L. Zhang Data-verified

OverviewAI-generated summary

L. Zhang's research investigates algorithmic recourse in sequential decision-making, focusing on long-term fairness and the development of fairness-aware machine learning systems. This work is supported by multiple federal grants, including significant funding from the National Science Foundation (NSF) for projects aimed at developing counterfactually fair machine learning through causal modeling and advancing long-term fairness in sequential decision-making processes. Additionally, Zhang has received funding from the National Institutes of Health (NIH) for research into the mechanobiology of multicellular morphogenesis and the characterization of mechanically heterogeneous cell populations. These NIH grants support studies on branch stress microscopy for understanding 3D morphogenesis and invasive diseases, as well as investigations into the mechanobiology of cell sorting based on cellular contractility.

Zhang's recent publications include "FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents" (2025) and "Algorithmic recourse in sequential decision-making for long-term fairness" (2026). With an h-index of 1 and 10 total citations across 3 publications, Zhang is an active researcher in the fields of machine learning and biological mechanics. Collaborations include work with Francisco Gumucio at the University of Arkansas at Fayetteville.

Metrics

• h-index: 1
• Publications: 3
• Citations: 10