Saba Inam | Mathematics | Best Researcher Award

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Dr. Saba Inam | Mathematics | Best Researcher Award

Lecturer at Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan

Dr. Saba Inam is a dedicated academician and researcher in the field of mathematics, with a strong emphasis on cryptography, image encryption, and machine learning. Currently serving as a lecturer, she has contributed extensively to the research ecosystem through her innovative projects, scholarly publications, and supervision of numerous theses at various levels. Her work bridges theoretical mathematics with modern digital security challenges.

Profile

Google Scholar | ORCID | Scopus

Best Researcher Award

Dr. Saba Inam is a highly suitable candidate for the “Best Researcher Award” owing to her consistent research excellence in cryptography, blockchain, and image encryption. Her work reflects a strong interdisciplinary approach, integrating mathematics with advanced technologies such as quantum encryption and AI. The volume, quality, and international impact of her publications, alongside her active engagement in funded projects and academic leadership, make her an exemplary choice for this recognition.

Education

Dr. Inam holds a Ph.D. in Mathematics from Capital University of Science and Technology (2019), an MS in Mathematics from COMSATS Institute of Information Technology (2007), and an M.Sc. in Mathematics from Quaid-i-Azam University (2005). Her educational background is marked by academic distinction and scholarships at each stage, underlining her early and continued dedication to the mathematical sciences.

Experience

Dr. Inam has been a Lecturer in Mathematics at Fatima Jinnah Women University since 2007, with leadership experience as the department Incharge from 2016 to 2018. Additionally, she served as a Research Associate at COMSATS Institute of Information Technology. She has taught courses at Ph.D., MPhil, and undergraduate levels and has supervised over 60 theses collectively across academic levels.

Research Interest

Her research interests include algebraic cryptography, cryptology, quantum encryption, image encryption, blockchain, IoT, deep learning, and fluid mechanics. She is particularly focused on developing secure and innovative encryption schemes for sensitive digital environments such as healthcare and satellite data transmission.

Publication

Dr. Saba Inam has published extensively in high-impact journals.

  • 2025: “Securing face images in UAV networks using chaos and DNA cryptography” – Scientific Reports.

  • 2025: “A novel image encryption scheme based on elliptic curves” – The European Physical Journal Plus.

  • 2025: “A Blockchain-Integrated Chaotic Fractal Encryption Scheme” – Scientific Reports.

  • 2025: “Blockchain-driven medical image encryption using chaotic tent map” – Scientific Reports.

Aychew Wondyfraw | Mathematics | Best Academic Researcher Award

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Mr. Aychew Wondyfraw | Mathematics | Best Academic Researcher Award

Researcher at Haramaya University, Ethiopia

Aychew Wondyfraw Tesfaye is an Ethiopian academic and researcher, currently serving as a lecturer and researcher in the Department of Mathematics at Haramaya University, Ethiopia. With a strong academic background, including an MSc in Mathematical Modeling from Haramaya University, Aychew is deeply engaged in the study and application of mathematical modeling techniques, focusing on areas such as stochastic models, disease dynamics, and corruption transmission dynamics. His work has contributed significantly to the understanding of various complex systems through mathematical approaches.

Profile

Orcid

Education

Aychew’s educational journey began with a Bachelor of Science (BSc) in Mathematics from Haramaya University, which he completed between 2015 and 2017. His academic pursuit continued with a Master of Science (MSc) in Mathematical Modeling at Haramaya University, which he completed in 2021. He further expanded his knowledge with a Higher Diploma in Teaching Methodology in 2022. In addition to his formal education, Aychew has participated in various training programs to strengthen his expertise, including courses on cloud computing, MATLAB, data science, and statistical data management.

Experience

Since 2019, Aychew has been a lecturer and researcher in the Department of Mathematics at Haramaya University. His role involves teaching undergraduate and graduate courses, conducting research, and coordinating the university’s Freshman Program since 2022. He has developed a keen interest in mathematical modeling and its applications in real-world problems. His responsibilities also extend to mentoring students and leading academic workshops, further contributing to the growth of mathematical sciences at Haramaya University.

Research Interests

Aychew’s research interests are primarily centered around mathematical modeling, focusing on stochastic processes, disease dynamics, and corruption transmission. His work explores the application of mathematical models to understand the spread of diseases such as COVID-19 and cholera, as well as social phenomena like corruption. His research methodology often combines stochastic and deterministic models to analyze complex systems, contributing to fields such as public health, social sciences, and applied mathematics.

Awards

Throughout his academic career, Aychew has been recognized for his contributions to mathematical modeling and research. His participation in various training programs and conferences has allowed him to expand his knowledge and network within the mathematical community. Additionally, he has been involved in presenting his research at significant academic platforms, such as the Ethiopian Mathematics Professionals Association Annual Conference, where he showcased his work on disease dynamics and corruption modeling.

Publications

Aychew has published several important papers, with a focus on stochastic modeling and its applications in disease dynamics and social issues. His notable publications include:

Tesfaye, A.W., Tolasa, T.M., Cheri, E.H. & Mekonen, T.M., 2025. “Modeling, Analyzing, and Simulating the Dynamics of Racism Using a Stochastic Dynamical System.” Abstract and Applied Analysis, 2025(1), 2472412. Cited by: 20.

