Jinse Jacob, an accomplished Assistant Professor of Statistics, brings a wealth of expertise and a deep-rooted passion for data analysis to the academic realm, specializing in regression analysis and robust estimation and statistical programming language R, where he effortlessly navigates intricate datasets. Beyond traditional statistical methods, his commitment to staying at the forefront of statistical innovation is evident in his enthusiasm for multivariate techniques, including regression, classification, and machine learning.

In the academic sphere, Jinse Jacob is recognized for contributing significantly to regression models and robust estimation procedures. His research, blending theoretical insights with practical applications, advances statistical methodologies and provides valuable contributions to the broader statistical landscape. This dynamic figure in the statistical community combines academic rigour with a hands-on approach, driven by a profound curiosity for uncovering patterns and extracting meaningful insights from data.

Beyond his academic pursuits, Jinse finds joy in the world of arts and creativity. As a music connoisseur, he immerses himself in melodic compositions while his leisure moments showcase his artistic flair through intricate pencil drawings. This well-rounded individual's dedication to the precision of statistics and the expressive world of art exemplifies a commitment to pursuing knowledge and creativity

Regression and classification models, robust estimation