Work: I am currently a Tech Lead for Big Data and Machine Learning Professional Services on Google Cloud Platform. My mission is to democratize machine learning so that it can be done by anyone anywhere using Google's amazing infrastructure (i.e., without deep knowledge of statistics or programming or ownership of lots of hardware).
Previous Work: As a Director at the Climate Corporation, I led a team of data scientists (statisticians, engineers, meteorologists) who build probabilistic estimates of past, current and future weather. Before that, I was a Senior Research Scientist at CIMMS/U. Oklahoma/National Severe Storms Laboratory. My Google Scholar page captures the ways in which that work is used by other scientists.
Books: My O'Reilly book on Data Science on Google Cloud Platform, an end-to-end look at building data pipelines (from ingest to machine learning) is available on Kindle and paperback. My earlier book on Automating the Analysis of Spatial Grids can be read online and ordered from Springer's website.
Teaching: I lead the development of data analysis and machine learning courses for Google Cloud Platform and taught several of the Data & ML courses on Coursera. Course slides on Spatial Programming and GIS (Fall 2013) and Automated Analysis of Spatial Grids (Spring 2011/2013) are online.
Software: I designed and built much of the Warning Decision Support System Integrated Information (WDSS-II). The sample code that goes with both books (data-science-on-gcp and analysis-of-spatial-grids) is open-source and available from GitHub.
Leadership: I led the meteorology science team at the Climate Corporation, have advised numerous graduate students, and chaired the AI Science and Technology Advisory Committee at the American Meteorological Society. I have helped organize two Climate Informatics conferences, two Kaggle contests and multiple sessions at American Meteorology Society and IEEE conferences.
Blogs: My technical blog and my bridge blog.
About: My resume is here.
Previous Work: As a Director at the Climate Corporation, I led a team of data scientists (statisticians, engineers, meteorologists) who build probabilistic estimates of past, current and future weather. Before that, I was a Senior Research Scientist at CIMMS/U. Oklahoma/National Severe Storms Laboratory. My Google Scholar page captures the ways in which that work is used by other scientists.
Books: My O'Reilly book on Data Science on Google Cloud Platform, an end-to-end look at building data pipelines (from ingest to machine learning) is available on Kindle and paperback. My earlier book on Automating the Analysis of Spatial Grids can be read online and ordered from Springer's website.
Teaching: I lead the development of data analysis and machine learning courses for Google Cloud Platform and taught several of the Data & ML courses on Coursera. Course slides on Spatial Programming and GIS (Fall 2013) and Automated Analysis of Spatial Grids (Spring 2011/2013) are online.
Software: I designed and built much of the Warning Decision Support System Integrated Information (WDSS-II). The sample code that goes with both books (data-science-on-gcp and analysis-of-spatial-grids) is open-source and available from GitHub.
Leadership: I led the meteorology science team at the Climate Corporation, have advised numerous graduate students, and chaired the AI Science and Technology Advisory Committee at the American Meteorological Society. I have helped organize two Climate Informatics conferences, two Kaggle contests and multiple sessions at American Meteorology Society and IEEE conferences.
Blogs: My technical blog and my bridge blog.
About: My resume is here.