Tesfaye, A.W. & Alemneh, H.T., 2023. “Analysis of a Stochastic Model of Corruption Transmission Dynamics with Temporary Immunity.” Heliyon, 9(1). Cited by: 15.

Tesfaye, A.W. & Satana, T.S., 2021. “Stochastic Model of the Transmission Dynamics of COVID-19 Pandemic.” Advances in Difference Equations, 2021, pp.1-21. Cited by: 50.

Tilahun, G.T., Woldegerima, W.A. & Wondifraw, A., 2020. “Stochastic and Deterministic Mathematical Model of Cholera Disease Dynamics with Direct Transmission.” Advances in Difference Equations, 2020(1), pp.1-23. Cited by: 35.

Conclusion

Aychew Wondyfraw Tesfaye is an accomplished academic and researcher whose contributions to mathematical modeling are shaping the understanding of disease transmission and social dynamics in Ethiopia and beyond. His continuous involvement in education, research, and academic leadership at Haramaya University underscores his commitment to advancing the field of mathematics. Aychew’s work continues to inspire and drive innovation in mathematical modeling, offering valuable insights into real-world challenges.

Maedeh GholamAzad | Mathematics | Best Researcher Award

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Dr. Maedeh GholamAzad | Mathematics | Best Researcher Award

Postdoctoral Researcher at University of Kurdistan, Iran

Dr. Maedeh Gholam Azad is a distinguished postdoctoral researcher at the University of Kurdistan, specializing in optimization model design with a focus on operations research and data envelopment analysis (DEA). With a strong foundation in artificial intelligence (AI), she has contributed significantly to various domains, including supply chain management, healthcare, and environmental sustainability. Her research aims to develop intelligent methodologies that integrate AI with optimization techniques to improve decision-making and efficiency in complex systems. Passionate about innovation, she continuously explores new approaches to tackling contemporary challenges through data-driven solutions.

Profile

Scopus

Education

Dr. Gholam Azad earned her doctorate in operations research, where she concentrated on data envelopment analysis and mathematical modeling to enhance industrial and environmental efficiencies. Her academic journey provided her with extensive knowledge in AI applications for optimization and sustainable decision-making. Throughout her studies, she actively engaged in interdisciplinary research, bridging the gap between computational intelligence and real-world problem-solving. Her commitment to academic excellence and research rigor has established her as a respected scholar in her field.

Experience

With extensive experience in research and academia, Dr. Gholam Azad has undertaken multiple projects that integrate AI with optimization techniques. She has worked on evaluating the environmental impact of industrial production using DEA networks, optimizing supplier selection in the petrochemical industry through hybrid AI approaches, and applying machine learning to healthcare analytics. Beyond academia, she has collaborated with industry partners, including the petrochemical sector and educational institutions, to implement data-driven decision-support systems. Her editorial role at REA Publications further highlights her contributions to advancing research dissemination in AI and optimization.

Research Interests

Dr. Gholam Azad’s research interests lie at the intersection of AI and sustainable supply chain management, healthcare optimization, logistics, and transportation. She focuses on designing mathematical models that enhance efficiency and sustainability in various industries. Her expertise in machine learning, big data analytics, and stochastic modeling enables her to develop intelligent frameworks that address real-world challenges. She is particularly interested in leveraging AI for predictive analytics, scalable optimization, and automated decision-making in industrial applications.

Awards

Dr. Gholam Azad has been recognized for her contributions to research and innovation in AI-driven optimization. Her work has received accolades from academic societies and industry partners, particularly for her advancements in sustainable supply chain management. She has been an active member of professional organizations such as the Iranian Operations Research Society and the Iranian Data Envelopment Analysis Society, which further validates her influence in the field.

Publications

“Proposing a new integrated MEREC-NDEA algorithm for assessing and selecting the optimal sustainable suppliers: A case study,” International Transactions in Operational Research, 2024.

“Performance evaluation of rapeseed producers in Iran using the W-DEA technique,” Quarterly Journal of Agricultural Economics and Development, 2024.

“Assessing the effect of industrial products on air pollution in Iran: A novel NDEA approach considering undesirable outputs,” Environment, Development and Sustainability, 2024.

“Determination of disease risk factors using binary data envelopment analysis and logistic regression analysis, case study: a stroke risk factors,” Journal of Modelling in Management, 2023.

“Predicting Stroke Risk Based on Clinical Symptoms Using the Logistic Regression Method,” International Journal of Industrial Mathematics, 2022.

“Data envelopment analysis using binary data,” Journal of Modelling in Management, 2021.

“Hybrid method of logistic regression and DEA (Case study: Stroke),” Iranian Journal of Operation Research, 2021.

Conclusion

Dr. Maedeh Gholam Azad’s extensive expertise in AI-driven optimization and data envelopment analysis has positioned her as a leading researcher in her field. Her contributions to sustainable supply chain management, healthcare analytics, and industrial efficiency have been widely recognized. Through her interdisciplinary research, she has successfully integrated mathematical modeling with AI methodologies to develop innovative solutions for complex challenges. As a dedicated scholar and researcher, she continues to push the boundaries of optimization and artificial intelligence to foster sustainability and operational excellence in diverse industries.