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Biography
Daniel Cer is a senior research scientist at Google Research. His work focuses on representation learning using deep learning methods for natural language processing (NLP) tasks such as semantic similarity, question answering (QA), semantic retrieval (SR), bi-text mining and text classification. Prior to Google, he was a post-doc in the Stanford NLP group where he worked on machine translation (MT), semantic textual similarity (STS) and early bilingual embedding models under the guidance of Dan Jurafsky and Chris Manning.
Recent courses taught
Spring 2023
Fall 2022
Summer 2022
Spring 2022
Fall 2021
Summer 2021
Spring 2021
Fall 2020
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