I am Umar Farooq Mirza from Pulwama, Kashmir. I have completed my B.Tech in Computer Science. I'm proficient in multiple programming languages and technologies including:
What sets me apart is my ability as a quick learner, which helps me adapt to new technologies and frameworks rapidly. I'm dedicated to continuous learning and growth in the field of software development.
My technical skills combined with my problem-solving abilities allow me to create efficient and innovative solutions.
The Crowdsafe Traffic & Accident Reporter is a web-based platform designed to enable real-time reporting of traffic incidents like accidents, roadblocks, and hazards using a community-driven approach. Built with Flask and SQLite3, this application features a robust user authentication system using Flask-Login, allowing users to register, log in, and submit reports that include descriptions, categories, images, and locations. All reports are displayed in a categorized layout for easy viewing.
The project also includes a dedicated admin panel where administrators can manage users and reports. Admins can view total counts, delete inappropriate entries, and remove malicious users. The dashboard includes neon-themed cards and icons for better visual clarity.
The tech stack comprises HTML, CSS, Bootstrap on the frontend and Python, Flask on the backend. Uploaded images are handled securely and stored in the static/uploads folder. The application runs locally and can be deployed on platforms like PythonAnywhere or Heroku.
Future enhancements include integration with Google Maps, user validation systems, a mobile app, and advanced data analytics for traffic pattern insights.
This Streamlit-based application predicts house rent using a deep learning model. It loads and processes a dataset containing house rental information, encoding categorical variables such as Area Type, City, Furnishing Status, and Tenant Preferences. The data is then split into training and testing sets. A neural network is built using TensorFlow's Keras, consisting of multiple dense layers with ReLU activation. The model is compiled with the Adam optimizer and trained using mean squared error loss. After training, users can input details such as BHK count, size, area type, city, furnishing status, tenant type, and number of bathrooms through a sidebar. On clicking the "Predict Rent" button, the model predicts the rental price and displays a confidence interval using the mean absolute error. The app also provides a visualization of rental trends and a summary of model performance metrics. This tool offers a user-friendly interface for predicting house rents based on key parameters.
This project is a Flood Prediction Web Application developed using Python, Flask, and a machine learning model. It allows users to predict the likelihood of a flood based on real-time input values such as rainfall and river level. The application utilizes a pre-trained machine learning model stored as a pickle file (PKL) and loaded using the Joblib library. The web interface, built with Flask, provides an input form where users can enter relevant data. Upon submission, the model processes the input and predicts whether a flood is likely or not. The prediction result is then displayed on the same page. The app is designed with a simple homepage and a /predict route to handle user inputs and generate predictions. It runs in debug mode for easy testing and modification. This project is useful for authorities, researchers, and individuals who want a quick and efficient way to assess flood risk based on environmental factors
This project is a Password Generator built using Python and the Tkinter library for a graphical user interface. It allows users to generate strong and secure passwords of customizable length with a simple and interactive interface. The application includes an input field where users specify the desired password length. Upon clicking the "Generate Password" button, the program creates a random password using uppercase and lowercase letters, numbers, and special characters to enhance security. The generated password is displayed on the screen, and users can easily copy it to the clipboard with a single click using the "Copy to Clipboard" button. The application starts in fullscreen mode to ensure a seamless experience but allows users to exit fullscreen by pressing the Escape key. This project is ideal for anyone needing a secure password quickly without relying on online tools. It is a simple yet effective solution for improving password security and ease of access.
The Ancient DNA Sequence Analysis API is a sophisticated bioinformatics tool built with FastAPI for forensic research on ancient alien DNA samples. This project provides an interactive and modular API that allows users to upload CSV files containing ancient DNA metadata, generate synthetic DNA sequences using seed data, compare sequence similarities, and even ask natural language questions about the API using the Google Gemini model. Key endpoints include /upload-csv for importing data, /generate-sequence for creating DNA from a seed, /compare-sequences for DNA similarity analysis, and /ask-me-anything for querying the API using everyday language. The system uses a custom K-mer algorithm for precise DNA comparison and supports debug endpoints for inspecting sample data. The application is structured into modular components such as main.py, dna_generator.py, and models.py, making it highly maintainable. To run the API locally, users must install dependencies from requirements.txt, configure their Google API key in a .env file, and launch the server using Uvicorn. This project is ideal for researchers needing a fast, flexible, and intelligent DNA analysis platform.
