Teaching interests

Machine Learning applied to planetary science

This course would provide students with hands-on experience on using state-of-the-art machine learning software like TensorFlow in planetary science research projects. Requirements would include a research paper and an in-class hackathon. 
For a tentative syllabus, click here.

Evolution of planetary surfaces

This course would focus on the modeling and analysis of remote sensing data of the evolution of planetary surfaces, including remote sensing of bodies with and without an atmosphere, future space missions and the use of machine learning techniques to analyze big datasets of planetary surfaces. Class requirements would include a research paper and presentations.

Planetary formation 

This course would focus on the current understanding of how terrestrial planets like Earth form and evolve, and the onset of habitable conditions in the larger context of exoplanetary data. It would also provide hands-on experience of how to code computational methods commonly used in planet formation and evolution studies. Requirements would include a research paper and in-class presentations.