Ramin Raesi | Computational Methods | Research Excellence Award

Mr. Ramin Raesi | Computational Methods | Research Excellence Award

PhD student | KU Leuven | Belgium

Mr. Ramin Raesi is an emerging researcher in computational fluid dynamics, focusing on two-phase flow, turbulent flow, and population balance modeling. His research interests include hydrocyclones, sediment transport, and multiphase simulations. He has strong skills in CFD modeling, turbulence development, and numerical analysis. His work on deoiling hydrocyclones highlights his contribution. He has gained recognition through citations and publications. Based on the provided data, he has 42 citations, 5 documents, and an h-index of 1, reflecting growing research impact and future potential.

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Lu Wang | Machine Learning in Physics | Research Excellence Award

Assist. Prof. Dr. Lu Wang | Machine Learning in Physics | Research Excellence Award

Assistant Professor | City University of Hong Kong | Hong Kong

Assist. Prof. Dr. Lu Wang, based at City University of Hong Kong, specializes in computational materials science and additive manufacturing. His research focuses on multi-physics modeling, crystal plasticity, and microstructure evolution. He is skilled in finite element analysis, simulation, and materials characterization. Dr. Wang has published in leading journals such as Nature Communications and earned recognition for impactful research contributions. According to Scopus, he has 30 documents, 1,411 citations, and an h-index of 18, reflecting his strong influence in advancing computational materials engineering.

 

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Haranath Ghosh | Computational Methods | Research Excellence Award

Prof. Dr. Haranath Ghosh | Computational Methods | Research Excellence Award

Professor | Raja Ramanna Centre for Advanced Technology | India

Prof. Dr. Haranath Ghosh is a leading researcher at the Raja Ramanna Centre for Advanced Technology, specializing in condensed matter physics and material science. His interests include superconductivity, electron correlation, and optical properties of advanced materials. He demonstrates expertise in theoretical modeling, computational analysis, and spectroscopy. He has received recognition for impactful scientific contributions. With over 1,593 citations, an h-index of 20, and 43 i10-index (Google Scholar), his work significantly advances understanding of quantum materials and supports innovations in modern physics and technology.

 

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David Amilo | Applied Mathematics | Young Scientist Award

Dr. David Amilo | Applied Mathematics | Young Scientist Award

Lecturer/Researcher at Near East University, Cyprus

Dr. David Ikechukwu Amilo 🎓 is an emerging scholar in applied mathematics, with a distinct focus on fractional-order epidemic modeling and network time series analysis. Holding a Bachelor’s degree from Ebonyi State University, Nigeria (2014), and both Master’s (2020) and PhD (2023) from Near East University, Cyprus, his academic journey reflects steady growth in mathematical modeling and computational research. He has developed sophisticated models tackling real-world health issues such as dual-strain infections and alcoholic cardiomyopathy 🧬. With multiple accolades including the 2025 Young Scientist Award 🏅 and a Bronze Medal from the National Mathematics Competition 🥉, he showcases excellence in theoretical development and simulation techniques. Dr. Amilo stands out for his interdisciplinary insights, passion for science, and commitment to impactful research. His scholarly promise and early contributions affirm his rising influence in the scientific and academic world. 🚀📚

Professional Profile 

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🎓 Education

Dr. Amilo’s academic path is marked by consistency, depth, and forward-thinking research. He earned his Bachelor’s in Mathematics from Ebonyi State University in 2014, laying the groundwork for his analytical and abstract reasoning skills 🧠. He later pursued graduate studies at Near East University, Cyprus, where he earned his Master’s degree in 2020, under the mentorship of Assoc. Prof. Dr. Bilgen Kaymakamzade, focusing on fractional-order epidemic systems with vaccination strategies 🧪. He continued under the same advisor for his PhD (2023), exploring advanced modeling of alcoholic cardiomyopathy with network-based time series — a novel fusion of fractional calculus and epidemiological insight 🧬. His education reflects a blend of mathematical rigor and public health relevance, equipping him with advanced tools in mathematical modeling, simulation, and system dynamics 🔬📈.

