Moiz Qureshi | Statistics | Best Researcher Award

Dr. Moiz Qureshi | Statistics | Best Researcher Award

Quaid-i-Azam University, Pakistan

👨‍🎓Profiles

🎓 Early Academic Pursuits

His academic journey began with a Bachelor's degree in Statistics from the University of Sindh, Jamshoro, completed in February 2018. His passion for statistical theory and applications led him to pursue an M.Phil. in Statistics at Quaid-i-Azam University, Islamabad, where he graduated in December 2020. During this time, he developed a robust foundation in statistical methodologies and analytical problem-solving.

💼 Professional Endeavors

Moiz embarked on his professional career as a Lecturer in Statistics at Shaheed Benazir Bhutto University (SBBU), Nawabshah, from February 2021 to July 2023. In this role, he taught statistical theory and application, mentored students, and actively participated in academic research. Currently, Moiz serves as a Lecturer in Statistics at Govt. Degree College TandoJam, District Hyderabad, Pakistan, where he continues to shape the minds of future statisticians and contributes to the field through teaching and research.

📚 Contributions and Research Focus

His research interests include statistical methods, data analysis, and their practical applications across various domains. His academic endeavors aim to bridge theoretical knowledge with real-world statistical problems, enhancing understanding and innovation in statistical science.

🌟 Impact and Influence

His dedication to education and research has left a significant mark on the institutions he has served. His students consistently appreciate his ability to simplify complex concepts, fostering a deep understanding of statistics.

✍️ Academic Cites and Contributions

As a researcher, Moiz has delved into various statistical topics, contributing to the academic community with publications and collaborations. While his academic citations continue to grow, they reflect his commitment to advancing statistical research and its applications.

🛠️ Technical Skills

He is proficient in a wide range of statistical and programming tools, including R, Python, MATLAB, Mathematica, STATA, SPSS, and EVIEWS. These skills enable him to analyze complex datasets and model statistical problems effectively.

🧑‍🏫 Teaching Experience

With experience in lecturing since 2021, Moiz has taught subjects encompassing statistical theory, data analysis, and applied statistics. His teaching style emphasizes clarity, engagement, and practical application, ensuring his students gain both knowledge and confidence in statistics.

🏅 Legacy and Future Contributions

He envisions leaving a lasting legacy in the field of statistics by fostering analytical thinking among students and contributing innovative solutions to statistical challenges. His future contributions include further research, academic mentoring, and collaborations to advance the discipline.

🔮 Vision for Statistical Education

Moiz aspires to create a transformative impact in statistical education by integrating advanced tools like AI and machine learning into his teaching and research. His goal is to ensure the next generation of statisticians is equipped to address emerging challenges in data-driven decision-making.

📖Notable Publications

 

 

Edmund Agyemang | Analytical Techniques | Best Researcher Award

Mr. Edmund Agyemang | Analytical Techniques | Best Researcher Award

University of Texas Rio Grande Valley, United States

👨‍🎓Profiles

🌱 Early Academic Pursuits

Edmund Fosu Agyemang’s academic journey has been a testament to dedication and excellence in the field of statistics. His early foundation in the sciences began at Aggrey Memorial A.M.E Zion Senior High School, where he earned accolades for his mathematical prowess. His pursuit of higher education at the University of Ghana, where he earned both his Bachelor’s and Master’s degrees in Statistics, laid the groundwork for his future research endeavors. His Master’s research, which focused on Bayesian Estimation of Presidential Elections, demonstrated his early interest in applying statistical methodologies to real-world issues.

🧠 Professional Endeavors and Contributions

Agyemang’s professional career reflects a blend of research, teaching, and consulting work, aimed at advancing statistical applications across sectors. His role as an adjunct faculty member at Ashesi University and his work as a Graduate Research Assistant at the University of Texas Rio Grande Valley (UTRGV) have been pivotal in shaping his academic trajectory. He has contributed to multiple fields, including machine learning, time series analysis, and data science, particularly in the context of healthcare and public policy. His consultancy work with organizations like the Ministry of Finance in Ghana on tax policy and the TV3 Election Command Center is an example of how his research has influenced both public and private sectors.

📊 Research Focus and Goals

Agyemang’s research interests are rooted in applied biostatistics with interdisciplinary applications, focusing on machine learning in health, time series analysis of health data, and the design and analysis of experiments. His current research includes exploring the intersection of artificial intelligence and healthcare, specifically using statistical, neural, and hybrid-based architectures to forecast the spread of Influenza A. His commitment to continuing his education, producing impactful research, and contributing to academia while uplifting society reflects his broader goals.

