I am a doctoral candidate in computer science at Stanford, advised by Professors Sherri Rose and Carlos Guestrin, and a member of the Health Policy Data Science Lab. The defense of my thesis, titled Statistical and mixed-methods approaches for analyzing health equity consequences of the use of medical algorithms, is scheduled for the summer of 2025.

My interdisciplinary research draws from machine learning, biostatistics, decision science, health services research, social epidemiology and community engaged research to study how statistical models used in US primary care affect health inequities, and how to build systems which alleviate, rather than exacerbate them.

Previously at Stanford, I have been a member of the Shah lab, a Technology & Racial Equity graduate fellow at the Center for Comparative Studies in Race and Ethnicity, and a McCoy Family Center for Ethics in Society graduate fellow.

Ongoing projects

A microsimulation-based framework for mitigating societal bias in primary care data
Agata Foryciarz, Fernando Alarid-Escudero, Gabriela Basel, Marika Cusick, Robert L. Phillips, Andrew Bazemore, Alyce S. Adams, Sherri Rose

We are developing a novel microsimulation-based framework for attenuating societal bias in chronic kidney disease progression data from a large primary care registry. This allows us to generate counterfactual outcome distributions, reflecting rates of end-stage renal disease that would have been observed in the absence of race-based diagnosis and treatment criteria. Our framework could flexibly be adapted to mitigate bias in other health data.

• Joint Statistical Meetings 2024 Invited Paper [slides]

A participatory approach for understanding social drivers of chronic kidney disease progression
Agata Foryciarz, Lisa Goldman Rosas, Oshra Sedan, Sherri Rose

We are conducting a participatory research study to understand specific ways in which social factors (e.g. housing, transportation, adverse experiences, access barriers, direct discrimination) impact chronic kidney disease patients’ ability to manage their condition. In a series of model building workshops, participants are guided through a multi-step process of constructing a causal loop diagram representing social factors and their interactions.

Selected Academic Publications

Incorporating area-level social drivers of health in predictive algorithms using electronic health record data
Agata Foryciarz, Nicole Gladish, David H. Rehkopf, Sherri Rose
Under review
[preprint]

Evaluating algorithmic fairness in the presence of clinical guidelines: the case of atherosclerotic cardiovascular disease risk estimation
Agata Foryciarz, Stephen R. Pfohl, Birju Patel, Nigam H. Shah
BMJ Health & Care Informatics 29, e100460
[paper] [preprint] [code]

Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease
Yizhe Xu, Agata Foryciarz, Ethan Steinberg, Nigam H. Shah
Journal of the American Medical Informatics Association 30 (5), 878-887, 2023.
[paper] [preprint]

Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
Stephen R. Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam H. Shah
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. 2022.
[paper] [preprint] [paper talk]

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations
Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah.
Scientific Reports 12 (1), 1-13, 2022
[paper] [code]

An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction
Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah.
Journal of Biomedical Informatics, 113:103621, 2021
[paper] [preprint] [code]

Non-academic Publications

If We’re Not Careful, Tech Could Hurt the Fight against COVID-19
Ria Kalluri, Lauren Gillespie, Agata Foryciarz, Wren Elhai, Sanjana Srivastava, Argyri Panezi, Lisa Einstein.
Scientific American Blog, 2020.
[article]

Black-Boxed Politics: Opacity is a Choice in AI Systems.
Agata Foryciarz, Daniel Leufer, Katarzyna Szymielewicz.
Medium and Internazionale (Italian translation)
[English] [Italian]

Sztuczna Inteligencja Non-Fiction.
Anna Obem, Katarzyna Szymielewicz. Współpraca merytoryczna: Agata Foryciarz
Fundacja Panoptykon, 2020.
[Polish]