Riccardo Fogliato (original) (raw)
I am an applied scientist at Amazon Web Services working on issues around Responsible AI. In July 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, and I spent seven months working as a research fellow at the Partnership on AI with Alice Xiang. Before joining CMU for my graduate studies, I was a student at the Collegio Carlo Alberto and at the University of Torino, where I was advised by Matteo Ruggiero. I received my ungraduate degree from the University of Padova, with an Erasmus exchange at the École Normale Supérieure de Cachan.
I am broadly interested in the application of statistical machine learning methods to the social sciences. My current research is driven by the following two questions:
• How does sampling bias affect the data on which risk assessment instruments are trained and and what are its consequences?
• How do experts integrate the recommendations made by risk assessment instruments into their decision-making processes?
You can contact me at riccardofogliato [at] gmail [dot] com.
When I'm not injured, I run and log some miles (kms) on Strava.
- 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
: anR
implementation of Models As Approximations
Riccardo Fogliato*, Shamindra Shrotriya*, and Arun Kumar Kuchibhotla (* co-first)
GitHub arXiv talk @ useR!2021
Publications
- 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 pdf 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 2020workshop - 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 - 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 AIissue brief