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Xintao Wu Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Federal Grant PI
High Impact
Professor
faculty
40 h-index
352 pubs
6,007 cited
Research Areas
Biography and Research Information
OverviewAI-generated summary
Xintao Wu is a professor at the University of Arkansas at Fayetteville whose research focuses on machine learning, particularly in the areas of fairness, privacy, and anomaly detection. Wu has received federal funding from the National Science Foundation (NSF) for two projects totaling $634,828. The first, a $484,828 grant for which Wu served as Co-PI, is titled "Counterfactually Fair Machine Learning through Causal Modeling." The second, a $150,000 grant where Wu was the PI, is "EAGER: Towards Fair Regression under Sample Selection Bias."
Wu's recent publications span diverse applications of computational techniques, including log anomaly detection using BERT, deep learning for insider threat detection, and fairness-aware federated learning. Further research includes work on statistical and causal fairness, removing disparate impact in differentially private stochastic gradient descent, and adaptive fairness-aware online meta-learning. Wu also has recent work investigating large visual language models for medical imaging analysis.
With a career h-index of 40 and over 5,900 citations across more than 350 publications, Wu is recognized as a highly cited researcher. Key collaborators at the University of Arkansas at Fayetteville include Wen Huang and Minh–Hao Van, with whom Wu has co-authored five publications. Alycia N. Carey and Kevin Labille are also frequent collaborators.
Metrics
- h-index: 40
- Publications: 352
- Citations: 6,007
Selected Publications
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Vision language models for scientific image analysis: an evaluation highlighting opportunities and challenges (2026)
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Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation (2026)
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AdaptJobRec: Enhancing Conversational Career Recommendation Through an LLM-Powered Agentic System (2026)
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Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models (2026)
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LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs (2026)
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Achieving Distributive Justice in Federated Learning via Uncertainty Quantification (2026)
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LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs (2026)
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A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation (2025)
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Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction (2025)
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A Hybrid Large Vision Model Powered GUI Agent for Walmart Myassistant Application (2025)
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Fair In-Context Learning via Latent Concept Variables (2025)
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Mmserve: A Distributed Personalization-Oriented Orchestration Framework for Multimodal Ai Models in Edge Computing (2025)
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Privacy Preserving Prompt Engineering: A Survey (2025)
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DP-TabICL: In-Context Learning with Differentially Private Tabular Data (2024)
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Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis (2024)
Federal Grants 2 $634,828 total
NSF
Co-PI
Oct 2021 - Sep 2026
III:Small: Counterfactually Fair Machine Learning through Causal Modeling
NSF
PI
Sep 2021 - Aug 2023
Collaboration Network
Top Collaborators
Shuhan Yuan
Utah State University (US)
9 shared publications
- LogBERT: Log Anomaly Detection via BERT
- Deep learning for insider threat detection: Review, challenges and opportunities
- Contrastive Learning for Insider Threat Detection
- Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process
- Using Dirichlet Marked Hawkes Processes for Insider Threat Detection
Showing 5 of 9 shared publications
Wen Huang
University of Arkansas at Fayetteville
5 shared publications
In database
- Achieving Counterfactual Fairness for Causal Bandit
- Achieving User-Side Fairness in Contextual Bandits
- SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge
- Fairness-aware Bandit-based Recommendation
- Transferable Contextual Bandits with Prior Observations
Hanghang Tong
University of Illinois Urbana-Champaign (US)
5 shared publications
- Fairness-aware Agnostic Federated Learning
- InfoFair: Information-Theoretic Intersectional Fairness
- Attent: Active Attributed Network Alignment
- Fair Regression under Sample Selection Bias
- InfoFair: Information-Theoretic Intersectional Fairness
Wei Du
University of Arkansas at Fayetteville (US)
5 shared publications
- Fairness-aware Agnostic Federated Learning
- Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent
- Fair and Robust Classification Under Sample Selection Bias
- Robust Personalized Federated Learning under Demographic Fairness Heterogeneity
- Robust Fairness-aware Learning Under Sample Selection Bias
Minh–Hao Van
5 shared publications
- On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study
- Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis
- On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study
- Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model
- A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
Depeng Xu
University of Arkansas at Fayetteville (US)
4 shared publications
- Fairness-aware Agnostic Federated Learning
- Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent
- Fair Data Generation and Machine Learning Through Generative Adversarial Networks
- Achieving Differential Privacy in Vertically Partitioned Multiparty Learning
Dongwon Lee
Pennsylvania State University (US)
4 shared publications
- Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT
- MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
- Achieving User-Side Fairness in Contextual Bandits
- Fairness-aware Bandit-based Recommendation
Neil T. Heffernan
Worcester Polytechnic Institute (US)
4 shared publications
- Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT
- MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
- Achieving User-Side Fairness in Contextual Bandits
- Fairness-aware Bandit-based Recommendation
Yongkai Wu
Singapore Management University (SG)
4 shared publications
- Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
- SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge
- A Generative Adversarial Framework for Bounding Confounded Causal Effects
- Counterfactual Thinking Driven Emotion Regulation for Image Sentiment Recognition
Alycia N. Carey
University of Arkansas at Fayetteville
4 shared publications
In database
- The statistical fairness field guide: perspectives from social and formal sciences
- The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences
- Robust Personalized Federated Learning under Demographic Fairness Heterogeneity
- DP-TabICL: In-Context Learning with Differentially Private Tabular Data
Chen Zhao
Baylor University (US)
4 shared publications
- Adaptive Fairness-Aware Online Meta-Learning for Changing Environments
- Towards Fair Disentangled Online Learning for Changing Environments
- Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
- Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously
Kai Jiang
The University of Texas at Dallas (US)
4 shared publications
- Adaptive Fairness-Aware Online Meta-Learning for Changing Environments
- Towards Fair Disentangled Online Learning for Changing Environments
- Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
- Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously
Latifur Khan
The University of Texas at Dallas (US)
4 shared publications
- Adaptive Fairness-Aware Online Meta-Learning for Changing Environments
- Towards Fair Disentangled Online Learning for Changing Environments
- Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
- Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously
Feng Chen
The University of Texas at Dallas (US)
4 shared publications
- Adaptive Fairness-Aware Online Meta-Learning for Changing Environments
- Towards Fair Disentangled Online Learning for Changing Environments
- Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
- Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously
Kevin Labille
University of Arkansas at Fayetteville
3 shared publications
In database
- Achieving User-Side Fairness in Contextual Bandits
- Fairness-aware Bandit-based Recommendation
- Transferable Contextual Bandits with Prior Observations
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