Rafita Haque | Diseases | Best Researcher Award

Ms. Rafita Haque | Diseases | Best Researcher Award

PHD Student at Florida International University, United States

Rafita Haque is a dynamic researcher and Ph.D. candidate in Computer and Electrical Engineering at Florida International University (FIU), USA. With a solid background in software and computer science engineering, her academic and professional pursuits are centered around Artificial Intelligence (AI), biomedical sensors, cardiovascular health management, and blockchain-based healthcare communication systems. Rafita has served as a lecturer at renowned institutions in Bangladesh, including Daffodil International University and the Asian University of Bangladesh. She has also gained valuable industry experience as a Software Quality Assurance (SQA) Engineer. Her research contributions span interdisciplinary domains with a strong focus on technological innovation for health and information security. Rafita has authored several impactful publications indexed in Scopus, Springer, and Web of Science. Her work has earned her multiple honors, including the Best Paper Award in Malaysia and Best Project Award in Bangladesh. She continues to push boundaries in AI-driven health technologies and secure data systems

Professional Profile 

 Scopus Profile | ORCID Profile | Goolge Scholar

Education

Rafita Haque is currently pursuing her Ph.D. in Computer and Electrical Engineering at Florida International University (FIU), USA, where her research is focused on AI, biomedical sensors, PPG signal analysis, optical systems, and cardiovascular health. She is under the supervision of Dr. Nezih Pala. She previously completed her M.Sc. in Software Engineering from Daffodil International University, Bangladesh, with a thesis centered on consumer-to-consumer (C2C) information quality in Facebook-based purchasing decisions. Her academic focus was in Management Information Systems and data analysis, graduating with a CGPA of  Rafita earned her B.Sc. in Computer Science and Engineering from Gono Bishwabidyalay, where she developed a secure intra-university network management system for her final year project, graduating with a CGPA of Throughout her academic journey, she has integrated software engineering fundamentals with applied machine learning and security domains to develop impactful research in interdisciplinary technologies.

Experience

Rafita Haque has held multiple roles combining academia and industry. She served as a Lecturer in the Department of Computer Science and Engineering at the Asian University of Bangladesh (AUB), and earlier at Daffodil International University. Her teaching repertoire included core courses like Operating Systems Design, Theory of Computing, and Programming Languages. Her role extended beyond classroom instruction to research collaboration and student mentoring. Before transitioning to academia, Rafita worked as a Software Quality Assurance (SQA) Engineer at Data-Soft Systems Bangladesh Ltd. and Cloud Production Ltd., where she was involved in banking and insurance-related AML (Anti-Money Laundering) software solutions. She applied her technical acumen in Python, ASP.NET, MySQL, and NoSQL technologies to modify, test, and document large-scale enterprise systems. These diverse experiences across teaching, research, and software engineering have shaped her into a versatile technology expert with a strong understanding of software reliability, cybersecurity, and academic innovation.

Award and Honor

Rafita Haque has received several academic and research distinctions. Most notably, she was awarded the Best Paper Award in the Internet of Things (IoT) Track at the 1st International Conference on Technology Innovation and Data Sciences (ICTIDS) in Malaysia. Earlier in her academic career, Rafita’s innovative project titled “Intra University Secure Network Management System” won the Best Project Award during the Spring  Project Fair at Gono Bishwabidyalay. Her excellence in research communication was also acknowledged through a Paper Presentation at Blockchain Olympiad Bangladesh (BCOLBD). These recognitions highlight her commitment to combining technical rigor with real-world applications. Her work has earned visibility and praise in both academic and public forums, establishing her as a promising researcher with both innovation potential and academic integrity. These accolades continue to drive her motivation toward impactful, ethical, and scalable technological solutions in the fields of health, AI, and cybersecurity.

Research Focus

Rafita Haque’s interdisciplinary research integrates Artificial Intelligence, biomedical sensors, signal processing, and data security. Her primary work at FIU focuses on using PPG signal analysis to improve cardiovascular health monitoring through AI-enhanced biomedical devices. Rafita also explores the integration of blockchain in securing Electronic Medical Records (EMRs), improving privacy and interoperability in healthcare communication systems. Previously, her research delved into Ajax vulnerability, session management flaws, and remote code execution, aligning with web application security. She has contributed to several Scopus and Springer-indexed publications on blockchain integration, CoT (Cloud of Things), and data-driven decision systems in smart environments. Rafita’s broader research vision is to harness intelligent, secure technologies to bridge healthcare gaps in under-resourced communities. Her future plans include advancing predictive models in biomedical engineering using deep learning and exploring real-time health monitoring systems powered by wearable sensors and blockchain infrastructure.

Research Skill

Rafita Haque brings a well-rounded skillset combining academic, technical, and analytical competencies. Her programming expertise includes Python, C/C++, JavaScript, Node.js, and ASP.NET. She is well-versed in blockchain platforms such as Ethereum, MetaMask, and Remix Framework, enabling secure and decentralized applications, especially in healthcare. In data analysis, she leverages tools like SPSS, PLS, and research methodology frameworks to conduct evidence-based studies. Her background in network and information security is bolstered by training in CCNA, RCE vulnerabilities, and cybersecurity practices. She has applied her knowledge in projects involving cloud computing, AML solutions, and secure communication systems. Rafita’s pedagogical skills include course design and student mentorship. Her interdisciplinary mindset allows her to excel in areas such as cardiovascular signal analysis, AI model development, project management, and system validation. She continuously upgrades her expertise through professional development and collaborative projects, ensuring a skillset aligned with industry and research trends.

Publication Top Notes

Title: Broken Authentication and Session Management Vulnerability: A Case Study of Web Application
Cited by: 48
Year: 2018

Title: Blockchain-based Information Security of Electronic Medical Records (EMR) in a Healthcare Communication System
Cited by: 36
Year: 2021

Title: Integration of Blockchain and Remote Database Access Protocol-Based Database
Cited by: 14
Year: 2020

Title: Modeling the Role of C2C Information Quality on Purchase Decision in Facebook
Cited by: 13
Year: 2018

Title: A Cloud of Things (CoT) Approach for Monitoring Product Purchase and Price Hike
Cited by: 10
Year: 2021

Title: Identification of Construction Era for Indian Subcontinent Ancient and Heritage Buildings by Using Deep Learning
Cited by: 10
Year: 2020

Title: Performance Analysis of Different Feature Detection Techniques for Modern and Old Buildings
Cited by: 9
Year: 2018

Title: A Study of Ajax Template Injection in Web Applications
Cited by: 9
Year: 2018

Title: A Combined Model of Blockchain, Price Intelligence and IoT for Reducing the Corruption and Poverty
Cited by: 8
Year: 2018

Conclusion

Rafita Haque’s academic progression, research diversity, and consistent involvement in impactful projects position her as a deserving recipient of the Best Researcher Award. Her ability to synthesize knowledge from software engineering, data science, and biomedical applications demonstrates her cross-disciplinary research potential. She is not only contributing to the academic domain but also aligning her research with societal needs—especially in healthcare innovation. With ongoing doctoral work in the U.S. and an expanding publication record, Rafita shows strong potential for future leadership in AI-driven biomedical research and academia.

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