Riccardo Fogliato
I am an applied scientist at Amazon Web Services working on statistical methods for computer vision and Responsible AI. In 2022, I completed a PhD in Statistics at Carnegie Mellon University under the supervision of Alexandra Chouldechova and Zachary Lipton.
During the PhD, I interned at Microsoft Research working with Besmira Nushi, Kori Inkpen, and Eric Horvitz. I also spent seven months as a research fellow at the Partnership on AI with Alice Xiang. Prior to my graduate studies at CMU, I was a student at the Collegio Carlo Alberto and the University of Torino, where I was advised by Matteo Ruggiero. I received my undergraduate degree from the University of Padova, with an Erasmus exchange at the École Normale Supérieure de Cachan.
You can contact me at riccardofogliato [at] gmail [dot] com.
When I'm not injured, I run and log some miles (kms) on Strava.
Working papers
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A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation
Riccardo Fogliato, Pratik Patil, Mathew Monfort, Pietro Perona (To appear at ECCV 2024) arXiv -
A Case for Humans-in-the-Loop: Decisions in the Presence of
Misestimated Algorithmic Scores
Riccardo Fogliato*, Maria De-Arteaga*, and Alexandra Chouldechova (*co-first) SSRN -
maars: anRimplementation of Models As Approximations
Riccardo Fogliato*, Shamindra Shrotriya*, and Arun Kumar Kuchibhotla (*co-first) code arXiv talk
Publications
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Multicalibration for Confidence Scoring in
LLMs
Gianluca Detommaso, Martin Bertran*, Riccardo Fogliato*, Aaron Roth
ICML 2024 arXiv -
Confidence Intervals for Error Rates in 1:1 Matching
Tasks: Critical Statistical Analysis and
Recommendations
Riccardo Fogliato, Pratik Patil, Pietro Perona
International Journal of Computer Vision arXiv (w/ power analysis in C.5) IJCV code PyPI - Estimating the Likelihood of Arrest from Police
Records in Presence of Unreported Crimes
Riccardo Fogliato, Arun Kumar Kuchibhotla, Zachary Lipton, Daniel Nagin, Alice Xiang, and Alexandra Chouldechova
Annals of Applied Statistics arXiv AOAS code - The Progression of Disparities within the Criminal
Justice System: Differential Enforcement and Risk Assessment
Instruments
Miri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher, Carolyn Ashurst, Adrian Weller
FAccT 2023 arXiv - Homophily and Incentive Effects in Use of
Algorithms
Riccardo Fogliato, Sina Fazelpour, Shantanu Gupta, Zachary Lipton, David Danks
CogSci 2022 arXiv - Who Goes First? Influences of Human-AI Workflow on
Decision Making in Clinical Imaging
Riccardo Fogliato, Shreya Chappidi, Michael Fitzke, Mark Parkinson, Diane Wilson, Paul Fisher, Matthew Lungren, Eric Horvitz, Kori Inkpen, Besmira Nushi
FAccT 2022 arXiv platform - Racial Disparities in the Enforcement of Marijuana
Violations in the US
Bradley Butcher, Chris Robinson, Miri Zilka, Riccardo Fogliato, Carolyn Ashurst, Adrian Weller
AIES 2022 arXiv code - On the Validity of Arrest as a Proxy for Offense:
Race and the Likelihood of Arrest for Violent Crimes
Riccardo Fogliato, Alice Xiang, Zachary Lipton, Daniel Nagin, Alexandra Chouldechova
AIES 2021 (oral) arXiv ACM code - The Impact of Algorithmic Risk Assessments on
Human Predictions and its Analysis via Crowdsourcing Studies
Riccardo Fogliato, Alexandra Chouldechova, Zachary Lipton
CSCW 2021 arXiv ACM data+code - Uncertainty as a Form of Transparency: Measuring,
Communicating, and Using Uncertainty
U. Bhatt, Y. Zhang, J. Antorán, Q.V. Liao, P. Sattigeri, R. Fogliato, G.G. Melançon, R. Krishnan, J. Stanley, O. Tickoo, L. Nachman, R. Chunara, A. Weller, A. Xiang
AIES 2021 arXiv ACM - Lessons from the Deployment of an Algorithmic Tool
in Child Welfare
Riccardo Fogliato*, Maria De-Arteaga*, Alexandra Chouldechova (*co-first)
Fair & Responsible AI Workshop, CHI 2020 workshop - A Case for Humans-in-the-Loop: Decisions in the
Presence of Erroneous Algorithmic Scores
Maria De-Arteaga*, Riccardo Fogliato*, Alexandra Chouldechova (* co-first)
CHI 2020 arXiv ACM Medium post - Fairness Evaluation in the Presence of Biased
Noisy Labels
Riccardo Fogliato, Max G'Sell, Alexandra Chouldechova
AISTATS 2020 arXiv PMLR - TRAP: A Predictive Framework for Trail Running
Assessment of Performance
Riccardo Fogliato, Natalia L. Oliveira, Ronald Yurko
Journal of Quantitative Analysis in Sports arXiv JQAS Talk @ MIT SSAC
† Best poster award at NESSIS 2019 and at CMSAC 2019 (1 of 4) poster - Trajectories of Prescription Opioids Filled Over
Time
J. Elmer, R. Fogliato, N. Setia, W. Mui, M. Lynch, E. Hulsey, D. Nagin
PLOS one 2019 PLOS
Other
- Why PATTERN Should Not Be Used: The Perils of
Using Algorithmic Risk Assessment Tools During COVID-19
Riccardo Fogliato, Alice Xiang, Alexandra Chouldechova
Issue brief of the Partnership on AI issue brief