Waqas Munir | Statistics | Best Researcher Award

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Waqas Munir | Statistics | Best Researcher Award

Mr Waqas Munir, Quaid-i-Azam University, Islamabad , Pakistan

Based on Mr. Waqas Munir’s academic and professional profile, he stands out as a suitable candidate for the Best Researcher Award. Hereā€™s a breakdown of his qualifications and achievements, structured in a title-paragraph format:

Publication profile

scopus

Educational Background

Mr. Waqas Munir holds a Master of Philosophy in Statistics from Quaid-i-Azam University, completed between 2014 and 2017. His thesis, titled ā€œNew Cumulative Sum Control Charts for Monitoring Process Mean and Process Dispersion,ā€ showcases his ability to contribute significantly to statistical methodologies. Additionally, he completed his Master of Science in Statistics at the same institution from 2011 to 2013, providing him with a strong foundational knowledge in various statistical concepts.

Life Philosophy

Mr. Munir embodies a profound enthusiasm for research and continuous learning. He recently completed his postgraduate studies and is now pursuing a Ph.D. program in Statistics. His strong foundation in statistical methodologies and programming fuels his ambition to uncover insights within the realm of Statistics and elevate his educational attainment.

Teaching Experience

His teaching experience is notable, having served at Fast University, Islamabad since Fall 2019, and at Quaid-i-Azam University, Islamabad since Spring 2023. This experience not only demonstrates his commitment to education but also highlights his role in shaping the next generation of statisticians.

Research Interests

Mr. Munir’s research interests encompass a range of statistical fields, including Statistics Process Control, Machine Learning, and Applied Statistics. His focus on practical applications of statistics positions him as a forward-thinking researcher in the field.

Publications

Mr. Munir has made substantial contributions to academic literature, with several publications in reputable journals. Notable articles include:

  • ā€œNew cumulative sum charts for monitoring process variabilityā€ (2017) – This publication explores innovative approaches to process control, demonstrating Mr. Munir’s expertise in cumulative sum (CUSUM) charts.
  • ā€œImproved CUSUM charts for monitoring process meanā€ (2018) – Co-authored with Haq A, this work enhances existing methodologies in process monitoring, reflecting his ability to improve statistical tools.
  • ā€œNew CUSUM and Shwhart-CUSUM charts for monitoring the process meanā€ – This research further establishes his focus on improving statistical methodologies, contributing to advancements in quality control.

Publication Top Notes

New CUSUM and EWMA charts with simple post signal diagnostics for two-parameter exponential distribution

New CUSUM and Shewhart-CUSUM charts for monitoring the process mean

Improved CUSUM charts for monitoring process mean

New cumulative sum control charts for monitoring process variability

Conclusion

In summary, Mr. Waqas Munir’s academic qualifications, teaching experience, research interests, and impactful publications position him as a strong candidate for the Best Researcher Award. His commitment to advancing the field of Statistics through rigorous research and education exemplifies the qualities sought in an award recipient.

 

Muhammad Shakir Khan | Statistics Award | Best Researcher Award

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Dr. Muhammad Shakir Khan | Statistics Award | Best Researcher Award

Dr. Muhammad Shakir Khan, Islamia College Peshawar, Pakistan

Dr. Muhammad Shakir Khan is a seasoned Statistician, Researcher, and Data Analyst with over 15 years of professional experience. He holds a PhD in Statistics from Islamia College Peshawar and specializes in regression analysis, statistical modeling, and machine learning. As the Deputy Director (Statistics & Economics) at the Livestock & Dairy Development Department, Khyber Pakhtunkhwa, he oversees data management, research guidance, and project planning. Dr. Khan has published extensively in reputed journals and led numerous research projects in livestock and genetics. Proficient in R, Python, SPSS, and other analytical tools, he is passionate about advancing his skills and knowledge.

Publication Profile

Orcid

Professional Experience šŸ¢

Muhammad Shakir Khan, a seasoned Statistician, Researcher, and Data Analyst, boasts 15 years of experience in statistical analysis and research. He currently serves as Deputy Director (Statistics & Economics) at the Livestock & Dairy Development Department, Khyber Pakhtunkhwa, Pakistan, where he oversees the statistics section, guides researchers, and manages data for policy formulation. His previous roles include Statistical Officer and Statistical Assistant, focusing on data analysis, research, and project management.

