I am a Computer Science undergraduate focused on backend engineering and system design, with hands-on experience building scalable software, machine learning systems, and real-time applications. I enjoy translating complex problem statements into clean, production-ready solutions while continuously improving my technical depth and problem-solving skills.

Deepfake Detection System — Designed and implemented a deepfake detection pipeline using convolutional autoencoders and deep learning techniques. The system performs face detection, preprocessing, feature extraction, and classification to distinguish real and manipulated media, with support for both image and video inputs. Emphasis was placed on robustness and model explainability using Grad-CAM to improve real-world reliability.

Speech Emotion Recognition (SER) System — Built a speech emotion recognition system using a hybrid CNN–LSTM architecture for effective temporal and spectral feature learning. The solution processes raw audio signals to classify emotional states and is tailored for Indian language datasets. Delivered as a full-stack application with Streamlit frontend, Flask backend, and MongoDB to enable scalable emotion analytics.

Cybercrime Investigation Dashboard — Developed a cybercrime investigation dashboard using the MERN stack to support law enforcement workflows. The platform correlates suspect data, call patterns, emotional indicators, and anomaly signals using unique case identifiers. Focused on modular backend APIs, intuitive data visualization, and extensible system design for investigative analysis.