I am a Final Year Computer Science and Engineering student at United Institute of Technology, Prayagraj, with a strong interest in Software Development, Machine Learning, and Full Stack Web Development.
I enjoy building practical software that combines clean user interfaces with efficient backend systems. My projects have given me hands-on experience in computer vision, machine learning, natural language processing, and REST API development using Python and JavaScript technologies.
Alongside development, I actively improve my problem-solving skills through competitive programming and continuously explore modern technologies by building real-world projects.
- Building practical AI-powered applications
- Full Stack Web Development
- Machine Learning
- Computer Vision
- Competitive Programming
- Software Development Internships
- AI / Machine Learning Internships
- Frontend Development Roles
- Open Source Collaboration
| Domain | Experience | Tools |
|---|---|---|
| Data Analysis | Intermediate | Pandas, NumPy |
| Machine Learning | Intermediate | Scikit-Learn, XGBoost |
| Computer Vision | Intermediate | OpenCV, MediaPipe |
| NLP | Beginner | TF-IDF, Scikit-Learn |
| Model Deployment | Intermediate | Flask, Streamlit |
🖐 AI Gesture Volume Control
A real-time computer vision application that detects hand gestures through a webcam and controls Windows system volume without requiring physical interaction.
| Category | Details |
|---|---|
| Stack | Python, OpenCV, MediaPipe, Pycaw, NumPy |
| Type | Computer Vision |
| Features | Hand Tracking, Finger Detection, Real-time Volume Control |
| Platform | Windows |
- Detects hand landmarks using MediaPipe.
- Calculates finger distance to adjust system volume.
- Uses smoothing to reduce abrupt volume changes.
- Runs completely in real time using webcam input.
🔗 Repository (https://github.com/dhriti09/Gesture-Volume-Control.git)
📰 Fake News Detector
A machine learning application that classifies news articles as Real or Fake using Natural Language Processing techniques.
| Category | Details |
|---|---|
| Stack | Python, Scikit-Learn, TF-IDF, Streamlit |
| Type | NLP |
| Features | Text Classification, Data Preprocessing, Web Interface |
- Cleaned and preprocessed textual datasets.
- Extracted features using TF-IDF Vectorizer.
- Trained a Scikit-Learn classification model.
- Built an interactive Streamlit application for prediction.
🔗 Repository
https://fake-news-detector-gh5ey3pw29ext2ppkshyrz.streamlit.app/
🌫 Air Quality Index Predictor
A full-stack web application that predicts Air Quality Index (AQI) using machine learning and environmental datasets.
| Category | Details |
|---|---|
| Stack | Python, Flask, XGBoost, React, REST API |
| Type | Machine Learning |
| Features | AQI Prediction, Flask API, React Dashboard |
- Processed environmental datasets using Pandas and NumPy.
- Trained an XGBoost regression model.
- Developed REST APIs using Flask.
- Connected the backend with a React frontend.
🔗 Live Demo
🚧 Currently Building — Hyperlocal Festive-Aware Demand AI
Work In Progress
Developing an AI-powered demand forecasting system to estimate product demand during festive seasons using historical trends and contextual retail data.
- Python
- Pandas
- NumPy
- Scikit-Learn
- Flask
- React
To build a practical machine learning solution that can help small retailers make better inventory decisions during high-demand festive periods.
June 2025 – July 2025
Worked on backend development for web applications while collaborating with the development team to improve application functionality and maintain code quality.
- Developed backend APIs to support web application features.
- Integrated databases for efficient data storage and retrieval.
- Used Git for version control and collaborative development.
- Assisted in debugging and improving backend functionality.
Skills: Flask • REST APIs • Git • Backend Development • Database Integration
June 2023 – July 2023
Completed institutional training focused on Python programming fundamentals and problem-solving.
- Core Python Programming
- Data Structures
- Object-Oriented Programming
- Problem Solving
- Programming Fundamentals
| Achievement | Details |
|---|---|
| 🧩 Competitive Programming | Solved 200+ Data Structures & Algorithms problems across LeetCode and CodeChef. |
| 🏅 LeetCode | Achieved a 1625 rating. |
| ⭐ CodeChef | Earned a 2★ rating with a peak rating of 1542. |
| 🏆 Coding Competition | Winner of E-BOX Top Coders 2025–26. |
Learning:
- Advanced Data Structures & Algorithms
- Full Stack Development
- Machine Learning
- System Design Fundamentals
Building:
- Hyperlocal Festive-Aware Demand AI
Exploring:
- Computer Vision
- Model Deployment using Flask & Streamlit
- Open Source Contributions
Open To:
- Software Development Internships
- AI / Machine Learning Internships
- Frontend Development Roles