Software Engineer @Microsoft | CSE | NIT Durgapur '22 | Currently working on WinAppSDK and WinUI3.
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Microsoft
Software Engineer
June 15, 2026 – Present
CameraCaptureUI_Multi_Window_Sample
September 4, 2024 – September 4, 2024
CameraCaptureUI_Multi_Window_Sample — GitHub repository
View ProjectCollge-Event-Landing-Page
July 15, 2021 – July 21, 2021
A static landing page built with html,css,js and dom.
View ProjectSurf-Shop
July 13, 2021 – July 13, 2021
A robust web application with Node.Js, Express.Js, MongoDb, JQuery plus a ton of other technologies. It's an e-commerce web app with integrated maps, cloudinary and search filter It also includes password reset features, two step authorization and user authentication
View ProjectPing-Pong-Score-Keeper
July 12, 2021 – July 12, 2021
A Simple Ping Pong Score Game (HTML,JS,CSS,Bulma)
View ProjectGalaxy_Classification_Using_CNN_Tensorflow_Keras_Updated
July 10, 2021 – July 10, 2021
A galaxy classification system using Optimal Convolution Neural Network has been designed and developed. Broadly there are five different types of galaxies. They are elliptical, spiral, disk, lenticular and irregular. We have proposed an optimal deep convolution neural network which learns the features of the different types of galaxies in the form of a set of filters and after the learning is over recognizes the type of the unknown galaxies. The CNN uses stratified data set of 300 images of different galaxies. With this, the optimal point with data size (150) as well as number of filters (130) of neither overshooting nor undershooting is found out to get the optimal network complexity – which highly improves the performance evaluation. The performance evaluation of the CNN architecture used for galaxy classification in terms of its accuracy, precision, recall and f-score is quite satisfactory. Also the training and testing time is affordable.
View ProjectGalaxy-Classification-Using-CNN-Tensorflow-Keras-
May 28, 2021 – May 28, 2021
Trained CNN model for Galaxy Classification into 5 broad categories using Tensorflow/Keras
View ProjectOrderBookFromLuno-master
May 16, 2021 – May 16, 2021
OrderBookFromLuno-master — GitHub repository
View ProjectWindowsAppSDK-Samples
September 23, 2020 – Present
Feature samples for the Windows App SDK
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a broad interest in various technical domains, from low-level C++ development to web applications and machine learning. This diversity suggests adaptability and a willingness to explore different technologies. However, without information on team-based projects or contributions to open source beyond personal repositories, it's difficult to fully assess cultural fit, especially regarding collaboration and alignment with specific team dynamics. The current role at Microsoft suggests a fit for a large tech company culture.
Soft Skills & Operational Fit
The provided data is insufficient to assess soft skills or operational fit. The candidate's project descriptions suggest a proactive approach to learning and building, but direct evidence of collaboration, problem-solving under pressure, or communication style is absent.