Hello, my name is Lingjing Wang. I earned my PhD in Applied Mathematics at Courant Institute of Mathematical Sciences and Engineering School of NYU. I am currently doing research in 3D visual computing and deep learning. I am working with Professor Yi Fang in NYU MMVC Lab. My committee advisors include: Prof.Deane Yang, Prof.Gaoyong Zhang and Prof.Edward Wong. I am also interested in trading strategies research, especially leveraging AI technicals for analyzing large size datasets over global financial markets for investment oppurtunities.
Selected research papers (first/joint first author)
1. Few-shot Learning of Part-specific Probability Space for 3D Shape Segmentation. CVPR 2020
2. Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration. NeurIPS 2019
3. PC-Net: Unsupervised Point Correspondence Learning with Neural Networks. 3DV 2019
4. Coherent Point Drift Networks: Unsupervised Learning of Non-Rigid Point Set Registration. Arxiv [ Paper , Code ]
5. Non-Rigid Point Set Registration Networks. Arxiv [ Paper , Code ].
6. Unsupervised Learning of 3D Model Reconstruction from Hand-Drawn Sketches. ACM Multimedia 2018
7. 3DensiNet: A Robust Neural Network Architecture towards 3D Volumetric Object Prediction from 2D Image. ACM Multimedia 2017