Ahlam H.Tolba | Diseases | Women Researcher Award

Prof.Ahlam H.Tolba | Diseases | Women Researcher Award

Mathematical Statistics at Mansoura University, Egypt

Dr. Ahlam H. Tolba is an Associate Professor of Mathematical Statistics at the Faculty of Science, Mansoura University, Egypt. Born in Talya, Al Minufiyah, she has excelled in the field of statistical modeling and reliability theory. With over a decade of academic experience, she has significantly contributed to mathematical research and education, particularly in stochastic processes, competing risks models, and advanced distribution theory. Dr. Tolba is an active member of several scientific associations and serves as a peer reviewer and editorial board member for numerous international journals. She has supervised multiple postgraduate theses and student research projects and has a prolific publication record with over 35 peer-reviewed papers in high-impact journals. Beyond academia, she engages in international workshops and seminars, strengthening her global presence in the field of applied mathematics and statistics.

Professional Profiles

Education

Dr. Ahlam H. Tolba earned all her academic degrees from Mansoura University, Egypt. She completed her Ph.D. in Mathematical Statistics with a thesis on “Statistical Inference for Some Reliability Models.” Prior to that, she obtained her Master’s degree with a thesis focusing on random differential equations and mean square calculus applications. She graduated with a Bachelor’s degree in Statistical and Computer Science, showcasing early proficiency in statistical theory and computational tools. Her education laid a strong foundation for her expertise in statistical modeling, stochastic processes, and reliability analysis. She has also undertaken numerous professional development courses through the Faculty Leadership Development Program (FLDP), covering a broad spectrum of teaching, research, leadership, and academic planning strategies. Her consistent academic progression reflects her dedication to continuous learning and academic excellence.

Professional Experience

Dr. Tolba began her academic journey as a Demonstrator at Mansoura University in 2009, progressing to Assistant Lecturer , and later Assistant Professor . Since January 2024, she has held the title of Associate Professor of Mathematical Statistics. She has taught and upgraded undergraduate and postgraduate courses such as Stochastic Processes, Reliability Theory, and Probability Theory. She has supervised Ph.D. and Master’s theses, alongside several student graduation projects involving statistical programming. Dr. Tolba actively contributes to Mansoura University’s quality assurance, electronic exams, and digital learning platforms. Her administrative and academic experiences are complemented by involvement in international seminars, quality assurance workshops, and conferences. She also serves as an academic advisor and a reviewer/editor for numerous scientific journals. Her career reflects a strong commitment to research, education, student mentoring, and institutional development.

Awards & Honors

While specific named awards were not listed, Dr. Ahlam Tolba’s recognition is evident in her significant roles across academia and research. She is an editorial board member for prestigious international journals like the Journal of Mathematical Techniques and Computational Mathematics, and a volunteer reviewer for MDPI journals such as Symmetry, Sustainability, and Mathematics. Her invited talks, conference presentations, and leadership roles in organizing national and international conferences further reflect her high standing in the mathematical statistics community. Her continuous promotion through academic ranks—culminating in her Associate Professorship in 2024—demonstrates institutional trust and professional respect. Additionally, her participation in elite programs such as Nature Research Academies workshops (e.g., Research Paper Writing, Grant Writing) and her repeated involvement in Egypt Knowledge Bank (EKB) events show national-level acknowledgment of her research expertise and educational impact.

Research Focus

Dr. Tolba’s research is deeply rooted in reliability theory, statistical inference, and survival analysis. She specializes in developing and analyzing new statistical distributions and shock models, with applications in engineering, medicine, and environmental sciences. Her focus areas include competing risks models, progressive censoring, masked data, and multivariate lifetime data. She employs both classical and Bayesian methodologies in her inference work. Notably, her research often intersects with bridge reliability, stress-strength models, and cancer survival analysis. She actively collaborates on projects involving bivariate and multivariate distributions, generalized data structures, and life-testing experiments. Her publication record includes applications to real-world datasets—ranging from industrial systems to medical data—making her contributions both theoretical and applied. Dr. Tolba is also interested in simulation studies, algorithm development for distributional analysis, and statistical computing using R, Python, and MATLAB.

Skills 

Dr. Ahlam H. Tolba possesses a diverse skill set in statistical computing, programming, teaching, and academic supervision. She is proficient in R, Python, SPSS, MINITAB, Maple, MATLAB, Q-Basic, and C++, reflecting her strong computational foundation. In research, she excels in Bayesian and classical estimation, life data analysis, reliability modeling, and simulation studies. She has guided students in practical projects using statistical software and tools. In teaching, she has upgraded and delivered various courses, including Stochastic Processes, Reliability Theory, and Time Series Analysis. Her training also includes quality assurance, strategic planning, scientific publishing, crisis management, and digital transformation. Her leadership and communication skills are evidenced by her role as an academic advisor and workshop facilitator. She is also adept at curriculum development, electronic exam creation, and research grant preparation, making her an all-rounded academic professional.

