Postdoctoral Scholar at University of California, San Diego working on meta-learning for spatiotemporal data with Professor Rose Yu. Ph.D. in Machine Learning from University of California, Santa Barbara. Interested in imbalanced data problems and deep learning meta-learning techniques for few-shot learning. Studying problems of underrepresented training sets for low-shot learning and understanding what impacts the visual similarities between various objects.
My research interests span the areas of machine learning and computer vision. A common thread in my research is understanding the training process of neural networks for image data, especially when the number of available training examples is scarce. I have studied both the theoretical and practical implications of such conditions and utilized the knowledge combining the areas of Deep Learning, Probability, and Optimization in addressing this issue. In broad understanding, my research belongs to the area of Deep Learning, which when referring to scenarios involving data scarcity problems is still in the early stages of development.