Neural Networks and Deep Learning

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Bachelor's degree

Developed a novel multi-class classifier based on Multi Layer Perceptron operating in the clustered feature space

- Studied various Clustering algorithms and their role in building an Ensemble of Classifiers. 
- Implemented an architecture for class decomposition and the combination of classifier outputs.

Research Intern

Worked in the Bing Defensive Team, with the aim of truly capturing extent of Problematic, Offensive and Hateful content of various kinds for all of our Bing Search experiences such as WebResults, ImageResults, AutoSuggest and other generated search results and suggestions. Leading the project as a Tech Lead in a team of 4 people with a keen focus on Metric Quality, and Metric Automation

Tech Lead

Worked in the Bing Defensive Ranker team where I built document/webpage level DL transformer based models to identify problematic content of various kinds such as hate, self-harm, misinformation. Worked on optimizing and hosting these models to infer at scale of 400B Web & Image Index. Worked on Bing Core Ranking stack to investigate and ship ranker changes to demote these identified problematic URLs for all user queries on both web and image search results.

Software Engineer 2, Machine Learning

Worked on creating a Big Data Platform for Security Researchers & Data Scientists to analyse and detect suspicious behaviour

Technology used - Scala, Python, Azure Synapse Analytics

Software Engineer 2

Working on End2end Compliance Automation by building a multi-agent compliance investigator for Compliance
investigation for different kinds of Fraud patterns.
Worked on the evaluation, testing for this multi-agent system

Senior Machine Learning Engineer

Developer on the Microsoft Defender team enabling Researchers protect users against malware across various platforms

Worked on creating a validation platform from scratch for Researchers to better detect malware across MacOS and Linux 

Technology used - C#, React, Bash, Python

Software Engineer

Worked on Reducing False Positives in OFAC (Office of Foreign Assets Control) Compliance Process.

Analyzed the working of various String Similarity, Machine Learning and Deep Learning algorithms for identifying the Fraudulent Financial Transactions with the aim of reducing False Positives and still keeping the False Negatives in check. 

LEAP Program

ML Intern

ML Engineer

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