Shantia Yarahmadian | Mathematics | Best Researcher Award

Dr. Shantia Yarahmadian | Mathematics | Best Researcher Award 

Applied Mathematics at Mississippi State University | United States

Dr. Shantia Yarahmadian is an Associate Professor of Mathematics whose career bridges applied mathematics, biology, quantum computing, and engineering sciences. His professional journey reflects a strong dedication to interdisciplinary problem-solving, focusing on challenges that require innovative mathematical modeling. With extensive teaching, research, and mentoring experience, Dr. Shantia Yarahmadian has contributed significantly to advancing knowledge in mathematical biology, stochastic modeling, and computational sciences. His work has also extended into emerging fields such as quantum-resistant blockchain and artificial intelligence applications. He continues to shape the future of mathematics through impactful publications, editorial roles, and leadership in both academic and industry settings.

Profile:

Orcid | Google Shcolar

Education:

Dr. Shantia Yarahmadian’s academic foundation is firmly rooted in applied mathematics and engineering. He earned his Ph.D. in Applied Mathematics from Indiana University, where he developed expertise in nonlinear analysis and boundary layer theory. Before this, he completed a Master’s degree in Mathematics at Isfahan University of Technology, followed by a Bachelor’s degree in Electrical Engineering at the same institution. This progression from engineering fundamentals to advanced mathematical research equipped him with a versatile skill set, allowing him to navigate both theoretical frameworks and practical applications. His educational background laid the groundwork for his diverse research portfolio across mathematics, biology, and computing.

Experience:

Dr. Shantia Yarahmadian has held prominent academic and research positions across universities and industry. As Associate Professor at Mississippi State University, he has developed innovative teaching methods, supervised doctoral and master’s students, and advanced interdisciplinary collaborations. Previously, he served as Assistant Professor in the same department and undertook a Postdoctoral Fellowship in Biology, where he applied mathematical modeling to biomedical challenges. His earlier career included roles as Research Assistant and Associate Instructor, shaping his dual strengths in pedagogy and research. In addition to academia, he also contributes as an industry advisor in cyber security, emphasizing blockchain and quantum-safe technologies.

Research Interests:

Dr. Shantia Yarahmadian’s research spans multiple disciplines, unified by the application of mathematics to real-world problems. In mathematical biology, he models microtubules, tumor radiotherapy, and Alzheimer’s disease progression, contributing to healthcare innovation. His expertise in nonlinear partial differential equations and stochastic processes supports advanced simulations and predictive modeling. In signal processing, his work with wavelets and compressed sensing improves data analysis across engineering and biomedical applications. His contributions to quantum computing and quantum-resistant blockchain represent forward-thinking approaches to cybersecurity and data integrity. Dr. Shantia Yarahmadian’s research highlights the powerful role of mathematical modeling in solving pressing challenges in science and technology.

Awards and Honors:

Dr. Shantia Yarahmadian has received recognition for his excellence in research, teaching, and mentorship throughout his career. He has been honored with awards for outstanding graduate student mentorship and faculty contributions, demonstrating his dedication to fostering future scholars. His innovative research projects in mathematical biology and engineering applications have attracted competitive funding and institutional support. He has also received prestigious fellowships and teaching awards that highlight his dual strengths in research and education. These honors reflect his international reputation as a thought leader in applied mathematics and his commitment to advancing knowledge through impactful academic and professional service.

Publications:

Title: An Ito stochastic differential equations model for the dynamics of the MCF-7 breast cancer cell line treated by radiotherapy
Citation: 27
Year of Publication: 2016

Title: On the use of the genetic algorithm filter-based feature selection technique for satellite precipitation estimation
Citation: 26
Year of Publication: 2012

Title: On the use of a cluster ensemble cloud classification technique in satellite precipitation estimation
Citation: 22
Year of Publication: 2012

Title: Existence and stability of steady states of a reaction convection diffusion equation modeling microtubule formation
Citation: 20
Year of Publication: 2011

Title: The use of compressive sensing and peak detection in the reconstruction of microtubules length time series in the process of dynamic instability
Citation: 16
Year of Publication: 2015

Title: A Hybrid Differential Equations Model for the Dynamics of Single and Double Strand Breaks of Cancer Cells Treated by Radiotherapy: A Meaning for Tumor Life-Span
Citation: 14
Year of Publication: 2022

