to continuous learning and academic excellence is evident in his publications and research engagements, establishing him as a competent scholar in mathematical finance 🎓. Dr. Liu’s education has not only shaped his professional journey but also empowered him to contribute innovatively to interdisciplinary research.

🧑‍🏫 Professional Experience

Dr. Jun Liu currently serves as a faculty member at the Shanghai Technical Institute of Electronics & Information 🏢. His professional journey includes valuable academic and research contributions in mathematical finance, where he focuses on developing models for asset pricing and energy economics 📊. With a practical understanding of market dynamics and mathematical tools, he bridges theoretical constructs with real-world applications. His experience extends to mentoring students, presenting research findings, and publishing in reputed journals like Fractal and Fractional and Heliyon 📚. Dr. Liu maintains active involvement in ongoing research projects, such as carbon options pricing, showcasing his ability to work on emerging and impactful topics 🌍. His professional expertise underscores a blend of academic rigor and forward-thinking innovation in finance and energy modeling 🔍.

🔬 Research Interest

Dr. Jun Liu’s primary research interests lie in mathematical finance, particularly in the area of asset pricing under uncertainty 📈. His recent work incorporates Geometric Brownian motion models to capture the volatility of electricity prices within integrated energy systems ⚡. By focusing on how various energy sources — like gas and heat — affect market pricing, he contributes novel insights to energy economics and stochastic modeling 🔢. Dr. Liu is also engaged in research on carbon options pricing, aligning with sustainable finance and global environmental concerns 🌱. His interests reflect a strong interdisciplinary approach, combining mathematics, economics, and data science. He is passionate about using mathematical tools to solve practical challenges in dynamic markets, thereby improving pricing strategies, risk assessment, and economic forecasting 📊.

🏅 Awards and Honors

Dr. Jun Liu’s dedication to mathematical research has earned him growing recognition in academic circles 🧠. While formal awards are still accumulating, his contributions to asset pricing and energy modeling have garnered positive peer reception 📣. His publications in indexed international journals, such as Heliyon and Fractal and Fractional, highlight the impact and relevance of his work on a global scale 🌐. As a young scholar, he is on a promising path toward receiving broader recognition in the future, particularly in the areas of sustainable finance and energy market analysis 🏆. His innovative pricing models and engagement with pressing issues like carbon options further position him as a rising talent in applied mathematics and finance 🧮.

🧠 Research Skills

Dr. Jun Liu possesses a diverse and evolving set of research skills critical to modern mathematical finance 🔬. He is proficient in quantitative modeling, stochastic analysis, and developing financial algorithms for real-world applications 📈. His adept use of Geometric Brownian motion to model uncertainty in electricity pricing demonstrates his ability to translate theory into impactful economic tools ⚡. Dr. Liu is also skilled in computational techniques and mathematical software, enabling rigorous numerical analysis and simulations 🔢. His academic writing, data interpretation, and interdisciplinary collaboration skills add to his research versatility 📚. With strengths in both independent investigation and team-based projects, Dr. Liu exemplifies the traits of a methodical, insightful, and results-driven researcher in an ever-evolving academic landscape 🌍.

Publications Top Note 📝

  • Title: A new pricing method for integrated energy systems based on geometric Brownian motions under the risk-neutral measure
    Authors: Jun Liu, Lihong Zhou, Hao Yu
    Year: 2024
    Source: Heliyon | DOI: 10.1016/j.heliyon.2024.e38140
    Publisher: Elsevier via Crossref

  • Title: New Stability Results of the Modified Craig-Sneyd Scheme in a Multidimensional Diffusion Equation with Mixed Derivative Terms
    Authors: Jun Liu, Qing Zhu, Lihong Zhou
    Year: 2023
    Source: Journal of Physics
    Publisher: Likely IOP Publishing (based on journal name)

  • Title: Convergence Rate of the High-Order Finite Difference Method for Option Pricing in a Markov Regime-Switching Jump-Diffusion Model
    Authors: Jun Liu, Jingzhou Yan
    Year: 2022
    Source: Fractal and Fractional | DOI: 10.3390/fractalfract6080409
    Publisher: MDPI

  • Title: Valuation of Insurance Products with Shout Options in a Jump-Diffusion Model
    Authors: Jun Liu, Zhian Liang, Emilio Gómez-Déniz
    Year: 2021
    Source: Mathematical Problems in Engineering | DOI: 10.1155/2021/3948897
    Publisher: Hindawi via Crossref

📝 Conclusion

Dr. Jun Liu stands out as a promising researcher in mathematical finance, demonstrating both academic depth and practical relevance 💡. His innovative work in asset pricing, particularly within energy systems and carbon markets, addresses critical challenges in economics and sustainability 🌱. With a robust educational foundation, strong research methodology, and publications in reputable journals, Dr. Liu has positioned himself as an emerging thought leader in his field 🌐. While further recognition and citations will enhance his academic stature, his current contributions are already impactful. As he continues to expand his research scope and collaborate across disciplines, Dr. Liu is poised to make lasting contributions to both theoretical mathematics and applied economic modeling 🎓📊.