Centre for Advanced Research in Applied Mathematics and Statistics, MAHE, Manipal, India
Padma Vibhushan Professor Calyampudi Radhakrishna Rao is one among the great Indian statisticians who received 2023 International Prize in Statistics, which is equivalent to Nobel prize in Statistics. CRR, a living legend received this prize for his groundbreaking work entitled ‘Information and the Accuracy Attainable in the Estimation of Statistical Parameters’ published in Bulletin of Calcutta Mathematical Society in 1945. C R Rao, born on September 10, 1920 at Hoovina Hadagali, Karnataka lived a long fruitful life of 102+ years till August 22, 2023.
Center for Advanced Research in Applied Mathematics and Statistics (CARAMS, MAHE) has been organizing events and special sessions in honor of him since 2020, the year it celebrated ‘CRR Day’ marking Rao’s 100th birthday. In the same year, CARAMS organized an international conference ALAPS 2020 (online format) in honor of Rao, where Prof. C R Rao arrived on the screen with the help of his daughter, accepted felicitation, and conveyed his best wishes to his disciples, collaborators, and admirers among the participants. In the following year, CARAMS organized an international conference ICLAA 2021 and an international workshop IWMS 2021 (hybrid format), with common sessions in honor of Prof. Rao. The proceeding of ICLAA 2021 and IWMS 2021 is now being published in honor of Prof. Rao by Springer Nature in its Indian Statistical Institute Series.
CARAMS, MAHE will be organizing a two-days symposium in hybrid format during September 24-25, 2023 to pay him the tribute. On the same occasion, a book-volume in honor of C R Rao (and A K Lal) and a special issue of AKCE Int. J. Graphs Comb. dedicated to ICLAA 2021 will be released.
The objective of the symposium is to connect young scholars and students with Rao’s area of work and his achievements. Besides having seminars and technical sessions from eminent scientists in the field and various student activities refreshing the memories of Rao, scholars and students are also encouraged to present their research work with the theme connected to Rao’s work and achievements.
The theme of symposium shall focus on, but not limited to
and the articles in the above focus area may be submitted for the presentation in the contributory session. Research papers presented in the contributory session will get an opportunity of possible publication in a forthcoming special issue dedicated to ICLAA 2023 in the following journals, subject to acceptance after the standard peer review process adopted by the journals.
Book Release: The book ‘Applied Linear Algebra, Probability, and Statistics – a book-volume in honor of Prof. Rao and Arbind K Lal’ (Eds: R B Bapat, M P Karantha, S Kirkland, S K Neogy, S Pati, and S Puntanen) will be released on this occasion.
Tribute to Prof. Rao: A session following the book release will be dedicated to pay the tribute to Prof. Rao.
The organizing committee invites all students and the scholars working in the theme area to participate in the symposium.
Research papers presented in the contributory session of the symposium will get an opportunity of possible publication in a forthcoming special issue dedicated to ICLAA 2023 in the following journals, subject to acceptance after the standard peer review process adopted by the journals.
Category | Registration Fee |
---|---|
Foreign Nationals | 50 USD |
Indian Research Scholars and Faculty/Students presenting paper in contributory session | 1000 INR + GST |
Indian UG/PG Students | 500 INR + GST |
There is no GST for the Faculty/Research Scholars/UG/PG Students of MAHE.
Note: Participants taking part in the student activities are exempted from the registration fee payment.
Research Interests:
Matrices and Graphs, Nonnegative Matrices, Matrix Inequalities and Generalized Inverses Read more
Achievements:
He has published more than 140 research papers in these areas in reputed national and international journals and… Read more
Research Interests:
Applied Statistics, Linear Programming, Nonlinear Programming, Non-cooperative games, Stochastic games, Statistical Quality Control, Six Sigma, Quality Management. Read more
Achievements:
Based on his research and teaching interests, in applied statistics and matrix methods, he has published several research… Read more
Research Interests:
Matrix methods in statistics, Generalized inverses, Canonical correlations Read more
Achievements:
He was a Senior Researcher of the Academy of Finland in 1992--1995. His main research interest lies on… Read more
The International Prize in Statistics is awarded every two years by a collaboration among five leading international statistics organizations. The Prize is being considered as the statistics’ equivalent of the Nobel Prize. Professor C.R. Rao received the Prize this July at the International Statistical Institute World Statistics Congress in Ottawa, Canada. The goal of this talk is to give a brief look at the life and work of Professor Rao leading to this Prize. Moreover, some personal glimpses are given.
Research Interests:
Mathematical Statistics Read more
Achievements:
BLS Prakasa Rao received MStat (1962) from Indian Statistical Institute, Kolkata and PhD (1966) from Michigan State University.… Read more
Over the last several years, a large number of corporations are adapting a data-driven approach to have targeted services, reduced risks and improved performance. They are implementing specialized data analytic programs to collect, store, manage and analyze large data sets or what is now called BIG DATA. Analyzing large size of economic and financial data is challenging. BIG DATA has unique features that are not shared by the traditional data sets. BIG DATA sets are characterized by massive sample size and high dimensionality. Massive sample size allows one to unravel hidden patterns associated with small sub populations. Modeling the intrinsic heterogeneity of BIG DATA requires better statistical methods. There are several phenomena associated with high dimensionality such as noise accumulation, spurious correlation and incidental endogeneity. Traditional statistical methods are inappropriate to tackle such problems. There are also many types of events we can think of when there are a potentially large number of measurables or parameters/covariates quantifying the event but a relatively few instances of that event. Example: few patients with a given genetic disease but a large number of genes which might cause this event. In statistical terms, the number of parameters p is large as compared to the number of observations n. This type of data is termed as HIGH-DIMENSIONAL DATA. The basic methodology which was used in classical statistical methods is not applicable for analyzing such data. The basic question is when do we call a data as a BIG DATA? How do we quantify the size of the data? However Big Data is not the solution for all data analytic issues. There are privacy problems as well as ethical issues. There are also problems of selection bias when the Big Data is used, for instance, for Official Statistics by policy makers. We discuss some of these and related issues.
carams.mahe@gmail.com