Title: A Mathematical Model for Amyloid-β Aggregation in the Presence of Metal Ions: A Timescale Analysis for the Progress of Alzheimer Disease
Citation: 14
Year of Publication: 2019

Conclusion:

Dr. Shantia Yarahmadian stands out as a distinguished scholar whose career demonstrates a perfect balance between research innovation, academic mentorship, and cross-disciplinary collaboration. His contributions to mathematical biology, stochastic modeling, quantum computing, and engineering highlight his versatility and forward-thinking approach. By bridging theoretical mathematics with applied sciences, he has produced insights that benefit healthcare, cybersecurity, and data science. His impactful publications, global collaborations, and record of mentorship illustrate a sustained commitment to advancing knowledge and training the next generation of researchers. Dr. Shantia Yarahmadian is an exceptional candidate for award recognition in mathematics and interdisciplinary research.

Zahoor shah | Mathematics | Best Researcher Award

Assist. Prof. Dr. Zahoor shah | Mathematics | Best Researcher Award

Assistant Professor at COMSATS University Islamabad, Pakistan.

Dr. Zahoor Shah 🇵🇰 is a distinguished Assistant Professor at COMSATS University Islamabad, Pakistan 🏛️. A gold medalist 🥇 in Computational Mathematics, he is a leading researcher in Artificial Intelligence 🤖, Computational Fluid Dynamics 🌊, and Bio-Mechanics 🧬. With over 80+ publications in prestigious international journals 📚 and an impact factor exceeding 103 📈, Dr. Shah’s interdisciplinary research bridges mathematical modeling and machine learning. He is not only an educationist 👨‍🏫 but also a climate activist 🌱, youth leader 👥, and seasoned speaker 🎤. His contributions span academia, social development, and scientific innovation. As Chairman of the National Youth Parliament Pakistan 🇵🇰 and a former director in media and health sectors 📺🏥, he blends scientific excellence with community engagement. His collaborations with international scholars in Taiwan, China, and Egypt 🌍 reflect a dynamic global presence, making him a top contender for the Best Researcher Award 🏆.

Professional Profile 

Suitability For Best Researcher Award – Assist. Prof. Dr. Zahoor shah

Dr. Zahoor Shah exemplifies the ideal profile of a top-tier interdisciplinary researcher. His combination of academic excellence, research innovation, and community leadership positions him as a strong candidate for the Best Researcher Award. With a research impact factor exceeding 103, over 80 international publications, and pioneering work at the intersection of Artificial Intelligence, Fluid Dynamics, and Bio-Mechanics, he brings both depth and breadth to his research agenda. Moreover, his global collaborations and youth empowerment initiatives reflect a commitment to knowledge dissemination beyond academia.

Education 

Dr. Zahoor Shah’s academic journey reflects deep dedication to applied mathematics and computational sciences 📐📊. He earned his Ph.D. in Computational Mathematics from Mohi Ud Din Islamic University, AJ&K, in 2021 🥇, graduating with a Gold Medal 🏅. His thesis focused on the “Design and Applications of Stochastic Numerical Solver for the Solution of Non-Linear Fluidic Systems” 🧪. He also holds a Master of Science in Mathematics from International Islamic University Islamabad (2010) 🎓, where he specialized in Applied Mathematics, Numerical Analysis, ODEs/PDEs, and Mathematical Modeling 🧠. His foundational studies began with a Bachelor of Science in Mathematics from the University of the Punjab, Lahore (2006) 📖. With strong command over programming and simulation tools like Matlab, Mathematica, and Python 💻, Dr. Shah’s academic foundation provides the backbone for his pioneering AI-based research in fluid dynamics and bio-mechanics 🌡️⚙️.

Experience 

Dr. Shah brings over a decade of versatile teaching and research experience 🧑‍🏫📚. He is currently serving as an Assistant Professor at COMSATS University Islamabad (2013–present) 🏛️, where he teaches core mathematics, computational modeling, and AI applications to undergraduate and graduate students 📘👨‍🎓. He has also held academic positions at Allama Iqbal Open University, Federal Urdu University, Foundation University, and International Islamic University Islamabad 📍. Beyond academia, he served as Director at AVT Channels Pvt Ltd (2013–2019) 📺, contributing to public awareness through health and education campaigns. As a member of statutory bodies, registrar committees, and course development teams 🗂️, he has influenced institutional strategy and academic policy. His teaching includes applied mathematics, differential equations, and neural network modeling 🧮, preparing future researchers in the intersection of AI and fluid mechanics 🌊🤖.

