AI4Bharat is a Research Center at IIT Madras focused on developing ML-based solutions for Indian communities. I was working as a contributor for the Shoonya Project and the Chitralekha Project.

Shoonya is a data labeling and annotation tool built to enhance digital presence of under-represented languages in India. Chitralekha is an open source platform tool for video subtitling across various Indic languages, using ML model support. Both the platforms are currently being used by 100+ annotators across India who are skilled translation experts.

Developed a React and Django based web portal to annotate and store the text translations from English to Indian languages and vice-versa.

Wrote efficient code for the logic of the APIs and Webhooks used by the platform for both internal and external software functionalities.

Implemented multiple async functionalities in the project using celery and Django to speed up the application.

Worked on developing and automating financial trading strategies using seminal research papers. Implemented the strategies, like Piotroski F Score and Momentum Trading Strategy, and backtested them for over 15 years' data with positive returns.

I conducted various test to ascertain the results which included downside risk measures like Value at Risk, CVaR, Semideviation, Sharpe and Sortino Ratios. I also developed pipelines which automated the process of investing and testing on past data using Python.

Developed and deployed a machine learning tool for the Union Bank of India which allotted risk scores to customers based on past customer data. The bank used the model to decide which customers would receive a loan. My risk allocation model brought down the customer default rate by 11% on 2 years of testing data.

Assisted ongoing research in the field of financial machine learning to help write a paper which was accepted in The Financial Review.

Worked on a project by the Botnar Foundation to capture and understand what young people (age 10-24 yrs) today think about topics like their future, aspirations, concerns, and challenges they face, etc.

Collaborated with a team of 50 Machine Learning engineers to develop tools to analyze and understand the sentiments and aspirations of young people and performed a temporal analysis to understand how the sentiments have been changing over time, especially due to the Covid-19 Pandemic.

I was also the task manager of the Reddit team which worked on Crowdsourcing data from the popular social media website. My team collected and processed over 30000 posts along with comments in three languages.

The project host, Fondation Botnar, is a Swiss-based foundation that champions the use of digital and AI to improve the health and wellbeing of children and young people globally. They used our work to create counselling services and mental well-being indicators for young people in the European Union.