Software Developer | AI & Full-Stack Engineer
Building intelligent systems that solve real problems.
I build end-to-end AI solutions — from data pipelines and deep learning models to scalable web applications.
About
I'm a Computer Engineering undergraduate with a strong focus on AI systems, computer vision, and full-stack development. I enjoy building end-to-end solutions — from designing data pipelines and training deep learning models to deploying scalable web applications.
My work spans fraud detection, image restoration, crop disease detection, and AI-powered financial tools, with hands-on experience in TensorFlow, PyTorch, Next.js, and cloud-native tooling. I value performance, interpretability, and real-world deployability over purely academic models.
Currently, I'm working as a Research Fellow under the TIH IIT Bombay CHANAKYA Fellowship, developing image-based crop disease detection systems validated through field trials.
Featured Projects
Taal-AI
AI financial coaching platform with income rhythm analysis, purchase impact simulation, and LLM-based guidance. Features 100% typed APIs with modular agent architecture and WhatsApp integration for real-time tax reminders.
Credit Card Fraud Detection & Behavior Analysis
Multi-model fraud detection pipeline achieving 74.4% accuracy on 10,000+ transactions. Improved AUC-ROC by 15% using feature engineering and optimized processing to under 30 seconds per batch.
AI Reflection Remover
Deep learning model for image reflection removal using CNNs. Achieved 26.64 dB PSNR and 0.9207 SSIM on validation, with test performance of 27.82 ± 3.33 dB PSNR. Finalist at Qualcomm VisionX Hackathon (IIT Bombay).