About Me

Graduate Student | Machine Learning Enthusiast | Full Stack Developer

Hi there! Welcome to my website

I am passionate about problems with high impact and I love to code. I strongly believe that technology has a way to solve our problems to an extent one cannot imagine. I have worked with variety of completely novel machine learning problems and their unique dataset. I am always out for a discussion on Machine Learning or Software Development or technology in general.

I am currently pursuing my masters in Computer Science at University of California, Irvine

Past Experiences

Machine Learning Engineer at Behavidence
(2019 – 2020)
First machine learning engineer at Behavidence Inc.

  • Engineered features to compute mental health score based on mobile phone usage and built machine learning models in python that diagnosed depression with the recall rate of 75% and precision of 71%
  • Developed a real-time pipeline using Amazon Web Services Sagemaker to calculate mental health score – optimized a pipeline that ran for 24 hrs to 5 seconds
  • Built data pipeline using AWS services (Glue, Sagemaker, DynamoDB, API Gateway) fetching data from mobile application to train machine learning models

Software Developer at Atlassian Corporation PLC(2019- 2021)
Full stack developer at Atlassian Marketplace team.

  • Ideated an app recommendation system using association rule mining technique in Atlassian embedded marketplace. Developed the first backend prototype in Kotlin that constitutes 3.5% of app installs
  • Fixed license generation asynchronous flows across multiple Java services to reduce app installation failure by 35%
  • Optimized load management and batch emailing pipeline to launch request app feature on the embedded marketplace which led to 1.2M USD revenue in the following quarter
  • Updated MongoDB data model and exposed GraphQL API for the Cloud Fortified App program – to provide end customers a set of extensively secured top 10% of cloud apps
  • Redesigned UI filters on the marketplace homepage by developing reusable React components in Javascript which led to 4.3% increased filter usage
  • Created a Kotlin microservice and designed DynamoDB schema to build scalable distributed storage, and query systems that are fault-tolerant and easy to manage to facilitate migration of on-prem apps to the cloud with Rest APIs
  • Secured marketplace against privilege escalations and XSS attacks. Implemented the SLOs as API latency and availability of EC2 machines on SignalFX(terraform), providing real-time SLO violation alerts