Dong Lao

Assistant Professor

Contact

dlao1@lsu.edu 
Office 3272W
Patrick F. Taylor Hall

Educational Background

Ph.D King Abdullah ¾Å¾Å¸£ÀûÍø of Science and Technology (KAUST), 2021

B.S. Shanghai Jiao Tong ¾Å¾Å¸£ÀûÍø (SJTU) 2015

Dong Lao

  • CSC 4444: Artificial Intelligence
  • CSC 4343: Applied Deep Learning
  • Computer Vision
  • Multi-modal Perception
  • Representation Learning
  • Xiao, Y., Coronel, C., Zhan, J., Oskouie, H., Wong, A., Lao, D. (2026). Triangular consistency as a universal constraint for learning optical flow. European Conference on Computer Vision (ECCV 2026).
  • Lao, D (2026). Position: unlabeled ≠ no human supervision in visual learning. International Conference on Machine Learning (ICML 2026).
  • Wang, D., Rim, P., Tian, T., Lao, D., Wong, A., Sundaramoorthi, G. (2026). Ode-gs: Latent odes for dynamic scene extrapolation with 3d gaussian splatting. International Conference on Learning Representations (ICLR 2026).
  • Park, H., Chen, R., Rim, P., Lao, D., Wong, A. (2026). Orcas: Unsupervised depth completion via occluded region completion as supervision. International Conference on Learning Representations (ICLR 2026).
  • 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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