Research

Cross-Disciplinary Data-Driven Research

Data revolutionizes all research fields.
I am curious how data make new discoveries across a variety of fields and how data make changes in the real world.

I develop computational techniques to release the power of data.

traffic light, traffic signal, stoplight-514932.jpg

Pioneer in the research topic on reinforcement learning for traffic signal control

Traffic Signal Control

Selected Publications

Intellilight: A reinforcement learning approach for intelligent traffic light control (KDD 2018)

Presslight: Learning max pressure control to coordinate traffic signals in arterial network (KDD 2019)

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario (WWW 2019)

Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control (AAAI 2020)

Recent Advances in Reinforcement Learning for Traffic Signal Control: A Survey of Models and Evaluation (SIGKDD Explorations 2020)

Collaborations

Vikash Gayah, Civil Engineering, Penn State

Traffic policy makers in Hangzhou, Nanchang, Wuxi

Big data analysis for water quality in the area of shale gas development

Environment

Selected Publications

Searching for Anomalous Methane in Shallow Groundwater near Shale Gas Wells (Journal of Contaminant Hydrology 2016)

Contextual Spatial Outlier Detection with Metric Learning (KDD 2017)

Big groundwater data sets reveal possible rare contamination amid otherwise improved water quality for some analytes in a region of Marcellus Shale development (Environmental Science & Technology 2018)

Knowledge-based Residual Learning (IJCAI 2021)

Collaborations

Susan Brantley, Geosciences, Penn State

Tao Wen, Earth and Environmental Sciences, Syracuse University