🔬 Impact and Influence

Agyemang’s impact extends beyond his direct research contributions. As a member of the editorial board for several academic journals, including the Journal of HIV/AIDS Research and Journal of Multidisciplinar, he has positioned himself as a thought leader in his field. His work as a peer reviewer for journals like Heliyon and Studies in Educational Evaluation further demonstrates his influence in shaping global academic discourse. Additionally, his involvement in academic conferences—such as the Joint Conference on Science and Technology in Dubai and the International Mathematics and Statistics Student Research Symposium—highlights his role in the global academic community.

🎓 Teaching Experience

Agyemang has taught and assisted in a wide range of courses, contributing to the development of future statisticians and researchers. He has served as an adjunct faculty member, lead tutor, graduate assistant, and teaching assistant at several institutions, including Ashesi University and the University of Ghana. His diverse teaching experience spans topics such as introductory statistics, precalculus, applied calculus, statistical inference, and time series analysis. Through his pedagogical efforts, he has empowered students to grasp complex statistical concepts and develop the skills necessary to solve real-world problems.

💻 Technical Skills

Agyemang’s technical proficiency is a hallmark of his academic and professional endeavors. He is skilled in using statistical software tools such as R, Python, SAS, STATA, and IBM SPSS, which he applies to a variety of research projects. His expertise in reproducible research and publishing is evident in his use of LATEX and R Markdown for scientific report writing. These technical abilities have enabled him to contribute to cutting-edge research in applied biostatistics, machine learning, and data science, particularly in the health sector.

🌍 Legacy and Future Contributions

Agyemang’s academic journey is poised to leave a lasting legacy, not only through his research but also through his commitment to mentorship and service to society. His involvement in volunteer activities, including serving as an international student buddy at UTRGV and leading student mentor-mentee programs at Ashesi University, demonstrates his dedication to empowering others. Looking ahead, his future contributions will likely continue to focus on leveraging statistical and machine learning techniques to address pressing global challenges, particularly in the healthcare and public policy domains.

🏆 Awards and Recognitions

Agyemang’s exceptional work has earned him numerous awards and recognitions. These include the Outstanding Masters Research Performance Award, the Presidential Research Fellowship at UTRGV, and the Best MPhil Statistics Student award at the University of Ghana. His excellence in teaching and research has also been acknowledged through honors such as the Honor Roll for Academic Excellence and the Best Graduate Research Assistant award. These accolades are a testament to his unwavering commitment to excellence in all facets of his academic and professional life.

🌟 Future Directions and Aspirations

As Agyemang continues his research at UTRGV, his goal remains to contribute to the advancement of statistical methodologies in healthcare and public policy. His ongoing work on forecasting health data with AI models will likely have significant implications for predicting disease outbreaks and improving public health responses. Ultimately, he envisions a dual career as a research scientist and educator, transferring knowledge and empowering the next generation of statisticians and researchers.

📖Notable Publications

    • A Gaussian Process Regression and Wavelet Transform Time Series approaches to modeling Influenza A
      • Authors: Edmund Fosu Agyemang
      • Journal: Computers in Biology and Medicine
      • Year: 2025
      • DOI: 10.1016/j.compbiomed.2024.109367
    • Anomaly detection using unsupervised machine learning algorithms: A simulation study
      • Authors: Edmund Fosu Agyemang
      • Journal: Scientific African
      • Year: 2024
      • DOI: 10.1016/j.sciaf.2024.e02386
    • Predicting Students’ Academic Performance Via Machine Learning Algorithms: An Empirical Review and Practical Application
      • Authors: Edmund Fosu Agyemang, Joseph Agyapong Mensah, Obu-Amoah Ampomah, Louis Agyekum, Justice Akuoko-Frimpong, Amma Quansah, Oluwaferanmi M. Akinlosotu
      • Journal: Computer Engineering and Intelligent Systems
      • Year: 2024
      • DOI: Not provided
    • A GARCH-MIDAS approach to modelling stock returns
      • Authors: Ezekiel NN Nortey, Ruben Agbeli, Godwin Debrah, Theophilus Ansah-Narh, Edmund Fosu Agyemang
      • Journal: Communications for Statistical Applications and Methods
      • Year: 2024
      • DOI: 10.29220/csam.2024.31.5.535
    • 10th Annual Meeting of Asian Council of Science Editors (Certificate of Attendance)
      • Authors: Edmund Fosu Agyemang
      • Event: 10th Annual Meeting of Asian Council of Science Editors
      • Year: 2024
    • 5th Asian Conference on Science, Technology & Medicine (Certificate of Attendance)
      • Authors: Edmund Fosu Agyemang
      • Event: 5th Asian Conference on Science, Technology & Medicine
      • Year: 2024