Jason Weng

Spearheaded and implemented a machine learning model utilizing a vector quantized variational autoencoder to categorize human motion capture sequences with an accuracy rate >90%. Successfully deployed the model onto an internal database, enabling artists to efficiently locate clips featuring specific actions.