Sadaf Khan | Probability and Statistics | Best Scholar Award

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Dr. Sadaf Khan | Probability and Statistics | Best Scholar Award

Dr. Sadaf Khan, The Islamia University of Bahawalpur, Pakistan

👩‍🏫 Dr. Sadaf Khan, a dedicated statistician, earned her PhD and MPhil in Statistics from Islamia University Bahawalpur. With a robust academic background including a Master’s and Bachelor’s in Statistics and Mathematics, she excels in statistical modeling and data analysis using tools like R, Mathematica, and SPSS. Dr. Khan has contributed significantly to research, publishing numerous articles in HEC-recognized journals. Her interests span Distribution Theory, Statistical Modeling, and Applied Statistics. Currently serving as a Visiting Lecturer at Islamia University Bahawalpur and Cholistan University of Veterinary & Animal Science, she aims to pursue a career in administration within an esteemed international organization. 📊

 

Publication profile

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Education 🎓📚

PhD in Statistics, 2022
Islamia University Bahawalpur, Pakistan

Masters in Philosophy (Statistics), 2016
Islamia University Bahawalpur, Pakistan

Master’s in Statistics, 2010
Islamia University Bahawalpur, Pakistan

B.Sc (Mathematics, Statistics & Economics), 2008
Islamia University Bahawalpur, Pakistan

 

Research Focus

Sadaf Khan, a prolific researcher, focuses on statistical modeling and applications across various disciplines. Her research spans diverse areas such as climate-related data analysis using bivariate q-generalized extreme value distributions, COVID-19 and cancer data modeling with generalized Burr-Hatke models, and statistical inference under progressive type-II censoring schemes. She also contributes significantly to new lifetime models in biomedical and environmental data, including applications of new family distributions like the gamma power half-logistic model. Khan’s work combines theoretical developments with practical applications, showcasing her expertise in statistical methodologies and their real-world implications. 📊🔬

 

Publication Top Notes

Bivariate q- generalized extreme value distribution: A comparative approach with applications to climate related data

Modeling to COVID-19 and cancer data: Using the generalized Burr-Hatke model

KAVYA-MANOHARAN WEIBULL-G FAMILY OF DISTRIBUTIONS: STATISTICAL INFERENCE UNDER PROGRESSIVE TYPE-II CENSORING SCHEME

Analysis of COVID-19 and cancer data using new half-logistic generated family of distributions

The gamma power half-logistic distribution: theory and applications

A New Family of Lifetime Models: Theoretical Developments with Applications in Biomedical and Environmental Data

The Binomial–Natural Discrete Lindley Distribution: Properties and Application to Count Data

The Generalized Odd Linear Exponential Family of Distributions with Applications to Reliability Theory

A new extended gumbel distribution: Properties and application

The Minimum Lindley Lomax Distribution: Properties and Applications

An Extension of Karrup–King–Newton Index

New Modified Burr III Distribution, Properties and Applications

Neelesh Shankar Upadhye | Probability and Statistics Award | Best Researcher Award

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Prof Dr. Neelesh Shankar Upadhye | Probability and Statistics Award | Best Researcher Award

Prof Dr. Neelesh Shankar Upadhye, Indian Institite Of Technology Madras, India

🎓 Prof. Dr. Neelesh Shankar Upadhye, renowned mathematician, earned his Ph.D. in Mathematics from IIT Bombay in 2009, with a remarkable 9.67/10. With a rich academic background including an M.Sc. from IIT Bombay and a B.Sc. from Wilson College, Mumbai, he has excelled in teaching and research. Currently a Professor at IIT Madras, he has significantly contributed to various courses, enhancing student learning experiences. With expertise in areas like Applied Statistics, he’s garnered praise for his innovative teaching methodologies. Upadhye’s dedication to education and quantitative research reflects his commitment to academic excellence. 📚

 

Publication Profile

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Academic Achievements:

Dr. Neelesh Shankar Upadhye boasts an impressive academic journey, culminating in a Ph.D. in Mathematics from IIT Bombay in 2009, where he also earned his M.Sc. and B.Sc. degrees. His doctoral thesis, supervised by Professor P. Vellaisamy, focused on “Compound Negative Binomial Approximations to Sums of Random Variables.” 📚

🏆 Professional Experience

With over a decade of teaching experience, Upadhye has held prestigious positions at IIT Madras, currently serving as a Professor. His expertise extends beyond academia, having worked as a Quantitative Researcher at Dolat Investments Ltd. 🏛️

🏅 Awards and Recognitions

Upadhye’s scholarly contributions have been acknowledged with numerous awards, including Senior and Junior Research Fellowships from CSIR and IIT Bombay. His qualifications and dedication underscore his status as a distinguished academician and researcher in the field of mathematics. 🌟

 

Research Focus

Dr. Neelesh Shankar Upadhye’s research primarily centers around probabilistic methods and statistical approximations, with a particular emphasis on compound distributions and their applications in diverse contexts. His work delves into advanced topics such as Stein operators, discrete approximations, and tail behavior analysis of random variables. Upadhye’s contributions extend to developing novel techniques for estimating parameters in time series models and exploring the tail behavior of functions of random variables. Through his publications, he consistently explores and advances the boundaries of statistical theory and its practical applications, fostering a deeper understanding of complex probabilistic phenomena. 📊

Publication Top Notes