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)
  • maars: an R implementation of Models As Approximations
    Riccardo Fogliato*, Shamindra Shrotriya*, and Arun Kumar Kuchibhotla (* co-first)
    GitHub arXiv talk @ useR!2021


  • 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. AntorĂ¡n, 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
  • 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