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

Orcid

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

“On Stein factors for Laplace approximation and their application to random sums” (Statistics & Probability Letters, 2024)
“Constrained Bayesian Optimization with Lower Confidence Bound” (Technometrics, 2024)
“On Brascamp–Lieb and Poincaré type inequalities for generalized tempered stable distribution” (Statistics & Probability Letters, 2022)
“On first-come, first-served queues with three classes of impatient customers” (International Journal of Advances in Engineering Sciences and Applied Mathematics, 2021)
“Estimation of the parameters of vector autoregressive moving average (VARMA) time series model with symmetric stable noise” (International Journal of Advances in Engineering Sciences and Applied Mathematics, 2021)
“Generalizations of distributions related to (k1,k2)-runs” (Metrika, 2019)
“Pseudo-binomial approximation to (k1,k2)-runs” (Statistics & Probability Letters, 2018)
“On perturbations of Stein operator” (Communications in Statistics – Theory and Methods, 2017)
“On Stein operators for discrete approximations” (Bernoulli, 2017)
“On the tail behavior of functions of Random variables” (International Journal of Pure and Applied Mathematics, 2016)
“Compound Poisson Approximation to Convolutions of Compound Negative Binomial Variables” (Methodology and Computing in Applied Probability, 2014)

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