Cynthia Chen

Machine Learning in Transportation: Learning Mobility Patterns from Big Data

2020 Responsible Machine Learning Summit: AI and COVID-19

 

Cynthia Chen
Cynthia Chen, Professor, Civil and Environmental Engineering, University of Washington

Machine Learning in Transportation: Learning Mobility Patterns from Big Data

Abstract: This talk will introduce location- and time-relevant data used for inferring individual activity and travel patterns, which are crucial for effective contact tracing. Specifically, the talk will focus on data related issues in inferring mobility patterns, followed by some suggestions relating to fairness in AI/ML. 

Biography: Cynthia Chen is a professor in the department of civil and environmental engineering at the University of Washington, Seattle (UW). At UW, she directs the THINK (Transportation-Human Interaction-and- Network Knowledge) lab. Research at the THINK lab seeks to re-design our urban spaces and built systems (whether that is a transportation system or others) that can adapt to a variety of conditions by both answering fundamental scientific questions and also producing actionable technologies that can make a difference in the real world. More specifically, the current research at the THINK lab focuses on understanding data, modeling behaviors of individuals (mobility patterns) and networks (e.g., cascading processes), and designing interventions for modifying individual behaviors and network phenomena. Common to these threads is the development of innovative methodologies. Dr. Chen graduated from University of California, Davis with a PhD in civil and environmental engineering in 2001 and was an assistant professor with City College of New York between 2003 and 2009.