Sebastian Ruder is currently a Research Scientist at Deepmind. His research focuses on transfer learning for natural language processing, and making machine learning and NLP more accessible.

His PhD thesis is titled "Neural Transfer Learning for Natural Language Processing", which he completed in 2019. We cover transfer learning from philosophical and technical perspectives, and talk about its societal

implications, focusing on his work on sequential transfer learning and cross-lingual learning.

Episode notes: https://cs.nyu.edu/~welleck/episode3.html

Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html