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Bio: | |
I am a Ph.D. candidate advised by professor Nuno Vasconcelos, working on machine learning, deep learning and their applications on computer vision, more specifically on explainable AI, visualization, image generation and synthesis, object detection, domain adaptation, machine teaching for scalable learning, stylization, etc. |
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News: | |
One paper was accepted to T-PAMI.
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Representative Publications: | |
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A Generalized Explanation Framework for Visualization of Deep Learning Model Predictions |
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Omni-DETR: Omni-Supervised Object Detection with Transformers |
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A Machine Teaching Framework for Scalable Recognition |
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Gradient-Based Algorithms for Machine Teaching |
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Rethinking and Improving the Robustness of Image Style Transfer |
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IMAGINE: Image Synthesis by Image-Guided Model Inversion |
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SCOUT: Self-aware Discriminant Counterfactual Explanations |
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Deliberative Explanations: visualizing network insecurities |
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Towards Realistic Predictors |
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Graph Based Skeleton Motion Representation and Similarity Measurement for Action Recognition |
Professional Experience: | |
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University of California, San Diego |
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Adobe Research |
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Amazon AWS |
Awards: | |
UCSD ECE department FellowShip, Sep 2017
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Last update: Dec, 2021
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SVCL