Zeng, Z., Wu, Y., Park, H., Wang, D., Yang, F., Soatto, S., & Lao, D., Hong, B. W.,
& Wong, A. (2024). Resolving scale ambiguities in monocular depth estimators through
language descriptions. Advances in Neural Information Processing Systems (NeurIPS
2024).
Lao, D., Yang, F., Park, H., Wang, D., Lu, S., Wong, A., & Soatto, S. (2024). On the
viability of monocular depth pre-training for semantic segmentation. European Conference
on Computer Vision (ECCV 2024).
Wu, Y., Liu, T. Y., Park, H., Soatto, S., Lao, D., & Wong, A. (2024). AugUndo: Scaling
up augmentations for monocular depth completion and estimation. European Conference
on Computer Vision (ECCV 2024).
Lao, D., Wu, Y., Liu, T. Y., Wong, A., & Soatto, S. (2024). Sub‑token ViT embedding
via stochastic resonance transformers. International Conference on Machine Learning
(ICML 2024).
Lao, D., Wang, C., Wong, A., & Soatto, S. (2024). Diffeomorphic template registration
for atmospheric turbulence mitigation. Conference on Computer Vision and Pattern Recognition
(CVPR 2024). (Highlighted)
Zeng, Z., Wang, D., Park, H., Yang, F., Soatto, S., Lao, D., & Wong, A. (2024). WorDepth:
Variational language prior for monocular depth estimation. Conference on Computer
Vision and Pattern Recognition (CVPR 2024).
Sun, Y., Lao, D., Yezzi, A., & Sundaramoorthi, G. (2024). A PDE-based explanation
of extreme numerical sensitivities and edge of stability in training neural networks.
Journal of Machine Learning Research (JMLR 2024).
Sun, Y., Lao, D., Sundaramoorthi, G., & Yezzi, A. (2022). Surprising instabilities
in training deep networks and a theoretical analysis. Advances in Neural Information
Processing Systems (NeurIPS 2022).
Lao, D., Zhu, P., Wonka, P., & Sundaramoorthi, G. (2021). Flow-guided video inpainting
with scene templates. International Conference on Computer Vision (ICCV 2021).
Yang, Y., Lao, D., Sundaramoorthi, G., & Soatto, S. (2020). Phase consistent ecological
domain adaptation. Conference on Computer Vision and Pattern Recognition (CVPR 2020).
Lao, D., & Sundaramoorthi, G. (2019). Minimum delay object detection in videos. International
Conference on Computer Vision (ICCV 2019).
Lao, D., & Sundaramoorthi, G. (2018). Extending layered models to 3D motion. European
Conference on Computer Vision (ECCV 2018).
Lao, D., & Sundaramoorthi, G. (2017). Minimum delay moving object detection. Conference
on Computer Vision and Pattern Recognition (CVPR 2017).
Honors degree in mathematics by the College of Zhiyuan, SJTU, 2015
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