Ereena Bagga
A software engineer, specializing in full-stack Development and Cyber Security.
- 🎓 Recently completed my Honour's in Software Engineering at Deakin University,
Melbourne.
- âš¡ I like to craft solid and scalable full-stack applications with great user
experiences.
- 🔠I’m currently working as an Automation Test Engineer at JDR Software.
- 🚀 Grad Girls Volunteer, Student Ambassador at Microsoft Learn, SEBE Peer Mentor at
Deakin University.
- 📮 Current Project - Deep Learning Web Application: Real-Time Posture Correction
System.
- 📚 Apart from software development I love reading books, cycling, travelling.
- Take a look around my digital garden 🌱, and
let's chat about how we can create something awesome together!
Get To Know
About Me
A driven software developer with a knack for crafting innovative solutions across diverse technologies. From building efficient web applications to diving deep into machine learning, I thrive on creating impactful, user-friendly experiences. My journey has equipped me with skills in programming, web development, and cybersecurity, allowing me to bring a versatile approach to every project. Whether it's optimizing systems for performance or collaborating with teams to deliver quality products, I’m driven by a desire to push boundaries and deliver real-world results.
projects
Skills
My Technical SkillsProgramming Languages
Python
90%C++
80%.NET
80%Java
70%C# (Object-oriented)
80%JavaScript
90%TypeScript
90%Web Technologies
HTML
90%CSS
90%Node JS
80%React JS
80%Vue.js
70%Express.js
70%AngularJS
70%JavaScript
90%MEAN/MERN stack
70%Cybersecurity
Ethical Hacking
70%Cybersecurity Management
70%Database
Mongo DB
80%MySQL
70%PostgreSQL
70%DevOps
Microsoft Azure
60%Docker
60%IDEs
Jupyter Notebook
90%VS Code
90%PyCharm
80%Eclipse
80%IntelliJ
80%Qualification
My Personal JourneyBachelor of Software Engineering (Honours)
Deakin University, Melbourne10+2
New Public School, IndiaAutomation Test Engineer
JDR Software, MelbourneWeb Development Engineer
Food Remedy Co, Deakin University, MelbourneProjects
My recent projects
React Color Palettes
A Color palettes app built using React and chrome picker, where the user can copy the hex/rgb/rgba of the color they like. The user can create their own palettes with their own beautiful colors.
Demo
Deep Learning Web Application: Real-Time Posture Correction System
SafeLift utilizes advanced computer vision, image processing, and machine
learning technologies to revolutionize workplace safety.
This intelligent solution employs real-time posture tracking and analysis during manual
lifting activities, preventing musculoskeletal disorders.
Accessible through standard webcams, SafeLift educates and continuously monitors
employees, ensuring optimal safety through innovative technology.
Engineered a web application incorporating deep learning and computer vision
algorithms using Python to accurately track and analyze employees' postures during
manual lifting activities with a 93% accuracy rate, enabling real-time monitoring,
feedback, and prompt corrective measures for safer work practices.
Implemented the application using Flask for the backend with a responsive user
interface resulting in a 20% reduction in workplace
injuries associated with manual lifting activities, demonstrating a tangible improvement
in employee safety.
Explore This Project Demo
Generative AI-Driven Chatbot Application: The Medi
The care that health practitioners can provide to patients is only as good as the
information available
to them. The Chatbot, also known as Medi, aims to simplify the process of
information gathering and retrieval through a unified conversational interface for
patients and health
practitioners to enter and review data. The aim for Medi is to become a welcoming,
simple, and efficient
one-stop medical assistant.
Led the university capstone program for Gopher Industries and spearheaded the
development of a Gen AI chatbot called 'The Medi', designed to streamline patient
interactions, including appointment booking and online diagnosis.
Leveraged Google Dialogflow and Firebase to build and integrate sophisticated
natural language processing features, enabling the chatbot to accurately interpret and
respond to user queries, achieving a 25% increase in accurate user query
comprehension.
Explore This Project Demo
Full Stack Development: A Smart Food Granary Management System
The goal of the project is to create a mass food storage system that could be used to
remotely monitor and manage food granaries or cold storage. StoraTAG is an
RFID-enabled mass storage system that helps reduce food waste and improve food mobility
and management by allowing us to trace the lifecycle of a sack from the time it enters
the storage unit until it exits. It uses a UID system (Unique Identification System) to
distinguish sacks from one another and stores their related data in a database, making
it simple for the user to track the status of the sacks from the StoraTAG
website.
Created a responsive, RFID-enabled food granary management web application using
the MEAN stack (MongoDB, Express.js, AngularJS, Node.js), facilitating remote monitoring
and management of granaries. This system reduced food waste by 25% and optimized
operational costs.
Integrated hardware components into the application to develop a robust embedded
system, achieving a 30% reduction in system response time and improving overall
efficiency.
Explore This Project
C++ Game Development: An Adventorous Space Game
I’ve been watching Lost In Space on Netflix and thought it would be fun to create a space game where the user explores a game universe moving between planets, dodge things, collecting coins, getting power-ups, etc. There is also a time limit where they are aiming to find a destination planet, with limited fuel. This way there is the trade off between reading the goal and improving your score.
Explore This Project Demo
React Color Palettes
A Color palettes app built using React and chrome picker, where the user can copy the hex/rgb/rgba of the color they like. The user can create their own palettes with their own beautiful colors.
Demo
Deep Learning Web Application: Real-Time Posture Correction System
SafeLift utilizes advanced computer vision, image processing, and machine
learning technologies to revolutionize workplace safety.
This intelligent solution employs real-time posture tracking and analysis during manual
lifting activities, preventing musculoskeletal disorders.
Accessible through standard webcams, SafeLift educates and continuously monitors
employees, ensuring optimal safety through innovative technology.
Engineered a web application incorporating deep learning and computer vision
algorithms using Python to accurately track and analyze employees' postures during
manual lifting activities with a 93% accuracy rate, enabling real-time monitoring,
feedback, and prompt corrective measures for safer work practices.
Implemented the application using Flask for the backend with a responsive user
interface resulting in a 20% reduction in workplace
injuries associated with manual lifting activities, demonstrating a tangible improvement
in employee safety.
Explore This Project Demo