Research My research mainly focuses on machine learning problems in computational sustainability. My collaborators and I have applied various machine learning techniques to problems in the study of sustainability, especially ecosystem management. I include the following three projects in my thesis: Superset Label Learning (SLL) for bird song classification Gaussian Collective Graphical Model (GCGM) for bird migration modeling Constrained Transductive Selection for reserve design The third project is still ongoing. I have also participated in several other projects, such as Occupancy-Detection model with Boosted Regression Trees and spatial data fitting. Future research: I will still focus on machine learning problems in computational sustainability. Particularly, I will focus on topics such as the impact of climate change on ecosystems and long-term ecosystem management. On the machine learning side, I will pay more attention to interactive machine learning robust decision-making. Principle of my research: application-driven fundamental machine learning research.