Hi, I'm
Vansh Badjate
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B.Tech student specializing in AI & Machine Learning at Sanjivani University. Building intelligent solutions with Computer Vision and Deep Learning.
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Hi, I'm
B.Tech student specializing in AI & Machine Learning at Sanjivani University. Building intelligent solutions with Computer Vision and Deep Learning.
Scroll Down
I'm a third-year B.Tech student specializing in Artificial Intelligence & Machine Learning at Sanjivani University, Kopargaon. With a strong foundation in computer science and a passion for AI, I'm dedicated to building intelligent systems that solve real-world problems.
My expertise spans Computer Vision, Deep Learning, and Machine Learning. I've developed projects ranging from real-time threat detection systems to healthcare AI applications, always focusing on creating impactful solutions.
Beyond academics, I actively participate in hackathons and continuously expand my knowledge through hands-on projects and internships. I'm driven by curiosity and the desire to push the boundaries of what's possible with AI.
Hackathon Participant
Internship Experience
Sanjivani University, Kopargaon
2024 - 2027
Sanjivani K.B.P. Polytechnic, Kopargaon
2021 - 2024
S.G.Vidyalaya, Kopargaon
2021
A collection of my work in AI, Computer Vision, and Web Development
Real-time smart CCTV threat detection system with weapon detection, masked individual identification, and automated alert mechanisms for enhanced security.
Image-based skin cancer classification system using deep learning to identify cancer types (AK, BCC, SK) with confidence scores and heatmap visualization.
Smart crop yield forecasting platform using ML with real-time weather monitoring and multilingual voice assistant for enhanced accessibility.
AI-powered educational platform using Google Gemini to generate personalized learning paths. Features social community for sharing roadmaps and trending paths.
State-of-the-art deepfake detection using Vision Transformers and EfficientNetV2 ensemble. Built with PyTorch and MediaPipe for robust real-time detection.
Real-time facial emotion recognition using computer vision pipeline with classical detection and deep learning-based classification for instant feedback.
Have a project in mind? Let's discuss how we can work together.