Software Engineer

• Jun 2021 - Present

Graduate Teaching Assistant

• Aug 2020 - May 2021

• Graduate Teaching Assistant and Lab Instructor for Application Development in AWS Cloud using C#, and Advanced Web Development at George Mason University.• Responsible for instructing and helping students in development and programming applications operated on ASP.NET in Cloud, and for coaching undergraduate students to develop skills in JavaScript and C#.

React Developer

• Nov 2020 - Jan 2021

• Led a team responsible for development of a chrome extension utilizing ReactJS called as Hypothesizer, this chrome extension acts as a debugging tool for react applications, it helps developers generate correct hypothesis for what might be causing underlying problem.• Created test cases for end-to-end testing of application implementing React JS and Bootstrap, worked with JSON files to store, and retrieve hypothesis.

Lead Software Developer C# and VR Development

• Dec 2019 - Aug 2020

• Worked on Sony’s Aibo AI robot-dog to research Human-Machine Interaction. Wrote Web API’s to train robot with Python scripts.• Programmed/trained Aibo for Speech recognition of Cognitive Phrases utilizing Python and Performed SQL commands to store and maintain data in Database.• Implemented a controlled and laboratory-validated ecological system inVirtual Reality using C# and Unity3d, also used the XR development Tool kit.• Assembled environment for ROKOKO smart-suit development with C#, Unity3D and ROKOKO Software. Show less

Software Developer Intern

• Feb 2019 - Aug 2019

• Led Research-team to assembling a Software for doctors helping them detect cancer at a early stage, software took mammograms as input and classified It as a Malignant or Benign type of cancer with help of Machine Learning and Data Mining using Python. • Computer-assisted coding to improve efficiency and speed of cancer detection with Deep Learning and Image Processing. • Led Research-team to assembling a Software for doctors helping them detect cancer at a early stage, software took mammograms as input and classified It as a Malignant or Benign type of cancer with help of Machine Learning and Data Mining using Python. • Computer-assisted coding to improve efficiency and speed of cancer detection with Deep Learning and Image Processing.