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

🎓 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.👩‍🏫

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.

🔬 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.

🏅 Honors and Certificates

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

Research Focus 📊

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.

Rizwan Yousuf | Statistics Award | Best Researcher Award

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Dr. Rizwan Yousuf | Statistics Award | Best Researcher Award

Dr. Rizwan Yousuf, CHANDIGARH UNIVERSITY MOHALI PUNJAB INDIA, India

Dr. Rizwan Yousuf, a Ph.D. holder in Statistics, boasts expertise in statistical modeling, analysis, and regression techniques 📊. With a robust academic background from Sher-e-Kashmir University and University of Kashmir, he has delved into diverse statistical realms, including bio statistics and multivariate analysis 🧮. Driven by a passion for research, he has investigated structural properties and estimation techniques in his dissertations. Formerly a Field Investigator, he now imparts knowledge as an Assistant Professor at Chandigarh University, bringing his extensive experience to the forefront of academia 🎓

Publication Profile

Google Scholar

Education

Dr. Rizwan Yousuf’s academic journey reflects a steadfast dedication to statistical sciences 📊. He earned his Ph.D. in Statistics from Sher-e-Kashmir University of Agricultural Sciences & Technology of Jammu (SKUAST-J) in December 2021, preceded by an M.Sc. from the University of Kashmir, Srinagar, in January 2018. His scholarly pursuits began with a B.Sc. (3 years) degree from the University of Kashmir in May 2015. Dr. Yousuf’s research endeavors culminated in dissertations exploring diverse statistical domains, notably his Ph.D. thesis delving into the estimation and validation of linear and non-linear production functions through robust regression techniques 🎓.

Working Experience

Dr. Rizwan Yousuf embarked on his professional journey as a Field Investigator, traversing through the intricacies of data collection and analysis at Degree College Beerwah Budgam Kashmir from September 2022 to March 2023 📋. Transitioning seamlessly, he currently serves as an Assistant Professor of Mathematics at Chandigarh University since May 2023, contributing his statistical expertise to academia 🎓. His experiences span from fieldwork to classroom instruction, enriching his understanding of statistical methodologies and their practical applications. With a dedication to fostering knowledge and research, Dr. Yousuf continues to inspire and guide students in their academic pursuits.

Research Focus

Dr. Rizwan Yousuf’s research primarily focuses on statistical modeling and analysis 📊, with a particular emphasis on robust regression techniques. His work encompasses a wide range of applications, including the assessment of stress levels and coping mechanisms among married working women, economic ramifications of the COVID-19 pandemic, and modeling production functions in agricultural contexts. Dr. Yousuf’s expertise extends to outlier detection, estimation of productivity, and exploring novel regression estimators. Through his diverse research endeavors, he contributes significantly to advancing statistical methodologies and their practical implications across various domains.

 

Publication Top Notes 

  1. Assess the level of stress and coping level among married working women in Kashmir 📄 Cited by: 6 Year: 2022
  2. Unexpected Ramifications of Corona Pandemic Economic and Statistical Issues📄 Cited by: 6 Year: 2020
  3. Robust Model for the Quadratic Production Function in Presence of High Leverage Points📄 Cited by: 4 Year: 2021
  4. Modified Ratio-cum-Exponential Estimator for Appraising the Population Mean using Conventional and non-Conventional Parameters📄 Cited by: 3 Year: 2022
  5. ROBUST MODELS AND THEIR VALIDATION FOR MAIZE PRODUCTION IN JAMMU REGION OF JAMMU AND KASHMIR UNION TERRITORY 📄 Cited by: 1 Year: 2021
  6. Applications of Mitscherlich Baule function: a robust regression approach 📄 Year: 2024
  7. Detection of High Leverage Points in Regression Model in Apple Data 📄 Year: 2022
  8. Outlier Detection and Identification in Square root Production Function using Robust Regression 📄 Year: 2022
  9. Estimation and Validation of Robust Model for Productivity of Apple in UT of J&K using Cobb Douglas Method 📄 Year: 2021
  10. A New form of Ratio Estimator under Rank set Sampling📄 Year: 2021

 

Anu Sirohi | Survival Analysis | Best Researcher Award

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Dr. Anu Sirohi | Survival Analysis | Best Researcher Award

Dr. Anu Sirohi, Amity University, India

👩‍🏫 Dr. Anu Sirohi is an accomplished Assistant Professor in Statistics, with experience at prestigious institutions like Amity University and Sharda University. Holding a Ph.D. in Statistics, her research focuses on survival models for infant and child mortality in India. With expertise in Python, R, SPSS, and more, she excels in machine learning, regression, and statistical analysis. Passionate about education, she supervises Ph.D. candidates and imparts knowledge in advanced statistical techniques. Dr. Sirohi’s dedication to academia is matched only by her commitment to advancing statistical research and empowering future statisticians.

Publication Profile:

Scopus

Education:

👩‍🎓 Dr. Anu Sirohi completed her Ph.D. in Statistics from Banasthali University, Rajasthan, in September 2020. Her doctoral thesis, titled “Survival Models for Mortality Experience of Infant and Child Underfive: An Evidence from India,” showcases her dedication to understanding and addressing critical issues in public health. In June 2015, she achieved UGC-NET JRF accreditation in Population Studies, demonstrating her expertise in demographic research. Dr. Sirohi’s academic journey reflects her passion for exploring statistical methodologies to improve outcomes for vulnerable populations, particularly infants and children under five, in India.

Work Experience:

👩‍🏫 Dr. Anu Sirohi currently serves as an Assistant Professor in the Department of Statistics at Amity University, Noida, since May 10, 2023. Prior to this, she held a similar position at Sharda University, Greater Noida, starting from August 3, 2021, until May 9, 2023. With her expertise in statistics and commitment to academic excellence, Dr. Sirohi contributes significantly to shaping the minds of future statisticians. Her tenure at both institutions reflects her dedication to fostering learning environments where students can thrive and develop a profound understanding of statistical concepts and methodologies.

Research Focus:

🔬 Dr. Anu Sirohi’s research spans diverse areas within statistics and mathematical modeling, with a particular emphasis on public health and agricultural optimization. Her work delves into intricate topics such as proportional hazard regression models, frailty analysis, and dynamic programming approaches in agriculture. Dr. Sirohi’s expertise shines through in her exploration of collinearity effects on statistical estimators and the development of novel methodologies to address these challenges. With a keen focus on applications in infant mortality assessment, precision agriculture, and system reliability analysis, she contributes significantly to advancing knowledge and solutions in these critical domains, blending empirical evidence with mathematical rigor to drive impactful research outcomes.

Publication Top Notes:

Biased proportional hazard regression estimator in the existence of collinearity

AI-based Dynamic Programming Approach in Agriculture for Solving Intuitionistic Fuzzy Assignment Problems

Performance analysis of Precision Agriculture model using copula distribution and common cause Breakdown

Some r–k class proportional hazard regression models in the presence of collinearity: an evidence from Indian infant mortality

Parametric Frailty Analysis in Presence of Collinearity: An Application to Assessment of Infant Mortality

Stochastic Analysis of a Priority-Based Warm Standby System Working under k-out-of-n G Policy Using Multi-Dimensional Repair

Alternative approach to moments of order statistics from one-parameter Weibull distribution

On the structure of infant mortality using accelerated failure time (AFT) model: A comparative study based on national family health survey (NFHS) data in India