Publications Top Notes

  1. Title: Modelling the COVID‐19 Mortality Rate with a New Versatile Modification of the Log‐Logistic Distribution
    Authors: AH Muse, AH Tolba, E Fayad, OA Abu Ali, M Nagy, M Yusuf
    Citations: 54
    Year: 2021

  2. Title: An Extended Cosine Generalized Family of Distributions for Reliability Modeling: Characteristics and Applications with Simulation Study
    Authors: Z Mahmood, TM Jawa, N Sayed-Ahmed, EM Khalil, AH Muse, AH Tolba
    Citations: 39
    Year: 2022

  3. Title: New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates
    Authors: EQ Chinedu, QC Chukwudum, N Alsadat, OJ Obulezi, EM Almetwally, AH Tolba
    Citations: 31
    Year: 2023

  4. Title: A Unit Half-Logistic Geometric Distribution and Its Application in Insurance
    Authors: AT Ramadan, AH Tolba, BS El-Desouky
    Citations: 31
    Year: 2022

  5. Title: Bayesian and Non-Bayesian Estimation Methods for Simulating the Parameter of the Akshaya Distribution
    Authors: A Tolba
    Citations: 28
    Year: 2022

  6. Title: A New Distribution for Modeling Data with Increasing Hazard Rate: A Case of COVID-19 Pandemic and Vinyl Chloride Data
    Authors: AH Tolba, CK Onyekwere, AR El-Saeed, N Alsadat, H Alohali, OJ Obulezi
    Citations: 24
    Year: 2023

Conclusion

Nadeem Zaidkilani | Biotechnology | Best Zoology Research Award

Mr. Nadeem Zaidkilani | Biotechnology | Best Research Award

  PhD Researcher In AI at Rovira I Virgili University, Palestine

Nadeem Zaidkilani is a Palestinian computer science and software engineering professional with extensive experience in business analysis, software design, and quality assurance. He obtained his bachelor’s degree in Computer Science from Birzeit University in 2005 and later pursued a master’s in Software Engineering from the same institution in 2019. Over the years, he has worked in various roles, including Senior Application Specialist at Paltel and Text Mining Engineer, contributing to the enhancement of electronic systems, business portals, and document management solutions. His expertise extends to deep learning, image processing, computer vision, and natural language processing (NLP). Currently, he is pursuing a Ph.D. in Computer Engineering and Mathematics at URV University, Spain, focusing on medical image analysis using artificial intelligence. With strong programming skills in Python, Java, and C++, Nadeem continues to explore AI-driven solutions for healthcare and other domains, leveraging advanced technologies for innovative problem-solving.

Professional Profiles📖

Scopus

Education 🎓

  • Bachelor’s Degree in Computer Science (2005) – Birzeit University 🏅
    Nadeem’s undergraduate studies laid the foundation for his expertise in programming, database management, and software development. He gained proficiency in Java, C++, and web technologies, leading to early career opportunities in software engineering.

  • Master’s Degree in Software Engineering (2019) – Birzeit University 🎖️
    His master’s research focused on automatic classification of app reviews for requirements engineering, specifically analyzing user needs for healthcare applications. He mastered agile methodologies, system architecture, and business process modeling.

  • Ph.D. in Computer Engineering & Mathematics (Ongoing) – URV University, Spain 🎓
    Currently, Nadeem is researching computer vision and deep learning for medical image analysis, employing AI-based techniques to enhance diagnostics. His work integrates advanced machine learning, convolutional neural networks (CNNs), and medical imaging technologies to improve healthcare solutions.

Work Experience💼

  • Part-Time Lecturer (2024–Present) – Al-Zaytoonah University of Science and Technology 🎤
    Teaching Python, C++, and HCI, focusing on Agile and Scrum methodologies for UI/UX design.

  • Text Mining Engineer (2023–2024) 🔍
    Developed a biomedical literature classification system using Python, MySQL, INDRA, and PubMed, enhancing researcher workflows.

  • Senior Application Specialist (2012–2022) – Paltel 📡
    Managed portals, electronic payment systems, document management, and vendor systems to optimize business operations.

  • Senior Software Developer (2009–2012) – Hulul Company 💻
    Led the development of donor management and archiving systems, using JEE, Struts 2, and JavaScript.

  • IT Manager (2007–2009) – Ministry of Finance 📊
    Supervised IT projects, project timelines, and reporting structures.

  • Junior Developer (2005–2007) – Palestinian Authority Tax System 💾
    Contributed to tax management software using J2EE, XML, and Oracle 10g.

