Developed the cGANs project, a PyTorch implementation of GANs models for generating geological facies; maintains other open-source projects including but not limited to:
- Real-ESRGAN-lp
- SIIM-ISIC-Melanoma-2020
- NonstationaryGANs
- 3D-plot-in-python
- Sparse-kernel-for-SVM
Research Experience
Involved in research on Generative Adversarial Networks (GANs) for geological facies generation; participated in several image processing related projects such as Real-ESRGAN-lp aimed at eliminating tiling artifacts when super-resolving large inputs, and the SIIM-ISIC Melanoma 2020 Kaggle competition for melanoma classification.