Match tier
Likely match
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
M
Minh-Hao Van
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: Santa Fe Institute (2019); University of California, Los Angeles (2019); University of Arkansas System (2026)
Faculty Researcher
5 h-index
32 pubs
144 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Minh-Hao Van's research focuses on the application of large visual language models (VLMs) and artificial intelligence (AI) in diverse analytical domains. His work investigates the capabilities of VLMs for complex tasks such as medical imaging analysis, microscope image analysis, and the detection and correction of hate speech in multimodal content. Van also explores foundational aspects of AI, including its application in materials science and the principles of unlearning in large language models.
His publications delve into empirical studies of VLMs, examining their performance in specific contexts. Van's research network includes extensive collaboration with colleagues at the University of Arkansas at Fayetteville, such as Xintao Wu, Alycia N. Carey, Prateek Verma, and Karuna Bhaila, with whom he has co-authored numerous publications. His scholarship metrics include an h-index of 5, with 32 publications and 140 citations.
Metrics
- h-index: 5
- Publications: 32
- Citations: 144
Selected Publications
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Vision language models for scientific image analysis: an evaluation highlighting opportunities and challenges (2026)
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A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools (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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Fair In-Context Learning via Latent Concept Variables (2025)
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Influence-based approaches for tumor classification in noisy brain MRI with deep learning and vision-language models (2025)
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Soft Prompting for Unlearning in Large Language Models (2025)
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Selecting In-Context Learning Demonstrations Via Influence Analysis (2025)
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Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis (2024)
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Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions (2024)
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On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study (2024)
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Robust Influence-Based Training Methods for Noisy Brain MRI (2024)
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HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks (2023)
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Defending Evasion Attacks via Adversarially Adaptive Training (2022)
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Poisoning Attacks on Fair Machine Learning (2022)
Collaboration Network
Top Collaborators
Xintao Wu
University of Arkansas at Little Rock
11 shared publications
In database
- On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study
- Poisoning Attacks on Fair Machine Learning
- Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis
- A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
- Soft Prompting for Unlearning in Large Language Models
Showing 5 of 11 shared publications
Alycia N. Carey
University of Arkansas at Fayetteville
4 shared publications
In database
- Robust Influence-Based Training Methods for Noisy Brain MRI
- Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions
- HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks
- Influence-based approaches for tumor classification in noisy brain MRI with deep learning and vision-language models
Prateek Verma
University of Arkansas at Fayetteville
4 shared publications
In database
- 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
- Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
Xintao Wu
University of Arkansas at Fayetteville
3 shared publications
In database
- Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction
- Fair In-Context Learning via Latent Concept Variables
- A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation
Aidong Lu
University of North Carolina at Charlotte (US)
2 shared publications
- Poisoning Attacks on Fair Machine Learning
- Defending Evasion Attacks via Adversarially Adaptive Training
Chen Zhao
Baylor University (US)
2 shared publications
- Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction
- Fair In-Context Learning via Latent Concept Variables
Wei Du
University of Arkansas at Fayetteville (US)
1 shared publication
- Poisoning Attacks on Fair Machine Learning
Wei Du
University of Arkansas at Fayetteville
1 shared publication
In database
- Defending Evasion Attacks via Adversarially Adaptive Training
Feng Chen
The University of Texas at Dallas (US)
1 shared publication
- Defending Evasion Attacks via Adversarially Adaptive Training
Vinay M.S.
University of Arkansas at Fayetteville
1 shared publication
In database
- Selecting In-Context Learning Demonstrations Via Influence Analysis
Karuna Bhaila
University of Arkansas at Fayetteville
1 shared publication
In database
- Soft Prompting for Unlearning in Large Language Models
Prateek Verma
University of Arkansas at Little Rock
1 shared publication
In database
- A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
Chen Zhao
Baylor University (US)
1 shared publication
- A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
Karuna Bhaila
University of Arkansas at Fayetteville
1 shared publication
In database
- Fair In-Context Learning via Latent Concept Variables
Kennedy Edemacu
University of Arkansas at Fayetteville
1 shared publication
In database
- Fair In-Context Learning via Latent Concept Variables
Similar Researchers
Based on overlapping research topics
Yu Sun
University of Central Arkansas
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University of Arkansas for Medical Sciences
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Arkansas State University
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University of Arkansas at Fayetteville
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Susan Gauch
University of Arkansas at Fayetteville
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