Co-Founder
Echotrack
1. Built an end-to-end machine learning platform for acoustic image data, including data collection, processing, training, and real-time inference.2. Trained models like ResNet, MobileNet, and Transformers for human body pose, facial expression, and activity recognition using acoustic signals. Utilized data augmentation and masking techniques to createstate-of-the-art systems, achieving 90%+ accuracy on most tasks.3. Secured $240,000 in funding from Cornell University and $50,000 from National Science Foundation.