Camelia Simoiu, ASA
Management Science & Engineering Department
email: csimoiu [at] stanford [dot] edu
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 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.
At risk of ransomware: A behavioral analysis of web browsing habits [Work in progress]
with Joseph Bonneau and Sharad Goel
Collective intelligence: an at-scale analysis [Work in progress]
with Chiraag Sumanth, Alok Mysore, and Sharad Goel
Crowd Research: Open and Scalable University Laboratories. Forthcoming, UIST 2017.
Rajan Vaish, Michael Bernstein, Sharad Goel, Geza Kovacs, Ranjay Krishna, Camelia Simoiu, Imanol Arrieta Ibarra, Michael Wilber, Andreas Veit, Serge Belongie, James Davis, Snehalkumar (Neil) Gaikwad
A large-scale analysis of racial disparities in police stops across the United States [Under review]
Emma Piersona, Camelia Simoiu, Jan Overgoor, Sam Corbett-Davies, Vignesh Ramachandran, and Cheryl Phillips.
Stanford Open Policing project |
The Problem of Infra-marginality in Outcome Tests for Discrimination. Forthcoming, Annals of Applied Statistics, 2017.
Camelia Simoiu, Sam Corbett-Davies, Sharad Goel.
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
08/16 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