Currently I am postdoctral researcher at Computer Science Department in Aalto university in Finland under supervision of professors Samuel Kaski. My work focuses on personalized medicine, specifically exploring machine learning approaches for medical networking and graphical data.
Currently I am postdoctral researcher at Computer Science Department in Aalto university in Finland under supervision of professors Samuel Kaski. My work focuses on personalized medicine, specifically exploring machine learning approaches for medical networking and graphical data.
Earlier I was a Postdoctoral fellow at Indian Statistical Institute (ISI) Delhi. Here I was working under Prof. Isha Dewan and Dr. Sudheesh Kumar Kattumannil (from ISI Chennai). Prior to this, I completed my Ph.D. from the Department of Mathematics and Statistics at the Indian Institute of Technology (IIT) Kanpur, under the supervision of Prof. Neeraj Misra. My Ph.D. work is centered around "the Estimation of order-restricted parameters." The problem of estimating the location (scale) parameters of two distributions when the ordering between them is known apriori has been extensively studied in the literature. Many of these studies are centered around deriving estimators that dominate the best location (scale) equivariant estimators or the maximum likelihood estimators (MLEs) by exploiting the prior information that parameters are order restricted. In my thesis, I attempt to unify various results in the literature by considering a general bivariate location (scale) probability model and a general loss function. Some novel results in this area are included in my research.
Earlier I was a Postdoctoral fellow at Indian Statistical Institute (ISI) Delhi. Here I was working under Prof. Isha Dewan and Dr. Sudheesh Kumar Kattumannil (from ISI Chennai). Prior to this, I completed my Ph.D. from the Department of Mathematics and Statistics at the Indian Institute of Technology (IIT) Kanpur, under the supervision of Prof. Neeraj Misra. My Ph.D. work is centered around "the Estimation of order-restricted parameters." The problem of estimating the location (scale) parameters of two distributions when the ordering between them is known apriori has been extensively studied in the literature. Many of these studies are centered around deriving estimators that dominate the best location (scale) equivariant estimators or the maximum likelihood estimators (MLEs) by exploiting the prior information that parameters are order restricted. In my thesis, I attempt to unify various results in the literature by considering a general bivariate location (scale) probability model and a general loss function. Some novel results in this area are included in my research.
