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Hi, I am|

Work Experience

ARTDAI
Senior Software EngineerARTDAI
January 2024 - Present
ARTDAI
Software Engineer InternARTDAI
May 2023 - August 2023
BlackRock
Software Development Engineer IIBlackRock
July 2019 - July 2022
BlackRock
Software Developer InternBlackRock
January 2019 - July 2019
Council of Scientific and Industrial Research
Research InternCouncil of Scientific and Industrial Research
June 2018 - July 2018

Skills

Java
JavaScript
TypeScript
Python
HTML5
CSS
Tailwind CSS
ExpressJS
NodeJS
Angular
React
Flask
MySQL
MongoDB
Apache Ignite
AWS
Git
Protobuf
Grafana
Azure
Docker

Projects

AI Background Generator

  • Developed a web app using Angular and Python to automatically remove background from an image and replace it with image generated by AI based on user provided text prompt

ProTrac

  • Developed a Project Management Software with focus on task management, scheduling, and record keeping for Slnko Energy using Angular, MongoDB, and Node.js and deployed it on AWS

Daily Stock Metrics

  • Developed a web application using Angular and Java responsible for showing the analysis of different stocks by caching the relevant stock data in Apache Ignite clusters, collected by scraping data from multiple websites

Village Land Auction

  • - Led a team of 3 to develop backend and multi-lingual, user-friendly UI of an Android app used to organize events, handle payments, and capture auction details, saving time and reducing the cost of conducting the auctions significantly
  • - Designed and built a responsive website using React, Node.js, and MySql to help admin manage and visualize auction data

Automatic Personality Traits Detection using Handwriting

  • - Created a deep learning CNN model using TensorFlow and Keras to detect the personality of a person with 76% accuracy using 800 handwriting samples of more than 200 individuals
  • - Developed an Android application to scan handwriting samples and show predicted personality traits

Cancer Prediction using XGBoost

  • - Trained a machine learning model using Python with a real dataset of 1800 patients collected by Department of Biotechnology, TIET to predict lung cancer with 78% accuracy
  • - Processed raw data using statistical methods to filter out unwanted data and used Python libraries to visualize and compare performance of different machine learning models. Also created a website to predict cancer using the trained model

Let's Connect! 🚀

Whether you want to talk code, AI, coffee, or cat memes, I'm all ears! Drop me a message and let's make something awesome together. Prefer smoke signals or carrier pigeons? Email works too! ☕💬

+1 (480) 702-8580
himanshusharma7296@gmail.com