Academic Qualifications šŸŽ“

Ph.D. in Statistics (2018-2024): Islamia College Peshawar

M.Phil in Applied Statistics (2015-2017): Islamia College Peshawar

M.Sc. in Statistics (2007-2008): University of Peshawar

B.Sc. (2004-2006): University of the Punjab

Research Focus

Muhammad Shakir Khan’s research focuses on statistical modeling and data analysis, particularly in linear regression and its applications. He specializes in handling multicollinearity through ridge estimators and penalized regression techniques. His work includes applying these methods to medical, financial, and demographic data. He has contributed significantly to understanding statistical methodologies through simulations and practical applications. His expertise extends to machine learning, bootstrap methods, and advanced data analytics. His publications span various topics, including comparative performance analysis in zoology and food safety, showcasing his versatile application of statistical tools.

Publication Top Notes

  1. “On the estimation of ridge penalty in linear regression: Simulation and application” (2024, Kuwait Journal of Science, DOI: 10.1016/j.kjs.2024.100273) šŸ“ŠšŸ”¬
  2. “On some two parameter estimators for the linear regression models with correlated predictors: Simulation and application” (2024, Communications in Statistics – Simulation and Computation, DOI: 10.1080/03610918.2024.2369809) šŸ“ˆšŸ“š
  3. “On the performance of two-parameter ridge estimators for handling multicollinearity problem in linear regression: Simulation and application” (2023, AIP Advances, DOI: 10.1063/5.0175494) šŸ“‰šŸ§®
  4. “Comparative Performance of Jersey Sired Calves from Achai Dams and Azakheli Buffalo Calves Fed with Milk Replacer” (2018, Pakistan Journal of Zoology, DOI: 10.17582/journal.pjz/2018.50.5.sc7) šŸ„šŸ¼
  5. “Determination of Aflatoxin M1 in Raw Milk for Human Consumption in Peshawar, Pakistan” (2015, Pakistan Journal of Zoology, WOS:000357140700037) šŸ„›āš ļø

Sunita Sharma | Statistics Award | Best Researcher Award

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Ms. Sunita Sharma | Statistics Award | Best Researcher Award

Ms. Sunita Sharma, G.B. Pant University of Agriculture and Technlogy Pantnagar, Uttarakhand, India

Dr. Sunita Sharma is a dedicated statistician specializing in Bayesian analysis and reliability engineering. She holds a Ph.D. in Statistics from GB Pant University, with expertise in the Weighted Exponential-Lindley distribution. With teaching experience at Surajmal Agarwal Girls Degree College and as a Teaching Assistant at GB Pant University, she has honed her skills in imparting statistical knowledge. Her research, focused on repairable multi-component systems, has been published in esteemed journals. Dr. Sharma’s commitment to academic excellence is underscored by her participation in conferences and workshops. She is passionate about advancing statistical methodologies for real-world applications.

 

Publication Top Notes

šŸŽ“ Education

Dr. Sunita Sharma earned her Ph.D. in Statistics from GB Pant University, focusing on Bayesian Statistics and Reliability Engineering. She holds a Master’s and Bachelor’s degree in Statistics from Kumaun University, excelling with high grades.šŸ‘©ā€šŸ«

Teaching Experience

As a Lecturer at Surajmal Agarwal Girls Degree College and a Teaching Assistant at GB Pant University, Dr. Sharma taught various Statistics courses, ensuring student understanding and progress.

šŸ”¬ Research Experience

Her Ph.D. thesis delved into Bayesian approaches for analyzing the reliability of repairable multi-component systems, showcasing her expertise in statistical modeling and computational methods.

šŸ… Honors and Certificates

Dr. Sharma’s academic achievements include prestigious scholarships and certifications in data programming and statistical software.

Research Focus šŸ“Š

Dr. Sunita Sharma’s research primarily centers on Bayesian analysis and reliability engineering, particularly in the context of repairable multi-component systems. She specializes in utilizing the Weighted Exponential-Lindley distribution to model reliability characteristics, aiming to enhance accuracy and uncertainty quantification in estimation. Through her work, she explores the practical implications of Bayesian methods, comparing them with classical approaches. Her contributions span various domains, including the estimation of reliability in linear/circular k-out-of-n systems and multicomponent stress-strength models. Dr. Sharma’s dedication to advancing statistical methodologies reflects her commitment to addressing real-world challenges in system reliability assessment.