Dr. Deepak.M Sakate

Dr. Deepak.M Sakate

Name: Dr. Deepak.M Sakate
Designation: Associate Professor & Head
Phone: 04366-277230
Email: deepak@cutn.ac.in


Biographic Sketch:
Dr. Deepak M. Sakate is a Statistician with interest to develop statistical methods for identifying necessary predictors for responses considered in a variety of fields of research. He is principal investigator of a study on development of variable selection procedures in zero and multiple inflated models for count data. He is also interested in nonparametric tests for location, scale and location-scale problem based on ranked set sampling scheme. He is actively engaged in developing methods for analyzing high-dimensional data. His abilities to design and undertake interdisciplinary studies in collaboration with scientists from other fields are evidenced by the range of studies he is involved. He is an expert in data analysis using R software. Dr. Sakate is an Associate Professor and Head of the Department of Statistics and Applied Mathematics at Central University of Tamil Nadu (Dec. 2019 onwards). Previously, he was an Assistant Professor in Department of Statistics, Shivaji University Kolhapur (Dec. 2010-Dec. 2019). He started his career as an Assistant Professor in Department of Statistics, KBCNMU, Jalgaon (Dec. 2009-Dec. 2010). He did his Bachelor’s, Master’s and Doctorate in Statistics from Shivaji University, Kolhapur. He qualified CSIR NET conducted in Dec. 2008 while pursuing his M.Sc. He has also qualified ISS (Nov. 2008) and was offered position of JTS officer (super class I) in central civil services of Government of India. He visited USA as an exchange visitor for postdoctoral research at Department of Biostatistics and Epidemiology, Augusta University, Augusta, Georgia (Aug. 2015-July 2016). He was actively involved in clinical studies related to dementia and obesity in American children. He is a life member of ISPS, IISA and SUSTA.

Research Highlights :

The research of Dr. Deepak M. Sakate is primarily focused on development of variable selection procedures which are consistent, robust to outliers and computationally fast. He developed variable selection procedures in Generalized linear models and regression models for count data which are of all-subset, stepwise or penalized regression type. He developed nonparametric tests for two sample location problem based on simple random sampling and ranked set sampling. He developed an Artificial Neural Network training algorithm based on divergence loss. Apart from this, he is also involved in studies involving the application of statistical models.

Recent Publications :

1. Vanjare, S. R., & Sakate, D. M. (2022). Consistent variable selection using R2 criterion in generalized linear models. International Journal of Agricultural and Statistical Sciences, 18 (2), 467-473. https://connectjournals.com/03899.2022.18.46

2. Kulkarni, S., Kurane, A., & Sakate, D. (2022). Impulse Oscillometry System for the Diagnosis of Wheezing Episode in Children in Office Practice. Journal of Asthma and Allergy, 15, 353. (IF: 3.027) https://doi.org/10.2147/JAA.S344643

3. Salamwade, R. L., and Sakate, D. M. (2022) Robust variable selection via penalized MT-estimator in generalized linear models, Communications in Statistics - Theory and Methods, 51:22, 8053-8065 (IF: 0.893) https://doi.org/10.1080/03610926.2021.1887240

4. Salamwade, R. L. and Sakate, D. M. (2021). Comparison of Variable Selection Methods in Zero-Inflated Models. International Journal of Agricultural and Statistical Sciences, 17 (2), 443-451. https://connectjournals.com/03899.2021.17.443 

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