1. Google search tech impact award winner 2024 and 2023

2. Work on AI Overviews and AI mode

3. Working on various algorithms to improve RAG (retrieval augmented generation)

1. Developed methods from scratch to cluster large amount of time series data (approx.4 billion) and find correlation

2. Implemented Linear and Neural Granger Causality techniques to find the causality between time series data

3. Implemented tools to forecast time series data using LSTMs

4. Implemented tech stack in Kubernetes and Golang, along with Pytorch, Python

Worked as a teaching assistant for Natural Language Processing course under Dr. Alan W Black

1. Classified millions of reviews into aspects, analyzed aspect level sentiment to bring voice of customers to clients.

2. Implemented CNNs, bidirectional RNNs with ensemble learning to improve the benchmarked performances.

3. Researched and devised ways to handle long sentences by dividing into phrases and capturing non-adjacent contextual words by using skipgrams or dependency pair relations for the customers.

Technologies: Python, Theano, Keras, Scikit-Learn