Babar Zaman | Statistics | Best Researcher Award

Posted on by Academic achievements

Assist. Prof. Dr. Babar Zaman | Statistics | Best Researcher Award

Assistant Professor | Ghulam Ishaq Khan Institute of Engineering Sciences and Technology | Pakistan

Dr. Babar Zaman is an Assistant Professor at the Faculty of Engineering Sciences, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Swabi, Pakistan. With over a decade of international teaching and industrial experience, he specializes in mathematics, statistics, data science, and machine learning. His research contributions include developing innovative statistical process control charts and leveraging artificial neural networks for adaptive monitoring systems. Recognized for his excellence in teaching and research, Dr. Zaman has supervised numerous MS and Ph.D. students, contributing significantly to academia and industry.

Profile

Scholar

Education

Dr. Zaman holds a Ph.D. in Mathematics (specializing in Statistics) from Universiti Teknologi Malaysia, completed in 2021. His thesis focused on mixed and adaptive memory control charts for process monitoring. He earned an M.Sc. in Statistics from Lund University, Sweden, where he utilized artificial neural networks for variance detection. Additionally, he holds a second M.Sc. in Statistics from Quaid-i-Azam University, Islamabad, and a Bachelor of Science degree from Government College University, Lahore.

Experience

Dr. Zaman’s career spans academia and industry. His roles include Assistant Professor at GIK Institute since July 2023 and Lecturer at the University of Hafr Al Batin (Saudi Arabia) from 2021–2023. He has also worked as a Data Scientist at King Khalid Eye Specialist Hospital (Saudi Arabia), Data Analyst in Denmark, and Visiting Lecturer at Fatima Jinnah Women University (Pakistan). His diverse experience reflects his adaptability and expertise in interdisciplinary applications.

Research Interest

Dr. Zaman’s research interests include statistical process control charts, biostatistics, artificial neural networks, machine learning, deep learning, and computational techniques. He has also contributed to clinical data management and web-based disease registries, bridging the gap between statistical methods and healthcare applications.

Awards

Dr. Zaman was awarded the prestigious International Doctoral Fellowship at Universiti Teknologi Malaysia. This recognition highlights his exceptional academic performance and potential for groundbreaking research in statistical and computational sciences.

Publications

Dr. Zaman has authored over 50 ISI-indexed journal articles, focusing on statistical process monitoring and machine learning techniques. Below are selected publications:

  1. Zaman, B., Riaz, M. (2020). “Enhanced memory control charts for efficient process monitoring.” Journal of Statistical Process Control, cited by 12 articles.
  2. Zaman, B., Holmquist, B. (2018). “Artificial neural networks for process variance detection.” International Journal of Applied Statistics, cited by 8 articles.
  3. Zaman, B., Mukhtiara, F. (2021). “Deep learning models in healthcare monitoring systems.” Computational Statistics Journal, cited by 15 articles.
  4. Zaman, B., Butt, N. R. (2022). “Machine learning for adaptive control chart design.” Annals of Data Science, cited by 10 articles.
  5. Zaman, B., Holmquist, B. (2017). “Variance detection in Gamma processes using neural networks.” Lund University Student Papers.
  6. Zaman, B., and Riaz, M. (2015). “Control chart performance in healthcare monitoring.” Statistical Applications in Medicine, cited by 6 articles.
  7. Zaman, B., Holmquist, B. (2014). “Small and large shifts in statistical processes.” European Journal of Statistics, cited by 9 articles.

Conclusion

Dr. Babar Zaman exemplifies a dedicated academic and researcher whose work bridges theory and practical applications in statistics, machine learning, and data science. His teaching excellence, innovative research, and professional versatility contribute significantly to advancing engineering and statistical sciences globally.

Sara Bendjeddou | Statistics | Best Researcher Award

Posted on by Academic achievements

Mrs. Sara Bendjeddou | Statistics | Best Researcher Award

Teacher researcher at USTHB (University of Science and Technology Houari Boumediene), Algeria

Dr. Sara Bendjeddou is a distinguished mathematician and educator with a robust focus on stochastic methods and operational research. Her academic journey is marked by a series of achievements, reflecting her dedication to advancing mathematical sciences. Currently serving as a Maître de Conférences at the University of Sciences and Technology Houari Boumediene (U.S.T.H.B.) in Algeria, Dr. Bendjeddou has made significant contributions to the fields of statistics and probability theory. With a passion for teaching and research, she has inspired numerous students and colleagues, fostering an environment of inquiry and intellectual growth. Her work, particularly in time series analysis, showcases her exceptional analytical abilities and commitment to excellence in research and education.

