Amir Erfanian

About Me

My background is in modeling and analysis of the hydroclimate system; a complex system composed of several components which interact with each other through nonlinear feedback loops making it intrinsically difficult to model and predict the systems behavior. I have eight years of experience analyzing various geospatial data i.e. observation, satellite, reanalysis, and simulation datasets. My current and past research cover an extended range of responsibilities including numerical experiment design, running numerical prediction models, transferring and archiving large datasets (>10T) between High Performance Computers (HPCs), cloud servers, and local workstations, pre-processing and screening large data, and performing rigorous spatio-temporal data analysis to examine extreme hydrological events and improve model forecasting skill.

My academic research interests include climate variability and extreme events, land-atmosphere interactions, and convection. I am particularly interested in applying state-of-the-art machine learning and deep learning techniques to multi-dimensional data in order to extract new knowledge about climate variability and extremes over North and South America.

Outside of my academic research, I am interested in teaching, science communication, and financial markets. I am passionate about shared economy models (i.e. ride sharing) and decentralized services/assets including decentralized currencies. I have been a crypto-currencies and blockchain enthusiast and an active attendee of workshops/meetups since I was a graduate student.

In my free time I enjoy outdoor sports like hiking, swimming, running, ice-skating or reading a book, watching physics documentaries, and performing market research/technical analysis.