Hi, I'm Garv Anand

Built a multimodal deep learning framework aimed at enhancing student engagement and actionable insights in virtual classrooms. The system integrates Bi-LSTM, CNN, and Transformer-based architectures to effectively extract and analyze emotional cues—acoustic, semantic, and linguistic—from both voice and video data. Leveraged the RAVDESS and CREMA-D datasets.

Developed a comprehensive platform during a HackByte 3.0 at IIITDM Jabalpur that combines daily health monitoring (Google Fit sync, water and fasting trackers) with real-time disease risk prediction using Random Forest models. Designed intuitive UI dashboards and Flask APIs to visualize health trends, flag risks, and recommend doctor visits based on combined vitals and diagnostic results.

Built a platform to streamline the university’s document approval process by enabling online submission, tracking, and feedback—cutting approval time from days to hours and eliminating repeated physical visits.