👨‍🏫 Professional Experience

Though he has not yet held formal academic titles such as Assistant or Associate Professor, Dr. Amilo has already made a strong impression in academic circles through impactful research and recognized participation in prestigious conferences 🌍. His active engagement in scientific projects, coupled with a rapidly growing publication profile, speaks to his dedication and research-centric mindset 🧑‍💻. With peer collaborations and cross-disciplinary modeling work, he is building a solid foundation toward a professorial career. Dr. Amilo is poised to take on supervisory and academic responsibilities, potentially mentoring future scholars in the intricacies of fractional models and their real-world applications 📚🔢. His commitment to continual learning and contribution is evident from his self-motivated pursuit of high-impact research without waiting for formal titles.

🔬 Research Interests

Dr. Amilo’s research interests orbit around fractional-order differential equations, epidemiological dynamics, and network-based simulations. His Master’s and PhD work reveals a fascination with mathematical modeling of complex health systems, particularly those involving multiple interacting variables or co-infections 💉🦠. He is deeply drawn to the practical applications of theoretical models — employing fractional calculus to better understand the progression of diseases such as alcoholic cardiomyopathy or multi-strain epidemics. Recently, he has been venturing into time-series analysis on networks, adding another analytical layer to his work. This multidimensional approach enhances the real-time predictive power of disease spread and control measures 📊🌐. Through computational simulations, he aims to inform health policies and improve response strategies to public health crises. His research bridges pure mathematics with tangible societal impact 🧮❤️‍🩹.

🏆 Awards and Honors

Dr. Amilo’s brilliance has earned him several prestigious recognitions. In 2025, he was honored with the Young Scientist Award by Near East University 🎖️. Earlier, he won the Young Researcher Award (2022) and gained international attention with his victory in the 2023 Computational Modeling and Simulation of FRPsat, at the International Research Awards on Fiber Reinforced Polymer 🌟. These accolades underscore his versatility and potential in both pure and applied mathematical domains. Notably, his Bronze Medal at the NAMCUS (2015) national math competition reflects a long-standing excellence in mathematical problem-solving 🥉. His decorated profile at an early career stage is a testament to his innovation, determination, and relevance in global research dialogues. 📜💡

📚 Publications Top Note 

1. Title: A fractional-order mathematical model for lung cancer incorporating integrated therapeutic approaches

  • Authors: D. Amilo, B. Kaymakamzade, E. Hincal

  • Year: 2023

  • Citations: 41

  • Source: Scientific Reports, Volume 13, Article 12426

  • Summary: This study introduces a novel fractional-order model for lung cancer progression that integrates multiple treatment strategies including chemotherapy and immunotherapy. The model evaluates the synergistic effect of therapies on tumor suppression and aims to optimize treatment schedules.


2. Title: A mathematical model with fractional-order dynamics for the combined treatment of metastatic colorectal cancer

  • Authors: D. Amilo, K. Sadri, B. Kaymakamzade, E. Hincal

  • Year: 2024

  • Citations: 37

  • Source: Communications in Nonlinear Science and Numerical Simulation, Volume 130, 107756

  • Summary: This paper presents a fractional-order model that simulates the dynamics of metastatic colorectal cancer under combined therapies. The model analyzes the role of chemotherapy and immunotherapy in managing tumor spread, highlighting the benefits of fractional calculus in capturing memory effects.


3. Title: A tau-Gegenbauer spectral approach for systems of fractional integro-differential equations with the error analysis

  • Authors: K. Sadri, D. Amilo, K. Hosseini, E. Hinçal, A.R. Seadawy

  • Year: 2024

  • Citations: 16

  • Source: AIMS Mathematics, Volume 9, Issue 2, Pages 3850–3880

  • Summary: The authors develop a spectral numerical method based on tau-Gegenbauer polynomials to solve fractional integro-differential systems. The paper includes rigorous error analysis, demonstrating the accuracy and stability of the method.


4. Title: Mathematical Analysis and Dynamical Transmission of (SEIrIsR) Model with Different Infection Stages by using fractional operator

  • Authors: C. Xu, M. Farman, Y. Pang, Z. Liu, M. Liao, L. Yao, A. Shehzad, D. Amilo

  • Year: 2024

  • Citations: 15

  • Source: International Journal of Biomathematics

  • Summary: This study models the dynamics of infectious diseases with multiple infection stages using a SEIrIsR framework and fractional operators. The model demonstrates how memory effects influence the transmission and recovery processes.


