Princeton, New Jersey, United States
A computer science enthusiast, with a passion for programming and solving challenging problems and to write code that caters a large user base. Programming language agnostic, but experienced in Java and C#. AREAS OF INTEREST - Full Stack Software Design and Development - Machine Learning - Data Science TECHNICAL SKILLS • Programming Languages – Java, Python, SQL, Android • Web Technologies – PHP, HTML, CSS, JavaScript, XML, JSON • Tools – Git, Eclipse, Dev-C++, Android Studio, Visual Studio • Operating Systems – Windows, Linux (Ubuntu), macOS SUMMARY OF QUALIFICATIONS - Highly motivated about learning new technologies. - Always assumed a leading role at any level of projects while forming cohesive team environments. - Work ahead of time. - Can work well under pressure as well.
* Currently working as a backend developer for Registration and Eligibility Services team, to develop web services for Millennium Platform. * Tasks include developing enterprise grade REST API's for patient and encounter admittance, modification and deletion and managing patient profiles and insurance to be consumed by EJS System using JAX-RS Jersey implementation in Java. * Automated testing complex workflows using Cucumber. Additionally worked full stack on a user interactive dynamic website to manage company rooms and allow reservations during available time slots as per user requirements. Tasks included writing individual services, integration with Outlook API and designing UI for user interaction. Technologies used - Java, JUnit, React, Jest
* Worked for UF Health as a Software Engineer in full stack development to develop and maintain IDEALIST platform which predicts patient surgery risk and displays them to surgeons in realtime. * Tasks included working with patient data and write scripts to extract and transform predicted data about the kidney risk complications post surgery. * Technologies used - Java, Cassandra DB, Python, Pandas
* Worked as a developer to write code for improving the machine learning algorithm and training model of the agricultural crop data, by enhancing training data in quality and quantity. * Tasks included developing tool for dataset construction and labeling using AWS Python SDK and Command Line interface for Amazon Mechanical Turk, for expediting the labeling process, and extracting labelled data. * Technologies used - Python, NumPy, Click, AWSCLI