Pha Nguyen
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Chair
Also affiliated: Vietnam National University Ho Chi Minh City (2020); Van Lang University (2024); VinUniversity (2021)
Faculty Researcher
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Pha Nguyen's research agenda centers on advancing artificial intelligence and machine learning techniques for complex data analysis, particularly in areas of computer vision and object recognition. Nguyen has published work on self-supervised learning, spatiotemporal transformers, and attention-based models for group activity recognition, as well as methods for multi-camera multi-object tracking and zero-shot generic multiple object tracking. These efforts are aimed at improving the accuracy and efficiency of systems used in applications such as autonomous vehicles and video understanding.
Nguyen has secured significant federal funding to support this research. As PI on the NSF-funded "Shared Arkansas Research Plan for Community Cyber Infrastructure (SHARP CCI)," Nguyen received $199,592 to advance community cyber infrastructure. Additionally, as Co-PI on the large NSF E-RISE Rll grant, "Arkansas Smart Transportation Research Incubator through Data Engineering and Science," Nguyen is involved with a $7,000,000 project focused on data engineering and science for smart transportation. Other Co-PI roles on NSF grants include projects related to Alaskan riverine ecosystem stability ($75,000), spatial archaeometry ($248,135 and $209,726), and Lidar technology for truck detection ($50,000).
With an h-index of 7 and 162 citations across 39 publications, Nguyen's work demonstrates a consistent output in the field. Key collaborators include Page D. Dobbs (University of Arkansas for Medical Sciences), Khoa Luu (University of Arkansas at Fayetteville), Trong-Thuan Nguyen (University of Arkansas at Fayetteville), and Jackson Cothren (University of Arkansas at Fayetteville), with whom Nguyen has co-authored multiple publications. Nguyen also maintains an active lab website.
Metrics
- h-index: 8
- Publications: 38
- Citations: 174
Selected Publications
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Discriminative and Generative Video Modeling (2025)Journal of the Arkansas Academy of Science OpenAlex
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HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation (2025)
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Autoregressive Temporal Modeling for Advanced Tracking-by-Diffusion (2025)
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SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition (2025)
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Depth Perspective-Aware Multiple Object Tracking (2024)
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React: recognize every action everywhere all at once (2024)
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HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group-Activity Scene Graph Generation in Videos (2024)
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Multi-camera multi-object tracking on the move via single-stage global association approach (2024)
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REACT: Recognize Every Action Everywhere All At Once (2024)
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HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos (2023)
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SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition (2023)
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Self-Supervised Domain Adaptation in Crowd Counting (2022)
Federal Grants 6 $7,782,453 total
CC* CIRA: Shared Arkansas Research Plan for Community Cyber Infrastructure (SHARP CCI)
E-RISE Rll: Arkansas Smart Transportation Research Incubator through Data Engineering and Science
Collaboration Network
Top Collaborators
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- Multi-camera multi-object tracking on the move via single-stage global association approach
- Self-Supervised Domain Adaptation in Crowd Counting
- React: recognize every action everywhere all at once
- SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition
Showing 5 of 11 shared publications
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- React: recognize every action everywhere all at once
- SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition
- HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group-Activity Scene Graph Generation in Videos
- REACT: Recognize Every Action Everywhere All At Once
- Multi-camera multi-object tracking on the move via single-stage global association approach
- Self-Supervised Domain Adaptation in Crowd Counting
- HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group-Activity Scene Graph Generation in Videos
- HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- React: recognize every action everywhere all at once
- SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition
- HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group-Activity Scene Graph Generation in Videos
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition
- HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos
- REACT: Recognize Every Action Everywhere All At Once
- Multi-camera multi-object tracking on the move via single-stage global association approach
- Depth Perspective-Aware Multiple Object Tracking
- Multi-camera multi-object tracking on the move via single-stage global association approach
- Depth Perspective-Aware Multiple Object Tracking
- Self-Supervised Domain Adaptation in Crowd Counting
- Self-Supervised Domain Adaptation in Crowd Counting
- Self-Supervised Domain Adaptation in Crowd Counting
- SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition
- Multi-camera multi-object tracking on the move via single-stage global association approach
- Depth Perspective-Aware Multiple Object Tracking
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