Plenary Speakers

She is a Professor of Statistics at the University of Connecticut, and her research area includes Time Series Analysis, Actuarial Science, etc. She is a co-editor in Chief of International Statistical Review, and President of the International Society for Business and Industrial Statistics from 2015-2017. She is a fellow of the American Statistical Association and an elected member of International Statistical Institute with Dipak K. Dey. Nalini Ravishanker is the author of A First Course in Linear Model Theory, She is also one of the editors of Handbook of Discrete-valued Time Series.

- Nalini Ravishankar

Fabrizio Ruggeri is Research Director at the Italian National Research Council in Milano. His interests are mostly in Bayesian and industrial statistics, especially in robustness, decision analysis, reliability, stochastic processes; recently, he got involved in biostatistics and biology as well. Dr. Ruggeri is Adjunct Faculty at Polytechnic Institute (New York University), Faculty in the Ph.D. program in Mathematics and Statistics at University of Pavia, Foreign Faculty in the Ph.D. program in Statistics at the University of Valparaiso,
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Fabrizio Ruggeri is Research Director at the Italian National Research Council in Milano. His interests are mostly in Bayesian and industrial statistics, especially in robustness, decision analysis, reliability, stochastic processes; recently, he got involved in biostatistics and biology as well. Dr. Ruggeri is Adjunct Faculty at Polytechnic Institute (New York University), Faculty in the Ph.D. program in Mathematics and Statistics at University of Pavia, Foreign Faculty in the Ph.D. program in Statistics at the University of Valparaiso, Member of the Advisory Board of the Ph.D. program in Mathematical Engineering at Polytechnic of Milano. ASA Fellow and ISI Elected Member, Dr. Ruggeri is the current ISBA (International Society for Bayesian Analysis) President and former ENBIS (European Network for Business and Industrial Statistics) President. Author of more than 100 papers, one book and editor of three books, he is also the Editor-in-Chief of Applied Stochastic Models in Business and Industry (the official ISBIS journal) and Encyclopedia of Statistics in Quality and Reliability, besides being the Chair of the Bayesian Inference in Stochastic Processes workshops and Co-Director of the Applied Bayesian Statistics summer schools.

-Fabrizio Ruggeri

Malay Bhattacharya is a Professsor at IIM Banglore. His academic career spans more than three decades, and he has published in academic journals and conference proceedings. His research interests include Quantitative Finance, Time Series and Extreme Value Theory.

- Malay Bhattacharya

About Conference

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Post Workshop Details

A three day post confrerence Workshop led by Prof.William Q . Meeker during Jan 1 - Jan 3 2021

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About Conference

The International Society for Business and Industrial Statistics (ISBIS) selected Kochi as the venue for its regional conference in December 2020. Further this conference is a part of the activity of the Department of Statistics, CUSAT, under the SAP-DRS Level III of the University Grants Commission, India. The conference is a significant event as 2020 is the Silver Jubilee year of the Department of Statistics, CUSAT. The primary objective of the conference is to provide a platform for disseminating recent developments on statistical methods for different field of application in general, Business and Industry in particular. With an aim to expose young researchers and students to ideas in the theory and applications of Statistics, the seminar will consist of expository talks by experts in addition to invited talks and contributory sessions. The sessions will include deliberations in the area of Reliability Theory, Survival Analysis, Probability Theory, Statistical Inference, Industrial Statistics, Data Mining, Stochastic Models, Queuing and Inventory models, Time Series Analysis, Linear Models, Design of Experiments, Bio Statistics, Bio Informatics, Statistical Genetics, Multivariate Methods and Survey Sampling, Data Science, Machine Learning, etc.