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, advised by Professor Sharad Goel. My research interests are in developing novel statistical methods to evaluate and design effective public policy in the areas of cyber security and criminal justice. I draw on techniques from machine learning, Bayesian analysis, computational statistics, and social network analysis.

Previously, I was 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. I received a B.S. in applied statistics from the University of Toronto and a M.S. in artificial intelligence from the University of Amsterdam.


At risk of ransomware: A behavioral analysis of web browsing habits [Work in progress]
Camelia Simoiu, Joseph Bonneau, Sharad Goel

The effects of social influence on collective intelligence [Work in progress]
Camelia Simoiu, Chiraag Sumanth, Alok Mysore, Sharad Goel

Crowd Research: Open and Scalable University Laboratories. UIST 2017.
with Rajan Vaish, Michael Bernstein, Geza Kovacs, et. al.

A large-scale analysis of racial disparities in police stops across the United States [Under review]
Emma Pierson, Camelia Simoiu, Jan Overgoor, Sam Corbett-Davies, Vignesh Ramachandran, Cheryl Phillips.
Stanford Open Policing project | data | code | news

The Problem of Infra-marginality in Outcome Tests for Discrimination. Annals of Applied Statistics, 2017.
Camelia Simoiu, Sam Corbett-Davies, Sharad Goel.
data | code | slides

Investing the Wisdom of the Crowds at Scale UIST 2015
Alok Shankar Mysore, Vikas S. Yaligar, Imanol Arrieta Ibarra, Camelia Simoiu, Sharad Goel, et al.

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

In the News

08/17 The Daily Show. A Stanford University study uncovers racial disparity in routine traffic stops
06/17 The Economist. Measuring racial bias in police forces
06/17 NBC News. Police searches drop dramatically in states that legalized marijuana
06/17 The Daily Mail. Police officers are more likely to cite black or Latino drivers than whites during traffic stops

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

10/17 Invited talk at CODE (Conference On Digital Experimentation) on collective intelligence.
07/17 Excited to be joining Symantec this summer for a research internship.
07/17 Leading a data science workshop at IRE 2017 Investigative Reporters and Editors Conference
05/17 Invited to attend the GREPSEC III Workshop on computer security research.
05/17 Invited talk at the Wolrd Economic Forum's Cyber Risk Quantification Workshop (May 11-12, 2017)
11/16 New blog post on Bayesian statistics: A bag of tips and tricks for dealing with scale issues with Jim Savage
11/16 Invited talk at TEDxBeaconStreet Conference
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