Recent Computer Science Graduate from The University of Texas at Dallas.
Worked with the Product Lifecycle Management team within Bell IT. Responsibilities included development tasks like updating an existing Java application, developing for Dassault Systèmes 3DExperience, and writing automation scripts.
Member of a full-stack mobile app development team. Ported native iOS app to React native app. Designed react components that included the use of Redux to manage state. Implemented OAuth 2.0 authentication. Developed a Java Springboot API for the app. Implemented a user-initiated photo ID verification service using Equifax REST API.
Delivered training to children ages 5-12 using Minecraft. The open-source curriculum included logic gates, basic programming techniques and Object-Oriented Programming by modding the game’s source code.
Designed, developed, and deployed an Android app using the Android SDK for a Mumbai-based tour operators ‘Amaze Tours and Travel’. The app had over 500 installs through the Google Play Store as of July 2021.
Awarded merit-based Academic Excellence Scholarship (AES) covering tuition for 8 semesters.
Gained an understanding of deep learning neural networks and learned how to use TensorFlow and Keras Libraries.
Learned about Data Science, use of Linear and Logistic Regression, and performing operations on large datasets using Python, Pandas, NumPy, and MatPlotLib.
Learned about R, Rstudio, and the use of R in Data Science, Statistical Analysis and Prediction using Linear and Logistic Regression.
Workshop primarily targeted at preparing for the Azure AI 100 Certification Exam. I also learned about the Azure ML tools and its pre-built classification tools, along with a brief introduction to building chatbots and text intent interpretation.
A console-based calculator with support for order-of-operations, parentheses, memory save and recall developed entirely using the MIPS Assembly Language.
Source code avaliable here.
Designed a logistic regression model using R to predict the salary of an individual based on a dataset from Kaggle.
Source code avaliable here.