5. Title: A fractional-order model for optimizing combination therapy in heterogeneous lung cancer: integrating immunotherapy and targeted therapy to minimize side effects

  • Authors: D. Amilo, C. Izuchukwu, K. Sadri, H.R. Yao, E. Hincal, Y. Shehu

  • Year: 2024

  • Citations: 15

  • Source: Scientific Reports, Volume 14, Article 18484

  • Summary: This article proposes a fractional-order model targeting heterogeneity in lung cancer cells. It investigates how a combination of immunotherapy and targeted therapy can be optimized to reduce side effects while maintaining efficacy.


6. Title: A fractional-order model for nosocomial infection caused by pseudomonas aeruginosa in Northern Cyprus

  • Authors: C. Bagkur, D. Amilo, B. Kaymakamzade

  • Year: 2024

  • Citations: 14

  • Source: Computers in Biology and Medicine, Volume 171, 108094

  • Summary: The paper introduces a fractional-order model to understand and control hospital-acquired infections caused by Pseudomonas aeruginosa. It evaluates the dynamics of infection transmission and antibiotic resistance in clinical settings.


7. Title: Effect of Lactuca sativa supplemented diet on Poloxamer 407 induced hyperlipidemic albino rats (Rattus norvegicus)

  • Authors: V.I. Ayo, M.A. Adondua, A.E. Morayo, J. Ekele, D. Amilo, D.A. Ochuele, et al.

  • Year: 2023

  • Citations: 10

  • Source: Asian Journal of Natural Product Biochemistry, Volume 21, Pages 67–78

  • Summary: This experimental study explores the lipid-lowering potential of Lactuca sativa in rats with induced hyperlipidemia. It shows that the plant-based diet has a significant impact on improving lipid profiles.


8. Title: Fractional SVIR model for COVID-19 under Caputo derivative

  • Authors: N. Gokbulut, D. Amilo, B. Kaymakamzade

  • Year: 2021

  • Citations: 9

  • Source: Journal of Biometry Studies, Volume 1, Issue 2, Pages 58–64

  • Summary: This paper proposes a SVIR (Susceptible–Vaccinated–Infected–Recovered) model using Caputo fractional derivatives to simulate COVID-19 spread. The model emphasizes the role of fractional order in accurately reflecting pandemic memory and control measures.


9. Title: A fractional-order two-strain epidemic model with two vaccinations

  • Authors: B. Kaymakamzade, E. Hincal, D. Amilo

  • Year: 2021

  • Citations: 6

  • Source: AIP Conference Proceedings, Volume 2325, Article 1

  • Summary: This model investigates the dynamics of two co-existing viral strains and their control via dual vaccination strategies. The fractional component captures latency and immunity duration, providing better insights into epidemic management.


10. Title: A generalized Chebyshev operational method for Volterra integro-partial differential equations with weakly singular kernels

  • Authors: S.S.K. Sadri, D. Amilo, E. Hincal, K. Hosseini

  • Year: 2024

  • Citations: 5

  • Source: Heliyon, Volume 10, Issue 5, e27260

  • Summary: This work introduces a novel operational matrix method using generalized Chebyshev polynomials for solving complex Volterra integro-partial differential equations. It efficiently handles weak singularities and demonstrates excellent convergence.

Conclusion

In summary, Dr. David Ikechukwu Amilo is a promising mathematician whose work elegantly weaves together theory, computation, and real-world application 🔗. His academic trajectory, shaped by deep curiosity and precision, has led to impactful research on complex health models using fractional calculus. Backed by notable awards and a strong educational foundation, Dr. Amilo is not just a researcher but an innovator poised to lead in applied mathematics and health modeling 📈🌍. With continued mentorship and institutional support, his potential to shape new frontiers in mathematical epidemiology and dynamic systems is immense. His passion for problem-solving, evident early on in competitions and now in cutting-edge simulations, sets the tone for a meaningful and inspiring academic journey ahead. 💼📘✨