Researcher at Quaid-i-Azam university,Pakistan
Dr. Faiza Tufail is a dedicated researcher in pure mathematics with a strong academic foundation and a focus on fuzzy algebraic structures, rough sets, and decision-making theories. She has authored several impactful SCIE-indexed publications in reputed journals like IEEE Access and Physica Scripta, reflecting both theoretical depth and applied relevance, particularly in renewable energy and machine learning contexts. Her international exposure through research collaboration and a scholarship-supported visit to Ghent University further enhances her global academic profile. Dr. Tufail is also an active peer reviewer for well-known journals, demonstrating her engagement with the broader research community. Her work is distinguished by its originality, interdisciplinary applications, and strong methodological foundations. While she could further strengthen her profile through independent grant leadership and broader academic outreach, her current contributions clearly establish her as a rising and impactful researcher. Overall, she is highly deserving of consideration for the Best Researcher Award.
Professional Profile
Education🎓
Dr. Faiza Tufail possesses a robust academic background in mathematics, marked by consistent excellence and specialization in pure mathematics. She earned her Ph.D. from Quaid-i-Azam University, Islamabad (2019–2024), with part of her research conducted at Ghent University, Belgium, under a prestigious Higher Education Commission (HEC) scholarship. Her doctoral thesis focused on advanced topics such as covering-based rough bipolar fuzzy sets and their applications in decision-making systems. Prior to this, she completed her M.Phil. in Pure Mathematics (2016–2018) at Quaid-i-Azam University, where she explored bipolar fuzzy ideals in ring theory. She also holds an MSc in Mathematics from the University of Gujrat (2014–2016), where her thesis centered on coset diagrams in group theory. Each academic step reflects a deepening of her expertise in both abstract mathematical theory and practical modeling techniques, forming a strong foundation for her impactful research contributions in hybrid algebraic structures and computational decision models.
Professional Experience📝
Dr. Faiza Tufail has developed a strong professional profile through her academic and research roles in the field of mathematics. During her Ph.D. studies at Quaid-i-Azam University, she actively engaged in research projects focused on fuzzy logic, soft sets, and decision-making models, contributing to several high-impact publications. Her international research experience at Ghent University, Belgium, under the HEC’s IRSIP scholarship, provided her with advanced training in data analysis and mathematical modeling. She has collaborated with international researchers, contributing to multidisciplinary projects in and artificial intelligence. Additionally, Dr. Tufail has served as a reviewer for several reputed journals, including IEEE Access, Soft Computing, and Scientific Reports, reflecting her recognition in the academic community. Her technical proficiency with tools such as MATLAB, Python, Mathematica, and Overleaf further supports her research capabilities. Although primarily research-focused, her involvement in seminars and workshops demonstrates her commitment to academic engagement and professional development.
Research Interest🔎
Dr. Faiza Tufail’s research interests lie at the intersection of theoretical mathematics and applied computational models, with a strong emphasis on decision-making systems. Her work primarily focuses on fuzzy algebraic structures, covering-based rough sets, bipolar fuzzy soft sets, and their hybrid generalizations. She is particularly interested in exploring how these abstract mathematical frameworks can be applied to real-world problems, especially in the fields of artificial intelligence, renewable energy optimization, and machine learning. Dr. Tufail has developed innovative multi-criteria decision-making (MCDM) models using techniques like VIKOR, TOPSIS, and PROMETHEE, tailored to address complex evaluation and ranking problems. She is also deeply engaged in studying aggregation operators and pseudo-ordered structures, with applications in intelligent systems. Her interdisciplinary approach combines rigorous mathematical theory with practical implementation, making her research highly relevant for both academic advancement and industrial application. This blend of abstraction and utility defines her ongoing and future research direction.
Award and Honor🏆
Dr. Faiza Tufail has received several notable awards and honors that reflect her academic excellence and research potential. She was awarded a prestigious Ph.D. fellowship from Quaid-i-Azam University, Islamabad, which supported her advanced studies in pure mathematics. Additionally, she earned a highly competitive international research scholarship under the Higher Education Commission’s International Research Support Initiative Program (IRSIP), enabling her to conduct part of her doctoral research at Ghent University in Belgium. This opportunity not only enriched her research experience but also facilitated international collaboration. Earlier in her academic journey, she was recognized with a merit-based laptop under the Prime Minister’s National Laptop Scheme in 2016, awarded for her outstanding academic performance. These accolades highlight her dedication to research and her ability to meet rigorous academic standards. Collectively, these honors underscore Dr. Tufail’s standing as a promising scholar with strong potential for continued contributions to mathematics and interdisciplinary research.
Research Skill🔬
Dr. Faiza Tufail possesses a diverse and advanced set of research skills that enable her to conduct high-level theoretical and applied investigations in mathematics. She is proficient in mathematical modeling, particularly in the areas of fuzzy logic, rough sets, soft computing, and decision-making systems. Her expertise includes designing and analyzing multi-criteria decision-making (MCDM) frameworks, applying advanced techniques such as TOPSIS, PROMETHEE, VIKOR, and WASPAS. Dr. Tufail is skilled in using computational tools including MATLAB, Python, Mathematica, and Overleaf for mathematical simulations, symbolic computations, and documentation. Her ability to integrate abstract mathematical structures with real-world applications, such as energy project evaluations and machine learning models, reflects her analytical thinking and problem-solving capabilities. Additionally, she has experience in peer reviewing for international journals, which enhances her critical evaluation and research assessment skills. These competencies collectively highlight her as a capable and well-rounded researcher in both theoretical and applied mathematical sciences.
Conclusion💡
Dr. Faiza Tufail demonstrates clear excellence in research with high-quality publications, international collaborations, and expertise in mathematical modeling with real-world applications. Her profile strongly supports her candidacy for the Best Researcher Award, especially within the early-to-mid career bracket.
While there is room for growth in areas like grant leadership and academic service, her accomplishments so far are noteworthy and competitive, especially considering the technical depth and novelty of her work.
Publications Top Noted✍
1. Title: An Enhanced Machine Learning Covering-Based Bipolar L-Fuzzy Rough Set PROMETHEE Model for Battery Storage Systems in Renewable Energy
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Authors: Faiza Tufail, Rizwan Gul, Muhammad Shabir, Samaher Khalaf Alharbi, Hamiden Abd El-Wahed Khalifa
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Journal: Expert Systems with Applications
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Year: 2025
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DOI: 10.1016/j.eswa.2025.127951
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Citations: As of now, this article has not been cited.
2. Title: The novel WASPAS method for roughness of bipolar fuzzy sets based bipolar fuzzy covering
3. Title: A Comparison of Promethee and TOPSIS Techniques Based on Bipolar Soft Covering-Based Rough Sets
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Authors: Faiza Tufail, Muhammad Shabir, El-Sayed A. Abo-Tabl
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Journal: IEEE Access
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Year: 2022
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DOI: 10.1109/ACCESS.2022.3161470
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Citations: This article has been cited in subsequent research.
