I am a Domain Consultant for Berkeley Research Computing in the areas of HPC and Cloud Computing, in addition to being a graduate student in the Department of Environmental Science, Policy and Management on campus.

In my research, I am generally interested in ecoinformatics (data-intensive ecology) and data-science applications. Specifically, I am interested in using evolutionary algorithms (artificial intelligence) and machine learning (e.g. deep learning) approaches to theoretical and applied ecological frameworks. Example projects I am involved with; A) the use of adaptive learning algorithms to explore the evolution and emergence of ecological behaviors in animal populations and B) the use of deep learning to classify animal behaviors based on accelerometer and GPS collars on large carnivores (e.g. puma, lion, or hyenna populations).

General computational methods / approaches I am experienced in / with:

1. Agent-based models (& individual-based models)

2. Population dynamics (including Population Viability Analysis)

3. R, Python, and Javascript programming (including NodeJS and Django)

4. Adaptive optimization / evolutionary algorithms (including genetic algorithm, curiosity search, simulated annealing)

5. Machine (and deep) learning

6. Front- and back-end web development (e.g. jQuery and Bokeh / D3js front-end, NodeJS and Django back-end)