Causal Inference

Dynamic Causal Graph Convolutional Network for Traffic Prediction

Peter Luh Best Memorial Award for Young Researcher

MM-DAG: Multi-task DAG Learning for Multi-modal Data--with Application for Traffic Congestion Analysis

This paper proposes to learn Multi-task, Multi-modal Direct Acyclic Graphs (MM-DAGs), which are commonly observed in complex systems, e.g., traffic, manufacturing, and weather systems, whose variables are multi-modal with scalars, vectors, and …

Advanced Machine Learning for Smart Transportation (with GaTech)

Intelligent Transport Systems (ITS) have been an essential chapter in smart city blueprint. There are numbers of real practical applications of ITS: For instance, when you are driving on the road, the ITS could predict how crowded the traffic will be …