Camelia Simoiu, ASA
PhD Candidate

Management Science & Engineering Department
Stanford University

email: csimoiu [at] stanford [dot] edu

Curriculum Vitae


I am a PhD candidate at Stanford University in the Management Science and Engineering Department, working in the emerging area of computational social science. My research interests are in developing statistical methods and data-driven tools to evaluate and design effective public policy. Application areas of particular interest include behavioural and economic aspects of cyber security, as well as criminal justice. I draw on techniques from machine learning, Bayesian analysis, computational statistics, and social network analysis.

Previously, I was as a Fellow of the University of Chicago’s Data Science for Social Good program, and a visiting researcher at the MIT Media Lab in the Human Dynamics group. Prior to graduate school, I was a consulting actuarial analyst at Mercer, focusing on quantitative risk modeling. During my time there, I earned the ASA (Associate of the Society of Actuaries) designation, and initialized and taught a data analysis workshop for classes of 50 undegraduate students at the University of Toronto. I received a B.S. in applied statistics (actuarial science) from the University of Toronto and a M.S. in artificial intelligence from the University of Amsterdam.


A large-scale analysis of racial disparities in police stops across the United States [Under review]
With Emma Piersona, Jan Overgoor, Sam Corbett-Davies, Vignesh Ramachandran, and Cheryl Phillips.

The Problem of Infra-marginality in Outcome Tests for Discrimination
With Sharad Goel and Sam Corbett-Davies. Under review.
raw data | clean data | code | slides

Investing the Wisdom of the Crowds at Scale ACM UIST 2015, Charlotte, NC.
With Mysore A. et. al.

Understanding and Improving Energy Consumption in Commercial Buildings, Knowledge Discovery and Data Mining conference, 2013
With Scott Alfeld, and Andrea Fernandez-Conde, poster with oral presentation

In the News

08/16 Vox. Study: police officers have lower standards for searching black people than white people
06/16 Stanford researchers develop new statistical test that shows racial profiling in police traffic stops
02/16 Stanford Traffic Stops Database Will Let Public Analyze Racial Profiling
02/16 Engineers battle bias in the criminal justice system
02/16 Stanford engineers' 'Law, Order & Algorithms' data project aims to identify bias in the criminal justice system
07/13 New Data Project Seeks to Raise Investor Confidence in Energy Efficiency

11/16 Invited talk at TEDxBeaconStreet Conference (Nov 19, 2016)
09/16 Our paper "A large-scale analysis of racial disparities in police stops across the United States" accepted for presentation at the Computation + Journalism 2016 Conference at Stanford
09/16 Awarded ACCEL Fellowship, courtesy of the MS&E Department, Stanford
08/16 Our paper "Testing for Racial Discrimination in Police Searches of Motor Vehicles" voted most interesting papers on arXiv (week 08/06)
08/16 Invited talk at JSM 2016 on the threshold test
07/16 Invited talk at CSS 2016 on the threshold test (Security and Crime section)
03/16 Awarded ACCEL Fellowship, courtesy of the MS&E Department, Stanford
02/16 Selected as one of RSA Scholars. Courtesy of the Cyber Initiative, Stanford
06/15 Winner of the Knight News Challenge on our project Law, Order & Algorithms. With Sharad Goel, Sam Corbett-Davies, Ravi Shroff, and Vignesh Ramachandran
11/15 Invited poster with oral presentation at ACM UIST 2015 on collective intelligence
02/15 Serving as local chair for COSN 2015
02/15 Excited to lead the data science team of the Aspiring Researcher Challenge along with Sharad Goel, Rajan Vaish, and Imanol Arrieta Ibarra