Rupali Sinha

Researching on building efficient machine learning models in NLP using neural networks with Transfer Learning and Zero Shot Learning. The research uses Pytorch as DL framework.

1. Researched on issues arising when model assumptions are violated, including recommendations for remedy (both frequentist and bayesian approach). The project used R as the programming language, RSTAN for bayesian analysis and ggplot2 as the visualizing tool. 2. Developed machine learning tool for analysing portfolio of data using Python and front end. The project used Python Dash and Plotly for developing the dashboard.

Development and maintenance of software for insurance based client in Mainframes.

Testing the application of SoC for the set top box in STLinux.

Elements of Statistical Learning, NLP, Information Retrieval and Data Mining, Artificial Intelligence, Neural Networks, Knowledge Representation on Semantic Web.