Lu Zhang
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Research Areas
Biography and Research Information
OverviewAI-generated summary
L. Zhang's research focuses on advancing fairness in machine learning, particularly within sequential decision-making contexts. Zhang has contributed to developing methodologies for algorithmic recourse, aiming to provide individuals with actionable steps to achieve fairer outcomes from algorithmic systems. This work has been supported by two NSF grants: the CAREER award, "Towards Long-term Fairness in Sequential Decision Making" ($597,185), and "III:Small: Counterfactually Fair Machine Learning through Causal Modeling" ($484,828).
Recent publications by Zhang include "FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents" (2025) and "Algorithmic recourse in sequential decision-making for long-term fairness" (2026). These works highlight an active engagement with contemporary challenges in artificial intelligence and machine learning, exploring the practical implementation and theoretical underpinnings of fairness-aware systems. Zhang has collaborated with Francisco Gumucio at the University of Arkansas at Fayetteville on shared publications.
Metrics
- h-index: 1
- Publications: 3
- Citations: 10
Selected Publications
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Efficient Fairness Auditing Across Guidance Scales in Text-to-Image Diffusion Models via Causal Abstraction (2026)
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Algorithmic recourse in sequential decision-making for long-term fairness (2026)
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FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents (2025)
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Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration (2025)
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Fair Multiple Decision Making Through Soft Interventions (2020)
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Selective etching of InGaAs∕GaAs(100) multilayers of quantum-dot chains (2005)
Federal Grants 2 $1,082,013 total
III:Small: Counterfactually Fair Machine Learning through Causal Modeling
CAREER: Towards Long-term Fairness in Sequential Decision Making
Collaboration Network
Top Collaborators
- Fair Multiple Decision Making Through Soft Interventions
- FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
- Selective etching of InGaAs∕GaAs(100) multilayers of quantum-dot chains
- Selective etching of InGaAs∕GaAs(100) multilayers of quantum-dot chains
- Selective etching of InGaAs∕GaAs(100) multilayers of quantum-dot chains
- Fair Multiple Decision Making Through Soft Interventions
- Fair Multiple Decision Making Through Soft Interventions
- Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration
- Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration
- Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration
- Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration
- Novel Nanomaterials for Developing Bone Scaffolds and Tissue Regeneration
- Algorithmic recourse in sequential decision-making for long-term fairness
- FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
- FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
- FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
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