Riccardo Fogliato

Portrait of Riccardo Fogliato

I am a principal research scientist on the Responsible AI team at Microsoft Core AI, working on testing of LLM safety. Previously, I was an applied scientist on the Responsible AI team at AWS, where I worked on statistical methods for evaluating language and vision models.

I received a PhD in Statistics from CMU under the supervision of Alexandra Chouldechova and Zachary Lipton. During the PhD, I interned at MSR with Besmira Nushi, Kori Inkpen, and Eric Horvitz. I also was a research fellow at the Partnership on AI where I worked with Alice Xiang. Before going to CMU, I studied at Collegio Carlo Alberto, at the Universities of Torino and Padova, and spent some time at ENS Cachan.

You can contact me at riccardofogliato [at] gmail [dot] com.

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Recent Publications

Earlier publications (2019–2023)
  • The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments
    M. Zilka, R. Fogliato, J. Hron, B. Butcher, C. Ashurst, A. 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
  • Human Discernment of Algorithmic Errors: A Case Study in Child Welfare
    Maria De-Arteaga*, Riccardo Fogliato*, Alexandra Chouldechova
    SSRN
  • Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging
    R. Fogliato, S. Chappidi, M. Fitzke, M. Parkinson, D. Wilson, P. Fisher, M. Lungren, E. Horvitz, K. Inkpen, B. 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
  • maars: an R implementation of Models As Approximations
    Riccardo Fogliato*, Shamindra Shrotriya*, Arun Kumar Kuchibhotla arXiv code talk
  • 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
  • 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
  • Lessons from the Deployment of an Algorithmic Tool in Child Welfare
    Riccardo Fogliato*, Maria De-Arteaga*, Alexandra Chouldechova
    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 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)
  • 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