Research Area

We develop accurate, hardware friendly and privacy/power consumption-aware on-device AI systems for natural language processing and medical imaging processing.

We develop spatial-temporal machine learning models and online algorithms to leverage the geocoded IoT data for learning feature representation, forecast and anomaly detection.

We design fairness-aware decision support system to address the sampling, social, algorithmic biases in predictive analytics.

We develop medical AI system to automatic interpret medical images with visual aid by exploiting convolutional and recurrent neural networks to extract visual and textual features.

We use domain knowledge in the format of meta-data to design interpretable feature mapping and learning approaches for explainable and personalized recommendation.

We apply 4D CNN model and algorithm to learn the key developmental features from fMRI images.

We employ natural language generation models to develop context-aware and location-based conversational agent.