Joshua Wolff Anderson

Joshua Wolff Anderson

PhD Candidate,
Intelligent Systems

University of Pittsburgh

👋

Hi, I'm Josh

I’m a PhD student in Intelligent Systems at the University of Pittsburgh. My research sits at the intersection of fairness, interpretability, and causal reasoning in machine learning. I focus on bias mitigation in clinical decision-making working with models that are not just accurate, but also transparent in high impact applications such as healthcare.
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Education

PhD Intelligent Systems

Aug. 2022
Expected: Nov. 2026

University of Pittsburgh

MS Computational and Data Sciences

Aug. 2020
May 2022

Chapman University

BS Computer Science

Aug. 2016
May 2020

Chapman University

Interests

Clinical Decision Support Causal Inference Machine Learning AI Ethics & Fairness
Featured Publications
Algorithmic individual fairness and healthcare: a scoping review featured image

Algorithmic individual fairness and healthcare: a scoping review

The use of algorithms in healthcare holds the potential to improve care delivery and reduce costs. However, these algorithms can sometimes reflect biases, leading to unfair …

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An R package for parametric estimation of causal effects featured image

An R package for parametric estimation of causal effects

This article explains the usage of R package CausalModels, which is publicly available on the Comprehensive R Archive Network. While packages are available for sufficiently …

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Recent Publications
Joshua W Anderson, Shyam Visweswaran (2025). Algorithmic individual fairness and healthcare: a scoping review. JAMIA Open.
DOI PDF
Joshua Wolff Anderson, Shyam Visweswaran (2025). The Effect of Enforcing Fairness on Reshaping Explanations in Machine Learning Models. arXiv preprint arXiv:2512.02265.
Joshua W Anderson, Nader Shaikh, Shyam Visweswaran (2024). Measuring and Reducing Racial Bias in a Pediatric Urinary Tract Infection Model. AMIA Summits on Translational Science Proceedings.
PDF
Joshua Wolff Anderson, Cyril Rakovski (2023). An R package for parametric estimation of causal effects. arXiv preprint arXiv:2307.08686.
DOI Code PDF
Joshua Wolff Anderson, Luis Iñaki Alberro Encina, Tina George Karippacheril, Jonathan Hersh, Cadence Stringer (2022). A Topic Modeling Approach to Classifying Open Street Map Health Clinics and Schools in Sub-Saharan Africa. arXiv preprint arXiv:2212.12084.
DOI Code PDF
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Talks & Guest Lectures

Topics in Artificial Intelligence: Mechanistic Interpretability

Chapman University

Course: High Performance Computing
Lab: R code for example business fairness problem

Topics in Machine Learning: Algorithmic Fairness

Chapman University

Course: Machine Learning for Managers
Lab: Ethical hiring problem Python notebook

Topics in Machine Learning: Algorithmic Fairness

Chapman University

Course: Machine Learning for Managers
Lab: R code for example business fairness problem

Topics in Data Science: Causal Inference

Chapman University

Course: Intro to Data Science
Lab: example causal inference Python notebook

Teaching

Data Structures and Algorithms, Teaching Assistant

Chapman University

Data Structures and Algorithms, Teaching Assistant

Chapman University

Machine Learning for Manageers, Teaching Assistant

Chapman University

Statistical Models For Business, Teaching Assistant

Chapman University

News

Successfully defended dissertation proposal!

Successfully passed ISP comprehensive exam!

Successfully passed ISP preliminary exam!

Awards
Nomination for Best Student Paper
AMIA Informatics Summit ∙ March 2024
Nomitated for innovative application of fairness in healthcare.
Nomination for Best Poster
AMIA Annual Symposium ∙ November 2023
Received best poster nomination during main poster session.