Research
My research focuses on developing computationally efficient novel statistical methods that are capable of handling structurally complex datasets. The broader theme of my research is a confluence of Bayesian Statistics and Machine Learning.
My research interests include:
Latent Factor Models
Network analysis
Nonparametric Statistics
Recommender Systems
Reinforcement Learning.
Publications:
Environmental Impact of the COVID-19 Induced Lockdown Measures on the PM2.5 Concentration in USA
Rahul Ghosal and Enakshi Saha
Atmospheric Environment (2021)
Dynamic Sparse Factor Analysis
Enakshi Saha, Veronika Rockova and Kenichiro McAllin
Journal of Applied Econometrics (in Revision), (2021+)
On Theory for BART
Veronika Rockova and Enakshi Saha
The 22nd International Conference on Artificial Intelligence and Statistics. PMLR (2019)
Some High-dimensional One-sample Tests Based on Functions of Interpoint Distances
Enakshi Saha, Soham Sarkar and Anil K. Ghosh
Journal of Multivariate Analysis 161 (2017): 83-95.
Consulting Experience
Effect of Hunger on Moral Development in Children
with Elizabeth Huppert & Jean Decety, Department of Psychology, The University of Chicago
Role of Gene Tbx5 in Formation of Forelimb in Zebrafish
with Erin Boyle Anderson & Robert K. Ho, Department of Organismal Biology and Anatomy, The University of Chicago
Moderated Mediation Analysis of Moral Communication and Moral Hypocrisy
with Elizabeth Huppert, Emma Levine & Jean Decety, Department of Psychology, The University of Chicago
Miscellaneous
Human Activity Recognition Using Smartphones (2016)
Data Analysis Project Report (STAT 349), The University of Chicago
Some Multi-sample Run Tests Applicable to High Dimension Small Sample Size Data (2014)
with Anil K. Ghosh, Indian Statistical Institute, Kolkata