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.

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