Bo Jiang is a Research Assistant Professor in the Department of Sociology at The Chinese University of Hong Kong.  He is largely interested in applying methods from computational sciences to address policy-relevant issues within criminology and sociology.

Jiang’s work is represented by his 2017 article on social control, trade openness and human trafficking.  He developed a macro-level social disorganization perspective and discovered an inverted-U relationship between trade openness and human trafficking.  In his 2019 study on prison and violent extremism in the United States, he found consistent evidence that politically motivated extremists who have spent time in prison and were radicalized there are more likely to engage in violent political extremism post prison.  His work has been published in the Journal of Quantitative Criminology.

Jiang’s recent projects include 1) machine learning and big data for predictive modelling of terrorist organizations using the Global Terrorism Database, and 2) quantifying the impact of popularity on Twitter for religiously motivated terrorist organizations.  He is also interested in the consequences of these issues for public policy.

Mentored by Gary LaFree, Jiang earned a PhD from the Department of Criminology and Criminal Justice at the University of Maryland where he spent five years at the National Consortium for the Study of Terrorism and Responses to Terrorism (START).  Jiang was the First Place Winner of the American Society of Criminology, Division of International Criminology Student Paper Competition (Doctoral Program) and the recipient of University of Maryland’s Outstanding Graduate Assistant Award.  Prior to joining The Chinese University of Hong Kong, he held faculty positions at the National University of Singapore, George Washington University and University of Maryland.  Since 2018, Jiang has held an appointment with the Institute of Criminology, University of Cambridge as a Data Analysis Consultant. He has advanced the application of criminology to public policy.