Ngan Le Data-verified
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Assistant Professor
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Biography and Research Information
OverviewAI-generated summary
Dr. Ngan Le's research focuses on developing trustworthy, robust, and efficient multimodal frameworks for video analytics, particularly addressing challenges posed by imperfect data such as limited labeled data, noisy data, biased data, and unseen data. Her work also investigates real-time applications on edge devices and the analysis of complex real-world scenarios. Dr. Le is proficient in processing and understanding various data modalities, including image, video, point cloud, volumetric data, time series, and remote sensing data. Her expertise encompasses image processing, scene understanding, multiple object tracking, behavior analysis, and 3D reconstruction.
She is currently an Associate Professor and Director of the Artificial Intelligence & Computer Vision (AICV) Lab in the Department of Electrical Engineering & Computer Science at the University of Arkansas. Previously, Dr. Le was a Postdoctoral Fellow at Carnegie Mellon University. She holds a Ph.D. and Master's degrees in Electrical & Computer Engineering from Carnegie Mellon University and Master's and Bachelor's degrees in Computer Science from Vietnam.
Dr. Le has secured significant federal funding for her research. She is the Principal Investigator (PI) on an NSF CAREER award focused on trustworthy, robust, and efficient multimodal frameworks for video analytics, totaling $499,556. She also serves as a Co-PI on two NSF Convergence Accelerator awards: "Cultivate IQ - Empowering Regional Food Systems" ($4,998,818) and "Data-driven Agriculture to Bridge Small Farms to Regional Food Supply Chains" ($743,651). Her research output includes 36 publications, with an h-index of 13 and 384 total citations.
Metrics
- h-index: 13
- Publications: 36
- Citations: 384
Selected Publications
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SSL-MTab: Self-Supervised Distillation for Missing Data in Tabular Prediction Tasks (2026)
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MiGa: Multi-chicken gait assessment (2026)
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Rethinking Progression of Memory State in Robotic Manipulation: An Object-Centric Perspective (2026)
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DualFit: A Two-Stage Virtual Try-On via Warping and Synthesis (2025)
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TolerantECG: A Foundation Model for Imperfect Electrocardiogram (2025)
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CattleFever: An automated cattle fever estimation system (2025)
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A2VIS: Amodal-Aware Approach to Video Instance Segmentation (2025)
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Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models (2025)
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GazeSearch: Radiology Findings Search Benchmark (2025)
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ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions (2024)
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Amodal Instance Segmentation with Diffusion Shape Prior Estimation (2024)
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Enhanced Kalman with Adaptive Appearance Motion SORT for Grounded Generic Multiple Object Tracking (2024)
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FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation (2024)
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A2vis: Amodal-Aware Approach to Video Instance Segmentation (2024)
Federal Grants 3 $6,242,025 total
NSF Convergence Accelerator Track J Phase 2: Cultivate IQ - Empowering Regional Food Systems
CAREER: Trustworthy, Robust, and Efficient Multimodal Framework for Video Analytics.
Collaboration Network
Top Collaborators
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- Comprehensive assessment of viscous heat generation in rarefied gas microflows
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- EigenWave: An Optimal O(N) Method for Computing Eigenvalues and Eigenvectors by Time-Filtering the Wave Equation
- Eigenwave: An Optimal o(n) Method for Computing Eigenvalues And Eigenvectors by Time-Filtering the Wave Equation
- EigenWave: An Optimal O(N) Method for Computing Eigenvalues and Eigenvectors by Time-Filtering the Wave Equation
- Eigenwave: An Optimal o(n) Method for Computing Eigenvalues And Eigenvectors by Time-Filtering the Wave Equation
- EigenWave: An Optimal O(N) Method for Computing Eigenvalues and Eigenvectors by Time-Filtering the Wave Equation
- Turbulent energy cascade associated with viscous reconnection of two vortex rings
- Turbulent energy cascade associated with viscous reconnection of two vortex rings
- Comprehensive assessment of viscous heat generation in rarefied gas microflows
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