Karthik Venkataramani
Karthik Venkataramani is a postdoctoral scholar working in the Civil and Environmental Engineering department and the eScience institute at the University of Washington, Seattle. Dr. Venkataramani's research work focuses on developing machine learning tools and models for geospatial applications, and he is currently working on refining Digital Elevation Models (DEMs) using deep learning approaches. Prior to this, Dr. Venkataramani worked as a Postdoctoral Researcher at the NASA Jet Propulsion Laboratory on the Observational Products for End-Users from Remote Sensing Analysis project, which generates a near-global suite of analysis ready data products from synthetic aperture radar (SAR) and optical data. Dr. Venkataramani received his MS and PhD in Electrical and Computer Engineering from Virginia Tech.
GitHub: https://github.com/kvenkman
LinkedIn: https://www.linkedin.com/in/karthikvenkataramani/
Sessions
This tutorial walks participants — Earth scientists with some prior Python experience — through analyses of two particular climate risk scenarios: floods & wildfires. The goal is to obtain hands-on experience with common reproducible Jupyter/Python workflows based on data products from the NASA Earthdata Cloud. The case studies highlight the interplay of distributed data with scalable numerical strategies — "data-proximate computing" — implemented using scientific Python libraries like NumPy, Pandas, & Xarray. This tutorial — co-developed by 2i2c and MetaDocencia — constitutes part of NASA's Transform to Open Science (TOPS) initiative to reinforce principles of Open Science & reproducibility.