Awards and Honors 🏆

  • Scholarship for Ph.D. Studies – Received a merit-based scholarship at URV University, Spain, for his research in AI-driven medical image analysis.
  • Best Master’s Research Award – Recognized for his Automatic Classification of App Reviews for Requirements Engineering, focusing on user needs in healthcare applications.
  • AI Research Grant – Secured funding for text mining in biomedical research, supporting advancements in NLP and knowledge extraction.
  • Outstanding Contribution Award (Paltel, 2020) – Honored for enhancing Paltel’s electronic systems, particularly in E-Pay, EDMS, and Business Portals.
  •  Top Software Engineer Recognition – Acknowledged by Hulul Company for leading the development of high-impact enterprise applications.

Skills 💡

  • Nadeem Zaidkilani possesses a diverse and extensive technical skill set, making him proficient in various aspects of software engineering, artificial intelligence, and research. He is well-versed in programming languages such as Python 🐍, Java ☕, C++ 🚀, and JavaScript 🌐, allowing him to develop robust applications across multiple domains. His expertise in machine learning and AI includes frameworks like TensorFlow 🤖, Keras 🧠, PyTorch 🔥, and OpenCV 👀, enabling him to implement deep learning models for image processing and AI-driven applications.
  • In the field of data science and natural language processing (NLP), Nadeem utilizes Scikit-learn 📈, Pandas 🐼, NLTK 🗣️, and SpaCy 🧩 for analyzing datasets, extracting insights, and automating text processing. His software development expertise spans JEE 🌍, Struts 2 🏗️, Hibernate 🏛️, and Spring Boot 🌱, allowing him to build scalable enterprise applications. Additionally, he has hands-on experience in database management, using MySQL 🗄️, PostgreSQL 🛢️, and Oracle DB 🔗 for efficient data storage and retrieval.
  • As an advocate of Agile and Scrum methodologies, Nadeem integrates Jira 📋, Confluence 📑, and Kanban 🚦 to streamline project management and ensure efficient team collaboration. His knowledge in cloud and DevOps technologies includes Docker 🐳, Kubernetes ☁️, and GitHub Actions 🔄, facilitating automated deployment and scalable infrastructure. Moreover, he leverages scientific research tools such as PubMed 🏥, INDRA 🔬, and LaTeX 📖 to support his research in biomedical AI and text mining, further strengthening his role as a technology-driven researcher and innovator. 🚀

Research Focus 🔬

  • Nadeem Zaidkilani’s research focuses on the intersection of computer vision, deep learning, and artificial intelligence (AI) in medical imaging, aiming to develop innovative solutions for healthcare and technology-driven applications. His expertise in medical image analysis enables him to build deep learning-based diagnostic tools for detecting anomalies in MRI, CT, and X-ray images, improving early disease detection and patient outcomes. Additionally, he applies natural language processing (NLP) techniques to biomedical literature, leveraging text mining to extract and classify critical health-related insights, which aids in medical research and decision-making.
  • In the realm of deep learning and AI, Nadeem implements convolutional neural networks (CNNs) and transformer-based models for image segmentation, feature extraction, and classification, enhancing the accuracy and efficiency of automated diagnostic systems. His work in E-health applications focuses on integrating AI-driven solutions into healthcare systems, enabling automated diagnostics and decision support for medical practitioners.
  • Beyond healthcare, Nadeem’s expertise extends to software engineering and business analysis, where he integrates AI technologies into enterprise systems, E-Services, EDMS (Electronic Document Management Systems), and fintech solutions. His research contributes to the development of intelligent, data-driven applications that bridge the gap between AI, healthcare, and enterprise automation, driving innovation in both the medical and technological domains

Conclusion✅

Nadeem Zaidkilani is a strong contender for the Best Researcher Award due to his multi-disciplinary expertise in AI, computer vision, and biomedical informatics. His work in deep learning for medical imaging and text mining for biomedical applications highlights his innovative approach to solving real-world challenges. Enhancing publication output and interdisciplinary collaborations will further solidify his position as a leading researcher in his domain.

Publications Top Notes📚

  • “CoAtUNet: A Symmetric Encoder-Decoder with Hybrid Transformers for Semantic Segmentation of Breast Ultrasound Images”

    • Authors: N. Zaidkilani, M.Á. García, D.S. Puig
    • Journal: Neurocomputing
    • Year: 2025
    • Citations: 0
  • “Arabic Topic Classification Corpus of the Nakba Short Stories”

    • Authors: O. Hamed, N. Zaidkilani
    • Conference: Proceedings of the First International Workshop on Nakba Narratives as Language Resources
    • Year: 2025
    • Citations: Not specified
  • “Exploring Author Style in Nakba Short Stories: A Comparative Study of Transformer-Based Models”

    • Authors: O. Hamed, N. Zaidkilani
    • Conference: Proceedings of the First International Workshop on Nakba Narratives as Language Resources
    • Year: 2025
    • Citations: Not specified