This project is a Currency Converter application built using Python's Tkinter library, providing a simple and intuitive graphical user interface (GUI) for real-time currency conversion. The user enters an amount in Indian Rupees (INR), and upon clicking the Convert button, the application displays the equivalent values in various global currencies including USD, EUR, GBP, PKR, AED, CAD, and JPY. The application utilizes predefined exchange rates (as of 2024-04-01) and performs calculations dynamically when the user inputs a valid number. If an invalid entry is provided, the application gracefully handles the error and alerts the user with a message. This project demonstrates essential concepts such as event handling, input validation, and the use of widgets like Entry, Button, and Label in Tkinter. It serves as a practical tool for understanding basic GUI development and working with real-world data processing. Overall, this currency converter is a functional and user-friendly Python project, offering both educational value and utility in currency comparison tasks.
This project is a Tic-Tac-Toe Game built using with Framer Motion for smooth animations. It provides an interactive and visually appealing experience while maintaining the core mechanics of the classic game. The game is played on a 3x3 grid, where two players take turns marking the squares as 'X' or 'O'. The state of the game is managed using React's useState hook. The game logic checks for a winner after each move by evaluating predefined winning combinations. If all squares are filled without a winner, the game ends in a draw. The UI includes a dynamic turn indicator, a responsive game board, and an animated winner announcement. The game features a reset button to start a new match instantly. Framer Motion is used to animate elements, creating smooth transitions and effects when the game state changes. This project demonstrates the power of React for state management and UI updates while incorporating animations for an engaging user experience.
This Android project is a simplified version of the popular Candy Crush game developed using Java and the Android SDK. The app features an 8x8 grid made with GridLayout, where each block is randomly filled with colorful candies. Players interact with the game by swiping the candies in four directions—left, right, up, and down—to match three candies of the same color in a row or column. The core game logic includes drag-and-swap mechanics, candy matching, score tracking, and automatic refill of blank slots. The game continuously checks for valid matches using a Handler and runs at a fixed interval to update the board state. If three candies match, they disappear, the score increases, and the candies above fall down to fill the gaps. The remaining empty slots are filled with new random candies to keep the game dynamic. This project demonstrates effective use of event listeners, UI manipulation, and logic-based gameplay in Android development, providing a solid foundation for building interactive and engaging mobile applications.
This project is a dynamic quiz web application developed using Express.js, with EJS as the templating engine. It focuses on delivering a smooth user experience by allowing users to attempt quizzes and instantly view results. The app architecture follows the MVC (Model-View-Controller) pattern, where all quiz logic is managed inside the quizController module. It serves static files from the public directory and utilizes body-parser middleware to handle form data. Users land on the home page ('/'), navigate to the quiz page ('/quiz') to attempt a test, and are then redirected to the results page ('/result') after submission. The core logic handles rendering quiz questions, processing answers, and evaluating results. This project helped strengthen my skills in server-side routing, form handling, middleware integration, and template rendering. It's a strong example of building a real-world application using Express.js and is easily scalable for features like database integration, user authentication, and score tracking. It plays a significant role in enhancing my backend development skills.
This project is a Rock-Paper-Scissors game developed using Python's Tkinter library to provide an interactive graphical user interface. It allows the user to choose between Rock, Paper, or Scissors while the computer makes a random choice. The game logic then determines the winner and updates the score accordingly. The interface includes buttons for each choice, a display area for results, and a live score tracker using IntVar and StringVar. The core logic handles all possible game scenarios including wins, losses, and draws, and visually reflects outcomes on the screen. The application also manages the game state by displaying dynamic messages based on each round’s result. This project helped me strengthen my understanding of Python functions, conditional logic, and most importantly, GUI development using Tkinter. It was an excellent exercise in combining event-driven programming with simple game mechanics, offering a fun and engaging way to practice Python. The project is lightweight, user-friendly, and demonstrates the foundational structure of desktop application development.
I worked at Excellence Technology PVT LTD from July 2023 to August 2023, where I gained hands-on experience in Python development. During this 45-day period, I focused on enhancing my programming skills, understanding core Python concepts, and working on real-world projects. I learned essential topics such as object-oriented programming. This experience helped me develop a strong foundation in Python and improve my problem-solving abilities. Additionally, I worked on practical applications, which deepened my understanding of coding best practices and debugging techniques. This internship played a crucial role in strengthening my programming expertise and preparing me for future development projects.
I started my training at QSpiders Training Institute, Noida in January 2025, focusing on Full-Stack Development and Data Analytics. This training will be completed by July 2025 and has been instrumental in enhancing my technical skills. During this period, I have learned essential technologies, including HTML, CSS, JavaScript, Python, Django, SQL, and Power BI. These skills have helped me build a strong foundation in web development, backend technologies, and data analysis. The training provides practical exposure to real-world projects, reinforcing my understanding of application development and data visualization. This experience is playing a crucial role in shaping my technical expertise for future career opportunities.
Email: mirzaumar089@gmail.com
Phone: +91 9086926363
LinkedIn: linkedin.com/in/umar-farooq-mirza
GitHub: github.com/UmarFarooqMirza