My guest this week is Stefano Ermon, Assistant Professor of Computer Science at Stanford University, and Fellow at Stanford’s Woods Institute for the Environment. Stefano and I met at the Re-Work Deep Learning Summit earlier this year, where he gave a presentation on Machine Learning for Sustainability.
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Stefano and I spoke about a wide range of topics, including the relationship between fundamental and applied machine learning research, incorporating domain knowledge in machine learning models, dimensionality reduction, semi-supervised learning, proxy & transfer learning, and his interest in applying ML & AI to addressing sustainability issues such as poverty, food security and the environment.
New Stickers, New Contest
Inspired by an exchange with listener @bethann_nyc on Twitter, we want to try a little contest for you all. We’ve got some fresh new stickers on hand, and we’d like to get them into your hands! (I’ve got to say, they really turned out great!) So here’s what you need to do to get one: Let us know your favorite quote from this week’s podcast via Facebook, Twitter, Youtube or SoundCloud comment, or a comment on the show notes page by midnight Sunday (3/19) Pacific Time and we’ll send you one!
About Stefano Ermon
Mentioned in the Interview
- Project: Combining Satellite Imagery and Machine Learning to Predict Poverty
- Paper: Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
- Paper: Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping
- Paper: Combining Satellite Imagery and Machine Learning to Predict Poverty
- NASA MODIS Data Set
- Paper: Supervising Neural Networks with Physics and other Domain Knowledge | Code