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Evan Shelhamer is an assistant professor at UBC in Vancouver and member of the Vector Institute. His research is on visual recognition, self-supervised learning without annotations, and robustness by adaptation. He earned his PhD at UC Berkeley advised by Prof. Trevor Darrell. He was the lead developer of the Caffe open-source deep learning framework from version 0.1 to 1.0. His research and service have received awards including the best paper honorable mention at CVPR'15 for fully convolutional networks and the Mark Everingham award at ICCV'17, the open-source award at MM'14, and the test-of-time award at MM'24 for Caffe. He likes to brew coffee and community, and his latest organizing efforts include the 1st workshop on test-time adaptation at CVPR'24 and the 3rd workshop on machine learning for remote sensing at ICLR'25. He is new the Pacific NW and excited to experience every kind of rain and explore substitutes for sunshine.