Computer science Ph.D. student Reza Asadi and Professor of Computer Science and Transportation Systems Engineering Amelia Regan won the Best Paper Award at the ACM SIGSPATIAL Workshop on Prediction of Human Mobility (PredictGIS) on Nov. 5, 2019 for their paper, “Spatio-Temporal Clustering of Traffic Data with Deep Embedded Clustering.”

Asadi’s dissertation is concerned with neural network models for spatio-temporal data forecasting and analysis. Short-term traffic prediction is an example of a problem with complex spatio-temporal data, and multivariate time-series data with spatial similarities. “In this paper, we formulate a spatio-temporal clustering problem and define temporal and spatial clusters,” says Regan, “then we propose an approach for finding temporal and spatial clusters with a deep embedded clustering model.” Because of the award, an extended version of the paper will also be published in ACM Transactions on Spatial Algorithms and Applications.

— Shani Murray