Vedika Sood

I’m a motivated, detail-oriented CSE student with a strong interest in AI and software development. I enjoy turning structured logic into practical systems, especially where NLP and deep learning can make information more usable and decisions more accurate.

Through academic projects, I built end-to-end solutions like SmartTraffic Parking Management to monitor slot availability and support efficient space allocation using structured data handling. I also developed an AI-Powered Document Intelligence system that extracts and summarizes key information using NLP techniques and transformer models, including BERT. For deep learning, I created a Brain Tumor Detection model using TensorFlow, CNN, and OpenCV to classify MRI images, and a Mental Health Prediction model using machine learning to predict risks from user data.

I strengthen my foundation with targeted certifications in AI/ML, Data Science and Machine Learning, Deep Learning Tutorials, and Explore Machine Learning using Python, along with Database and SQL. My goal is to keep improving model performance while also writing clean, maintainable code in real development workflows.

I also bring teamwork and leadership to projects—serving as a Member in the IILM Discipline Committee and as a Coordinator for the Deeksharambh Registration & Orientation Program. I’m excited to collaborate with teams and keep building real-world AI applications while learning fast through practice and feedback.