Match tier
Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-08-16
T
Thanh-Dat Truong
Postdoctoral Fellow
Postdoc Researcher
11 h-index
60 pubs
397 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Thanh-Dat Truong's research focuses on the application of machine learning, particularly deep learning and neural networks, to address complex problems in computer vision and domain adaptation. His work includes developing novel approaches for action recognition, semantic scene segmentation, and face recognition. Truong has investigated methods for improving fairness in domain adaptation and has explored self-supervised learning techniques for crowd counting. He has also contributed to the development of foundation models for specialized visual understanding tasks, such as insect recognition, utilizing large-scale datasets. His research has led to publications in peer-reviewed journals and conferences, and he has collaborated with multiple researchers at the University of Arkansas at Fayetteville, including Khoa Luu, Ashley P. G. Dowling, Xuan-Bac Nguyen, and Jackson Cothren.
Metrics
- h-index: 11
- Publications: 60
- Citations: 397
Selected Publications
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DEGA: Dynamic Entropy Guided Adaptation (2025)
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Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding (2025)
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Cross-view action recognition understanding from exocentric to egocentric perspective (2024)
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CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars (2024)
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Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding (2024)
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LIAAD: Lightweight attentive angular distillation for large-scale age-invariant face recognition (2023)
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OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation (2022)
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Self-Supervised Domain Adaptation in Crowd Counting (2022)
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EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring (2022)
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BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation (2021)
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Movement Analysis for Neurological and Musculoskeletal Disorders Using Graph Convolutional Neural Network (2021)
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Fast Flow Reconstruction via Robust Invertible n × n Convolution (2021)
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DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking (2021)
Collaboration Network
Top Collaborators
Khoa Luu
University of Arkansas at Fayetteville
12 shared publications
In database
- Movement Analysis for Neurological and Musculoskeletal Disorders Using Graph Convolutional Neural Network
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- LIAAD: Lightweight attentive angular distillation for large-scale age-invariant face recognition
- Self-Supervised Domain Adaptation in Crowd Counting
- EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring
Showing 5 of 12 shared publications
Ngan Le
University of Arkansas at Fayetteville
5 shared publications
In database
- LIAAD: Lightweight attentive angular distillation for large-scale age-invariant face recognition
- Self-Supervised Domain Adaptation in Crowd Counting
- OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation
- Fast Flow Reconstruction via Robust Invertible n × n Convolution
- BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
Chi Nhan Duong
Concordia University (CA)
4 shared publications
- LIAAD: Lightweight attentive angular distillation for large-scale age-invariant face recognition
- Fast Flow Reconstruction via Robust Invertible n × n Convolution
- DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
- BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
Ashley P. G. Dowling
University of Arkansas at Fayetteville
3 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation
- Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
Kha Gia Quach
Concordia University (CA)
2 shared publications
- LIAAD: Lightweight attentive angular distillation for large-scale age-invariant face recognition
- DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Pha Nguyen
University of Arkansas at Fayetteville
2 shared publications
In database
- Self-Supervised Domain Adaptation in Crowd Counting
- DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Minh–Triet Tran
Vietnam National University Ho Chi Minh City (VN)
2 shared publications
- Fast Flow Reconstruction via Robust Invertible n × n Convolution
- DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Ibsa Jalata
University of Arkansas at Fayetteville
2 shared publications
In database
- Movement Analysis for Neurological and Musculoskeletal Disorders Using Graph Convolutional Neural Network
- EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring
Chase Rainwater
University of Arkansas at Fayetteville
2 shared publications
In database
- EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring
- BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
Pierce Helton
University of Arkansas at Fayetteville
2 shared publications
In database
- EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring
- CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars
Xuan-Bac Nguyen
University of Arkansas at Fayetteville
2 shared publications
In database
- Insect-Foundation: A Foundation Model and Large-Scale 1M Dataset for Visual Insect Understanding
- OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation
Hoang-Quan Nguyen
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
Huu Le
Chalmers University of Technology (SE)
1 shared publication
- DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Jessica L. Allen
West Virginia University (US)
1 shared publication
- Movement Analysis for Neurological and Musculoskeletal Disorders Using Graph Convolutional Neural Network
Han‐Seok Seo
University of Arkansas at Fayetteville
1 shared publication
In database
- Movement Analysis for Neurological and Musculoskeletal Disorders Using Graph Convolutional Neural Network
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