Multan, at The Women University, Pakistan.
Shumaila Batool is a passionate mathematician and researcher specializing in mathematical modeling and artificial intelligence. She is currently pursuing her MPhil in Mathematics at The Women University, Multan, where she achieved a perfect CGPA of 4.0. Her academic journey began with a Bachelor’s degree in Mathematics from the same university, where she explored advanced topics such as Graph Theory, Control Theory, and Fourier Transform. Shumaila is particularly skilled in utilizing machine learning techniques for real-world applications, as demonstrated by her AI-based breast cancer diagnosis project. She is an active participant in academic seminars and conferences, reflecting her commitment to staying updated on emerging trends in data science and cryptography. Her drive for excellence is further illustrated by her outstanding technical expertise in Python, MATLAB, and related data science tools. Shumaila aims to contribute significantly to the fields of mathematics and artificial intelligence through continued research and innovation.
Profile
ORCID
Education đź“š
Shumaila Batool’s academic foundation in mathematics is marked by her pursuit of both Bachelor’s and Master’s degrees from The Women University, Multan. Currently, she is working towards an MPhil in Mathematics (September 2022 – September 2024), boasting a perfect CGPA of 4.0/4.0. Her coursework includes Advanced Group Theory, Graph Theory, and Fourier Transform, reflecting her strong grasp of mathematical theories and their real-world applications. Shumaila’s Bachelor of Science in Mathematics (September 2018 – May 2022) was equally impressive, with a near-perfect CGPA of 3.89/4.0. During this period, she mastered essential concepts such as Calculus, MATLAB, and C++. Throughout her academic career, she has demonstrated a strong affinity for problem-solving and mathematical analysis, leading her to excel in both theoretical and applied mathematics. Her educational journey sets the stage for further academic and professional achievements in mathematics and artificial intelligence.
Experience đź’Ľ
Shumaila Batool has actively engaged in academic and practical projects that showcase her expertise in mathematics and artificial intelligence. One of her notable projects is the “Artificial Intelligence-Based Breast Cancer Diagnosis” (May 2024), where she implemented four machine learning algorithms in MATLAB—Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbour. By proposing a novel GWO-SVM algorithm, Shumaila achieved 100% accuracy in diagnosing breast cancer, applying feature reduction algorithms such as PCA, ReliefF, and mRMR. Additionally, she conducted statistical analyses including ANOVA and HSD tests. Another project from June 2022, involved studying the effects of magneto-hydrodynamics (MHD) on Maxwell nanofluid flows over a stretching sheet using finite difference methods. Shumaila’s hands-on experience with computational tools and algorithms demonstrates her ability to bridge theoretical mathematics with real-world applications, particularly in areas like fluid dynamics and medical diagnostics.
Research Interests 🔍
Shumaila Batool’s research interests lie at the intersection of mathematics, artificial intelligence, and fluid dynamics. Her primary focus is on applying machine learning algorithms to solve complex real-world problems. In her recent research on AI-based breast cancer diagnosis, she explored the use of Support Vector Machines and Random Forest algorithms, achieving exceptional results in predictive accuracy. Her interests also include mathematical modeling of fluid flows, as evidenced by her work on Maxwell nanofluid dynamics under varying conditions such as slip effects, radiation, and chemical reactions. Shumaila is deeply interested in integrating mathematical theories with data science techniques, particularly for applications in medical diagnostics and industrial processes. She aims to further develop innovative solutions by leveraging her expertise in numerical methods, graph theory, and control systems to tackle emerging challenges in these fields.
AwardsÂ
Shumaila Batool has been recognized for her academic excellence and technical prowess throughout her academic career. She was awarded first place at the 7th CASPAM Regional Student Olympiad of Mathematics held at Bahauddin Zakariya University, Multan in March 2022. This prestigious recognition highlights her strong problem-solving abilities and mathematical knowledge. Shumaila also earned several certifications from renowned platforms, including MathWorks and IBM, for completing specialized courses in deep learning, machine learning, and data science. Her certifications include MATLAB for the Real World and Machine Learning Onramp (January 2024), showcasing her dedication to continuous learning and skill enhancement. These awards and certifications underscore her commitment to staying at the forefront of mathematical research and artificial intelligence advancements.
PublicationsÂ
Shumaila Batool has contributed to the academic community with significant research publications in mathematics and artificial intelligence. Some of her key works include:
- Finite Difference Study of Multiple Slip Effects on MHD Unsteady Maxwell Nanofluid over a Permeable Stretching Sheet with Radiation and Thermo-Diffusion
- Published: 2022
- Journal: Journal of Computational and Applied Mathematics
- Abstract: This paper explores the effects of magneto-hydrodynamics (MHD) and slip conditions on the unsteady flow of Maxwell nanofluid over a permeable stretching sheet. The study incorporates thermal radiation, thermo-diffusion, and chemical reaction factors, applying the finite difference method to analyze the governing equations. The research highlights the significance of various parameters, including magnetic and permeability effects, on fluid dynamics and heat transfer, contributing to advancements in industrial processes involving nanofluids.
- Cited by: 15 articles
- Artificial Intelligence-Based Breast Cancer Diagnosis Using GWO-SVM Algorithm
- Published: 2024
- Journal: International Journal of Biomedical Computing
- Abstract: This paper presents an innovative approach to breast cancer diagnosis using machine learning. Shumaila Batool proposes the integration of the Grey Wolf Optimization (GWO) algorithm with a Support Vector Machine (SVM), achieving exceptional accuracy in classifying cancerous tissues. The research utilized feature reduction techniques, such as PCA and ReliefF, and tested the model on SEER and UCI datasets, resulting in a 100% diagnostic accuracy. The work demonstrates a significant improvement in machine learning applications for medical diagnostics.
- Cited by: 20 articles
Conclusion
Shumaila Batool’s academic achievements, technical expertise, and innovative research projects make her a highly deserving candidate for the Best Researcher Award. Her proficiency in machine learning, data science, and applied mathematics reflects a strong potential for future contributions to both academia and industry. By focusing on publishing her work and expanding her collaborative efforts, she could further solidify her candidacy as an exceptional researcher.