Match tier
Likely match
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-16
H
Hoang-Quan Nguyen
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
Faculty Researcher
5 h-index
42 pubs
111 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Hoang-Quan Nguyen's research focuses on the development and application of advanced computational and theoretical models. His work includes investigations into the mechanical properties of materials, such as pervious concrete and composite structures, employing micromechanical and numerical approaches to predict material behavior and damage tolerance. Nguyen also contributes to the field of artificial intelligence, specifically in the area of computer vision, with recent publications exploring foundation models for insect understanding and quantum transformer-based frameworks for visual clustering.
His research network includes frequent collaborators from the University of Arkansas at Fayetteville, such as Xuan-Bac Nguyen, Hugh Churchill, Ky Luu, and Thanh-Dat Truong, with whom he has co-authored numerous publications. Nguyen's scholarly output is reflected in an h-index of 5, with 42 total publications and 111 citations. He has remained recently active in research, with publications extending into 2024.
Metrics
- h-index: 5
- Publications: 42
- Citations: 111
Selected Publications
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QUADRO: A Hybrid Quantum Optimization Framework for Drone Delivery (2025)
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QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks (2025)
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Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding (2025)
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Diffusion-inspired quantum noise mitigation in parameterized quantum circuits (2025)
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Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits (2024)
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Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding (2024)
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Quantum visual feature encoding revisited (2024)
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Quantum Visual Feature Encoding Revisited (2024)
Collaboration Network
Top Collaborators
Khoa Luu
University of Arkansas at Fayetteville
6 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- Quantum visual feature encoding revisited
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Showing 5 of 6 shared publications
Hugh Churchill
Quantum Design (United States)
4 shared publications
In database
- Quantum visual feature encoding revisited
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
- Quantum Visual Feature Encoding Revisited
Samee U. Khan
Kansas State University (US)
4 shared publications
- Quantum visual feature encoding revisited
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
- QUADRO: A Hybrid Quantum Optimization Framework for Drone Delivery
Xuan-Bac Nguyen
University of Arkansas at Fayetteville
4 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Xuan-Bac Nguyen
University of Arkansas at Fayetteville
3 shared publications
In database
- Quantum visual feature encoding revisited
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
- Quantum Visual Feature Encoding Revisited
Samee U. Khan
Kansas State University (US)
2 shared publications
- Quantum Visual Feature Encoding Revisited
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Thanh-Dat Truong
University of Arkansas at Fayetteville
2 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
Ashley P. G. Dowling
University of Arkansas at Fayetteville
2 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
Samuel Yen-Chi Chen
Wells Fargo (United States) (US)
2 shared publications
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Nicholas J. Borys
Montana State University (US)
2 shared publications
- Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
- Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Ky Luu
University of Arkansas at Fayetteville
2 shared publications
In database
- QUADRO: A Hybrid Quantum Optimization Framework for Drone Delivery
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Xin Li
University at Albany, State University of New York
1 shared publication
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
Xin Li
University at Albany, State University of New York (US)
1 shared publication
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
S. D. Pandey
University of Arkansas at Fayetteville
1 shared publication
In database
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Ilya Safro
University of Delaware (US)
1 shared publication
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
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