I'm Fowzaan Rasheed, a passionate Computer Science student specializing in AI/ML and Full Stack. I thrive on building innovative solutions that make a difference, and I'm constantly exploring new technologies to push the boundaries of what's possible.

• 🎓 I'm currently pursuing a B.E. in Computer Science & Engineering at Madras Institute of Technology
• 🌱 I’m currently diving into the MERN stack to expand my web development skills
• 💻 I have a strong passion for AI/ML and have built several projects in this domain
• 📫 How to reach me: fowzaan.rasheed@gmail.com

Here are some of the key projects I've worked on:

1. Travel Planner AI

   • Developed a Python-based travel planning tool integrating OpenAI, Google PaLM, and Google Maps APIs to generate detailed itineraries with visualized routes based on user preferences.

2. Drug Interaction Checker

   • Built a Next.js-based website that allows users to check potential drug interactions, integrating MongoDB and Python for efficient data management and interaction results.

3. Gym Workout Tracker

   • Developed a gym workout app that leverages an API from RapidAPI to provide users with a variety of exercises tailored to their fitness goals.

4. Customizable URL Classifier

   • Created a hybrid CNN/LSTM model for URL classification, achieving 87.4% accuracy by leveraging custom feature extraction methods to categorize URLs into various security-related categories.

5. Energy Consumption Predictor

   • Implemented a machine learning model to forecast electricity production and detect anomalies using time-series analysis, achieving an R² score of 0.91 on a dataset with over 121,000 data points.

6. OffBoard UAV Path Planning

   • Proposed an off-board path planning system using advanced image segmentation and DBSCAN-PP clustering to optimize UAV-BS deployment in disaster areas, enhancing efficiency and flight time.

7. GAN Face Generator

   • Developed a GAN-based model to generate realistic celebrity face images using the CelebA dataset. Leveraged adversarial training techniques to enhance the quality of synthetic images, addressing challenges like computational overhead and stability issues.

8. DriveMind

   • Developed a real-time task management system using an ESP32 processor, dynamically adjusting task priorities based on real-time factors. Implemented with FreeRTOS for efficient task handling simulated via Wokwi.

• Programming: Python, Java, C++, C, JavaScript
• AI/ML Tools: TensorFlow, Keras, Scikit-learn, PyTorch
• Web Development: HTML/CSS, MERN Stack (in progress)
• Developer Tools: Git, Jupyter Notebook, Visual Studio, Colab
• Database: SQL, MongoDB

• LinkedIn
• GitHub