Subhan Ullah | Applied Mathematics | Best Researcher Award

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Dr. Subhan Ullah | Applied Mathematics | Best Researcher Award

Teacher at University of Malakand, Pakistan

Dr. Subhan Ullah is a dedicated Pakistani researcher in applied mathematics, specializing in fluid mechanics 🌊, nanofluids 🔬, and epidemic modeling 🦠. With a Ph.D. from the University of Malakand, his research on Jeffery-Hamel flows and thermodynamic analyses in convergent/divergent channels demonstrates a commitment to solving real-world engineering challenges 🔧. Dr. Ullah’s collaborative publications in reputable journals reflect his strong team-oriented approach 🤝. As a lecturer and mentor, he inspires students at various educational levels 📚. He is passionate about research and education, aiming to contribute both academically and practically. To elevate his candidacy for top-tier awards 🏆, Dr. Ullah can further strengthen his international visibility, leadership in research, and innovation, ensuring a lasting impact in the global mathematics community 🌍.

Professional Profile 

Education 🎓

Dr. Subhan Ullah’s academic journey is deeply rooted in mathematics, marked by his Ph.D. from the University of Malakand (2020–2023) with a dissertation on heat transfer in Jeffery-Hamel flows 🌊. He earned an M.S. in Mathematics (2012–2014) from Bacha Khan University, exploring the dynamics of epidemic diseases 🦠, and an M.Sc. (2009–2011) from the University of Malakand. His educational foundation was laid through a B.Sc. (2005–2007) and earlier schooling at Government Centennial Model High School Timergara. This solid academic progression showcases his commitment to mathematical sciences 📐, equipping him with advanced theoretical and analytical skills essential for tackling complex fluid dynamics, mathematical biology, and other applied mathematics challenges.

Professional Experience 💼

Dr. Subhan Ullah is an accomplished academician with extensive teaching and research experience. He currently serves as a full-time researcher at the University of Malakand, focusing on applied mathematics and interdisciplinary projects 🤝. His earlier roles as a Lecturer at Bukhara College of Science & Technology and The Educator School & College Timergara highlight his dedication to educating undergraduate and postgraduate students 📚. Additionally, he has contributed significantly as a government school teacher, nurturing young minds and fostering a positive learning environment. Throughout his career, Dr. Ullah has consistently designed innovative curricula, organized seminars, and mentored students, reflecting his passion for advancing mathematics education and research excellence in Pakistan and beyond 🇵🇰.

Research Interest 🔍

Dr. Subhan Ullah’s research interests span fluid mechanics 🌊, with a focus on nanofluids 🔬 and fluid flows in convergent/divergent channels, where he explores complex heat transfer and thermodynamic phenomena. His passion extends to mathematical biology, particularly population dynamics, epidemic dynamics, and infectious disease modeling 🦠, reflecting a multidisciplinary approach to real-world problems. His enthusiasm for applied mathematics drives him to investigate diverse research challenges, recognizing its versatile role in addressing engineering, environmental, and biological systems 🌍. This dynamic research portfolio positions Dr. Ullah at the forefront of mathematical modeling, contributing valuable insights and practical solutions to contemporary scientific and industrial challenges 🚀.

Awards and Honors 🏅

Dr. Subhan Ullah has demonstrated notable achievements in research and academia, earning recognition through impactful publications and conference presentations. His research contributions to high-impact journals—such as Physics Letters A, Chaos, Solitons & Fractals, and the International Journal of Energy Research—underscore his commitment to excellence 📈. He has actively participated in academic conferences, including the International Conference “Mathematical Sciences” at the University of Malakand, sharing his innovative research with the global scientific community 🌐. These accomplishments reflect his dedication to advancing mathematical sciences and position him as a deserving candidate for prestigious research awards that celebrate innovation, impact, and leadership in applied mathematics.

Research Skills 🧪

Dr. Subhan Ullah possesses a robust research skillset encompassing mathematical modeling, computational simulations, and theoretical analysis of fluid dynamics and nanofluid flows 🔬. His proficiency in tools like MATLAB, Mathematica, LaTeX, and LYX empowers him to tackle complex differential equations and thermodynamic problems efficiently 💻. He is adept at interdisciplinary collaboration, contributing to projects that intersect engineering, physics, and biological systems 🤝. His skills extend to mentoring undergraduate and graduate researchers, guiding them in research design, data analysis, and academic writing ✍️. These capabilities collectively enable Dr. Ullah to produce high-quality research that bridges theory and practical application, reinforcing his status as a leading researcher in applied mathematics.

Publications Top Notes

Title:
“Heat transfer augmentation of Jeffery–Hamel hybrid nanofluid in a stretching convergent/divergent channel through porous medium.”

Authors:
S. Ullah, Subhan; H.A.S. Ghazwani, Hassan Ali S.; D.N. Khan, Dolat N.; Z.A. Khan, Zareen Abdulhameed.

Year:
2025.

Citation:
S. Ullah, Subhan, H.A.S. Ghazwani, Hassan Ali S., D.N. Khan, Dolat N., and Z.A. Khan, Zareen Abdulhameed (2025). “Heat transfer augmentation of Jeffery–Hamel hybrid nanofluid in a stretching convergent/divergent channel through porous medium.” AIMS Mathematics.

Source:
AIMS Mathematics (2025). Link currently unavailable.

