Bio: Dr. Jyotishka Datta is an assistant professor in the Department of Statistics at Virginia Tech. Prior to this, he was an Assistant Professor in the Department of Mathematical Sciences at the University of Arkansas Fayetteville from 2016-2020. He received his Ph.D. in Statistics from Purdue University in 2014 and worked as an NSF postdoctoral fellow at Duke University and SAMSI (Statistics and Applied Mathematical Sciences Institute) from 2014-16.

Abstract of the Webinar:

Sparse signal recovery remains an important challenge in large scale data analysis and both Bayesian and frequentist literature have undergone an explosive development in the past in both theory an methodology. The purpose of this talk is to briefly review and discuss these developments. In the first half of this talk, I will survey the extant literature and connections with Bayesian models will be highlighted at various points. In the second half, I will discuss a few unexplored aspects of their behavior and cover several recent developments. I will offer some insights into these problems and point out future directions.

Date: 9th july 2021
Time: 7:00 PM IST

Bio: Abhimanyu (Abhi) Gupta is an instructor of data science at the Richard A. Chaifetz School of Business at Saint Louis University. He has a Master of Statistics degree from the Indian Statistical Institute and is currently pursuing a Ph.D. in Information Systems at Ghent University, Belgium. Abhi is also a mentor and supervisor of the MBA students in their industry-focused practicum projects. He loves listening to music, reading non-fiction books, and learning about artificial intelligence. He hates traveling and parties. In summary, he is a nerd.

Abstract of the Webinar:

Data visualization is a popular tool for exploratory data analysis. However, finding patterns in data using only visualizations is often very subjective, thus inconsistent and unreliable. This presentation will demonstrate how a Decision Tree can help us identify some of the data patterns quickly.

Date: 27th June 2021
Time: 8:00 PM IST

Bio: Faculty in Statistics Department, University of Florida.

PhD in Statistics at University of Chicago. B.Stat and M.Stat at Indian Statistical Institute, Kolkata.

His main research interests lie in multiple time series, time-varying models, econometrics and neural networks.

Abstract of the Webinar: 

Contrary to what we learn in all basic statistics classes real data rarely show independence. This dependence can be of different forms: time dependence, space dependence, network dependence etc. In this talk I'll briefly introduce a few basic time series models that help identify some of the actual real life series. Some applications towards spatial dependence and network dependence will be mentioned. Finally I'll conclude with some econometric model that are usually used to model indices such as cryptocurrencies or stock indices.

Date: 7th May 2021
Time: 4:00 PM IST

Bio: Dr. Diganta Mukherjee, BStat, MStat, PhD (Economics) all from Indian Statistical Institute. Research interests are Welfare & Development Economics in general and multidimensional poverty in particular. He is also active in the area of Finance, particularly mathematical models for pricing contracts and Analysis and modelling of Network data. Ex-faculty, Jawaharlal Nehru University, Essex University, ICFAI Business School. Now faculty at the Indian Statistical Institute. Has over 90 research publications in national and international journals and authored four books.

He Has been involved in projects with large corporate houses and various ministries of Government of India and West Bengal Government. Also consults for NGOS and other Public Action Groups.

Acting as technical advisor to Multi-Commodities Exchange, Reserve Bank of India, Securities and Exchange Board of India, National Sample Survey Office, National Accounts Division (Central Statistical Office), UNDP (through Ministry of Home Affairs), Ministry of Electronics & Information Technology.

Abstract of the Webinar:

The setting: data in financial market
The model: discrete time: Binomial model
Data Analysis for financial model: using Correlation, Regression

Date: 9th April 2021
Time: 4:00 PM IST