Professional Development 

Dr. Zahoor Shah has continually advanced his professional skill set through international fellowships, editorial roles, and youth leadership 🌍📈. He is an alumnus of the Nasser Fellowship for International Youth Leadership in Egypt (2021) 🇪🇬 and represented Pakistan in the International Congress for Youth & Rural Development in Russia (2019) 🇷🇺. His involvement in international conferences has led to global collaborations in Taiwan, China, and the Middle East 🌐. He is a reviewer for prestigious journals like Tribology International, Scientific Reports, and Results in Chemistry 📑, reflecting his academic influence. As Chairman of the National Youth Parliament Pakistan 🏛️, he combines academic leadership with civic engagement. He has supervised multiple Ph.D. and MPhil students 🎓 and contributed to curriculum innovation. With a professional portfolio blending AI expertise, teaching, and public service 🤝, Dr. Shah exemplifies holistic academic growth and leadership.

Research Focus

Dr. Shah’s research focuses on the intersection of Artificial Intelligence (AI) 🤖, Non-Newtonian Fluid Mechanics 🌊, Computational Fluid Dynamics (CFD) 💻, and Bio-mechanics 🧬. His primary goal is to develop AI-enhanced numerical solvers, especially neural networks like the Levenberg–Marquardt algorithm, for solving nonlinear differential equations and simulating complex fluidic phenomena ⚙️. His work has broad applications in biomedical engineering, nanotechnology, environmental fluid flows, and renewable energy systems 🌡️🔋. He is particularly known for his contributions to magneto-nanofluidic models, blood flow modeling, and thermodynamic optimization. These models are applied in industrial, medical, and environmental settings, making his research highly impactful 🌍. With over 80 high-quality publications in leading journals 🧾, his interdisciplinary focus brings innovation to both theoretical and applied sciences, blending mathematical rigor with AI-driven insight 🧠📈. His ongoing projects include bio-convective analysis, entropy generation, and climate-related fluid simulations 🌿.

Research Skills

Dr. Shah’s research skillset is a powerful blend of mathematical modeling 🧮, artificial intelligence 🤖, and computational simulations 🖥️. He specializes in stochastic numerical analysis, designing solvers for nonlinear fluid flow models using neural network algorithms such as Levenberg–Marquardt, Bayesian Regularization, and Nonlinear Autoregressive methods 📉. He has deep expertise in software platforms including Matlab, Mathematica, and Python 🔧, enabling him to simulate highly complex fluid and thermal systems like MHD, Casson, and Eyring-Powell models 🔬. His AI skills are applied to biomedical fluid modeling, pollutant transport, and hybrid nanofluid systems used in emerging technologies 💡. He integrates AI with entropy generation, thermal radiation, bioconvection, and chemical reaction modeling, producing solutions applicable in healthcare, energy, and environmental sectors ⚗️🌡️🌎. His innovative skills in deep learning, supervised/unsupervised computing, and AI-enhanced differential solvers place him at the frontier of scientific computing 🔍📊.

Awards & Honors 

Dr. Zahoor Shah has earned several accolades for his research and leadership contributions 🏅🎓. He was awarded the Gold Medal 🥇 in his Ph.D. for academic excellence in Computational Mathematics. Internationally, he was honored as the Best Diplomat by the Government of Egypt 🇪🇬 for his role in global youth leadership during the Nasser Fellowship. As Chairman of the National Youth Parliament Pakistan 🇵🇰, he has been recognized for combining science with policy advocacy and public engagement 👏. His peer recognition includes appointments as Reviewer for top-tier journals like Tribology International, Scientific Reports, Results in Chemistry, and others 🧾. These roles demonstrate his scholarly influence and standing within the research community 🌍. His research has received consistent citations and commendations, further solidifying his reputation as a high-impact researcher contributing to global scientific development 🌐.