Conclusion 📌

Dr. Subhan Ullah stands out as a highly motivated researcher with a strong academic foundation, extensive teaching experience, and a dynamic research portfolio 📚. His contributions to fluid mechanics, nanofluids, and epidemic modeling underscore his commitment to tackling real-world challenges through applied mathematics 🌍. While his achievements in research and publication are commendable, further strengthening his international collaborations, leading research projects, and securing competitive funding would enhance his candidacy for prestigious awards 🏆. Dr. Ullah’s passion for education, interdisciplinary research, and mentorship ensures that he will continue making impactful contributions to the mathematical sciences community, both in Pakistan and globally, fostering innovation and academic excellence 🚀.

Halima Bensmail | Applied Mathematics | Best Researcher Award

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Prof. Dr. Halima Bensmail | Applied Mathematics | Best Researcher Award

Principal scientist at Qatar Computing Research Institute, Qatar

Dr. Halima Bensmail is a distinguished Principal Scientist at the Qatar Computing Research Institute, specializing in machine learning, bioinformatics, biostatistics, and statistical modeling. With a Ph.D. in Statistics (Summa Cum Laude) from the University Pierre & Marie Curie, she has made significant contributions to Bayesian inference, multivariate analysis, and precision medicine. She has an impressive research record with an H-index of 31, i10-index of 54, and around 140 publications in prestigious journals such as Nature Communications, JASA, and IEEE TNNLS. As the founder of the Statistical Machine Learning and Bioinformatics group at QCRI, she has led groundbreaking projects, including the development of open-source data-driven tools like the PRISQ pre-diabetes screening model and MCLUST clustering algorithm. With extensive academic experience in the USA, France, and the Netherlands, she has mentored numerous postdocs and students, shaping the next generation of researchers. Her expertise and leadership make her a key figure in data science and precision health.

Professional Profile 

Google Scholar
Scopus Profile

Education

Dr. Halima Bensmail holds a Ph.D. in Statistical Machine Learning (Summa Cum Laude) from the University Pierre & Marie Curie (Paris 6), where she specialized in Bayesian inference, spectral decomposition, and mixture models. Her thesis focused on deterministic and Bayesian model-based clustering and classification for data science applications. Prior to that, she earned an M.S. in Machine Learning from the same university, with a focus on probability, financial modeling, and stochastic processes. She also holds a Bachelor’s degree in Applied Mathematics and Statistics from the University Mohammed V in Morocco, where she gained expertise in numerical analysis, stochastic processes, topology, and mathematical programming. Throughout her academic journey, she was mentored by esteemed professors and developed a strong foundation in theoretical and applied statistics. Her educational background has laid the groundwork for her pioneering research in machine learning, bioinformatics, and data-driven modeling for real-world applications.

Professional Experience

Dr. Bensmail is currently a Principal Scientist at the Qatar Computing Research Institute (QCRI), where she leads research in bioinformatics, statistical machine learning, and artificial intelligence. She also serves as a Full Professor in the College of Science and Engineering at Hamad Bin Khalifa University and a Visiting Full Professor at Texas A&M University at Qatar. Previously, she held tenured faculty positions at Virginia Medical School and the University of Tennessee, where she contributed significantly to public health and business administration research. She has also worked as a Research Scientist at the University of Leiden, a scientist at the Fred Hutchinson Cancer Research Center, and a postdoctoral researcher at the University of Washington. With decades of experience across academia and research institutions in the U.S., Europe, and the Middle East, she has built expertise in developing statistical and AI-driven solutions for biomedical and computational challenges.

Research Interests

Dr. Bensmail’s research spans statistical machine learning, bioinformatics, and precision medicine. She has developed novel clustering algorithms, such as an advanced Bayesian clustering model implemented in the MCLUST package, and statistical methods for analyzing Next-Generation Sequencing (NGS) data. She is also interested in computational biology, specifically protein-protein interactions, protein solubility, and structural biology. Her work includes dimensionality reduction techniques like nonnegative matrix factorization and discriminative sparse coding for domain adaptation. In the field of precision medicine, she has designed PRISQ, a statistical model for pre-diabetes screening. Her broader interests include Bayesian statistics, functional data analysis, information theory, and high-dimensional data modeling. With a strong focus on developing real-world data-driven tools, she actively contributes to statistical methodologies that enhance decision-making in medicine, genomics, and artificial intelligence applications.

Awards and Honors

Dr. Bensmail has received numerous accolades for her contributions to machine learning, bioinformatics, and statistical modeling. Her work has been widely recognized, with over 140 peer-reviewed publications and an H-index of 31, demonstrating the impact of her research. She has secured research grants and led major projects in AI-driven healthcare solutions. Her contributions to the field have been acknowledged through invitations to serve as a keynote speaker at international awards and as an editorial board member for high-impact journals. She has also been instrumental in mentoring young researchers, postdoctoral fellows, and doctoral students, fostering the next generation of scientists in AI, statistics, and bioinformatics. Additionally, her work on statistical methods for precision medicine and biomedical informatics has gained international recognition, positioning her as a leading expert in the field of data science for healthcare and computational biology.

Conclusion

Dr. Halima Bensmail is a pioneering researcher in machine learning, statistical modeling, and bioinformatics, with a career spanning leading institutions in the U.S., Europe, and the Middle East. Her contributions to clustering algorithms, high-dimensional data analysis, and precision medicine have made a lasting impact on the fields of AI and computational biology. As a mentor and leader, she has shaped numerous young scientists and postdocs, driving innovation in data science applications. With a robust publication record, influential research projects, and a dedication to developing real-world AI-driven solutions, she stands as a leading figure in statistical machine learning. Her expertise and contributions continue to push the boundaries of knowledge in bioinformatics, artificial intelligence, and healthcare analytics, making her a strong candidate for prestigious research awards and recognition in scientific communities worldwide.

Publications Top Noted