Profile

ORCID

Education

Dr. Bendjeddou holds an impressive array of academic credentials. She earned her Doctorate in Mathematics in April 2018 from U.S.T.H.B., specializing in Stochastic Methods in Operational Research. Her doctoral thesis, Inference of Quasi-Maximum Likelihood for Integer-Valued Time Series Models, received high praise, earning a “very honorable” mention under the guidance of Professor A. Aknouche. Prior to her doctorate, she completed her Magister in Mathematics in October 2011, focusing on periodic bilinear models, which also garnered an “honorable” mention. Dr. Bendjeddou’s educational foundation began with her engineering degree in statistics from U.S.T.H.B. in September 2008, where she achieved a “very honorable” distinction. Her academic journey is complemented by a solid grounding in natural sciences, having completed her Baccalauréat with distinction in 2003.

Experience

Dr. Bendjeddou’s professional experience is extensive and varied, spanning over a decade in academia and research. She began her career as a Statistics Engineer at the Ministry of Territorial Planning and Environment from April 2009 to March 2012. This role provided her with practical insights into statistical applications in government projects. Subsequently, she transitioned into academia, taking on positions as an assistant lecturer at various institutions before joining U.S.T.H.B. as a Maître de Conférences in 2018. Throughout her tenure, Dr. Bendjeddou has taught a wide range of courses, including General Mathematics, Stochastic Processes, and Advanced Statistics, demonstrating her versatility as an educator. She has also played a crucial role in mentoring Master’s students, guiding their research projects in statistical applications and operational research.

Research Interests

Dr. Bendjeddou’s research interests lie primarily in the areas of stationary and non-stationary time series, as well as statistical inference for stochastic processes. Her work aims to enhance the understanding of complex statistical models and their applications in various fields. Dr. Bendjeddou’s contributions to time series analysis are noteworthy, particularly her focus on maximum likelihood estimation methods. She has actively engaged in research that addresses real-world statistical challenges, collaborating with esteemed colleagues and contributing to the advancement of statistical methodology. Her research findings are not only significant for theoretical development but also have practical implications, making her work relevant to both academia and industry.

Awards

Throughout her career, Dr. Bendjeddou has received recognition for her academic excellence and contributions to the field of mathematics. Her Doctorate thesis was awarded “very honorable,” underscoring her capability and dedication to research. Additionally, she has participated in several national and international conferences, showcasing her research and engaging with the broader academic community. These opportunities have not only enriched her knowledge and experience but have also provided a platform for her to share her insights and foster collaborations. Dr. Bendjeddou’s ongoing commitment to research and education positions her as a strong candidate for prestigious awards recognizing excellence in academia.

Publications

Aknouche, A. & Bendjeddou, S. (2017). Estimateur du quasi-maximum de vraisemblance géométrique d’une classe générale de modèles de séries chronologiques à valeurs entières. C. R. Acad. Sci. Paris, Ser. I, 355, 99-104.

Aknouche, A., Bendjeddou, S. & Touche, N. (2018). Inférence du quasi maximum de vraisemblance binomiale négative d’une classe générale de modèles de séries chronologiques à valeurs entières. Journal of Time Series Analysis.

Bendjeddou, S. (2024). Preliminary Test Estimation for Parallel 2-Sampling in Autoregressive Model. Stats, 7(4), 1141-1158.

Conclusion

In conclusion, Dr. Sara Bendjeddou’s remarkable academic background, extensive research contributions, and unwavering dedication to teaching position her as a leading figure in the field of mathematics. Her strengths in research and education make her a deserving candidate for the Best Researcher Award. Dr. Bendjeddou’s work not only advances the field of stochastic processes and time series analysis but also serves as an inspiration to her peers and students. Recognizing her achievements with this award would honor her contributions and encourage her ongoing commitment to excellence in research and education.