Publication Top Notes

1. Multilayer Deep-Learning Intelligent Computing for the Numerical Analysis of Unsteady Heat and Mass Transfer in MHD Carreau Nanofluid Model
  • Journal: Case Studies in Thermal Engineering

  • Publication Date: Dec 2024

  • DOI: 10.1016/j.csite.2024.105369

  • Authors: Zahoor Shah, Mohammed Alreshoodi, Muhammad Asif Zahoor Raja, Hamza Iqbal, Hamid Qureshi

  • Citation Count: 6

  • Summary:
    This study presents a multi-layer deep learning framework to simulate and analyze unsteady heat and mass transfer in magnetohydrodynamic (MHD) Carreau nanofluids. The intelligent system captures nonlinearities in velocity, temperature, and concentration profiles under external magnetic and thermal influences. The model demonstrates good accuracy and generalization for engineering applications.

2. Machine Learning Investigation for Tri-Magnetized Sutterby Nanofluidic Model with Joule Heating in Agrivoltaics Technology
  • Journal: Nano

  • Publication Date: 30 July 2024

  • DOI: 10.1142/S1793292024500589

  • Authors: Hamid Qureshi, Zahoor Shah, Muhammad Asif Zahoor Raja, Muhammad Shoaib, Waqar Azeem Khan

  • Citation Count: 17

  • Summary:
    This research applies machine learning to model the behavior of a tri-magnetized Sutterby nanofluid influenced by Joule heating, particularly in the context of agrivoltaics systems. The approach blends AI with physical modeling to optimize energy transfer, thermal regulation, and fluid motion in hybrid agricultural–solar energy environments.

3. Numerical analysis of heat and mass transfer in Eyring–Powell fluid employing Python with convective boundary conditions
  • Journal: Case Studies in Thermal Engineering

  • DOI: 10.1016/j.csite.2025.106546

  • Publication Date: September 2025

  • Authors: Chenxu Duan, Muflih Alhazmi, Zahoor Shah, Hamza Iqbal, Maryam Jawaid, Mhassen E.E. Dalam, Mohammed M.A. Almazah

  • Summary:
    This paper presents a numerical study using Python for simulating heat and mass transfer in Eyring–Powell fluids under convective boundary conditions. It emphasizes the impact of fluid properties and external conditions on transport phenomena.

4. Machine learning investigation through Python for thermophoretic deposition with radiation on thermal mass transfer of trihybrid nanofluid across sharp dynamics
  • Journal: International Journal of Geometric Methods in Modern Physics

  • DOI: 10.1142/S0219887825500276

  • Publication Date: June 2025

  • Authors: Hamid Qureshi, Zahoor Shah, Muhammad Asif Zahoor Raja, Waqar Azeem Khan, Yasser Elmasry

  • Summary:
    This study combines Python-based machine learning with thermodynamic modeling to explore thermophoretic deposition and radiative effects on trihybrid nanofluid heat transfer.

5. Artificial neural network model for convectively heated Casson fluid with the appliance of solar energy
  • Journal: International Journal of Geometric Methods in Modern Physics

  • DOI: 10.1142/S0219887825500112

  • Publication Date: May 2025

  • Authors: Hamid Qureshi, Zahoor Shah, Muhammad Asif Zahoor Raja, Waqar Azeem Khan, Mehboob Ali, Yasser Elmasry

  • Summary:
    Introduces an ANN framework for simulating the thermal performance of Casson fluid under convective heating, incorporating solar energy influences.

6. Design of Nonlinear Autoregressive Neuro-Computing Structure for Bioconvective Micropolar Nanofluidic Model
  • Journal: Nano

  • DOI: 10.1142/S1793292024500462

  • Publication Date: April 2025

  • Authors: Zahoor Shah, Attika Jamil, Muhammad Asif Zahoor Raja, Muhammad Shoaib, Adiqa Kausar Kiani

  • Summary:
    Proposes a neuro-computational architecture for solving micropolar nanofluid models with bioconvection effects, using nonlinear autoregressive networks.

Conclusion

Dr. Zahoor Shah’s academic rigor, groundbreaking research in computational modeling, and sustained community impact make him a highly deserving candidate for the Best Researcher Award. His profile demonstrates not only scholarly excellence but also a rare blend of innovation, leadership, and global influence—hallmarks of a truly distinguished researcher.