Rami Al-Rfou is a Staff Research Scientist at Waymo Research. He leads a team to build foundational models for motion and driving based on his expertise in large language models.
Previously, Rami was a technical lead for assisted writing applications such as SmartReply at Google Research. His research focused on improving pretraining large language modeling through token-free architectures, synthetic datasets constructed with knowledge-base based generative models, and improved sampling strategies for multilingual datasets. These pretrained language models, trained on +100 languages, are being utilized in query understanding, web page understanding, semantic search, and response ranking in conversations.
Al-Rfou’s research goes beyond language into designing better architecture to understand large-scale data such as graphs. Al-Rfou repurposes language modeling tools to produce novel graph learning algorithms that measure node and graph similarities. These modeling ideas have been deployed for spam detection and personalization application on large scale.
Al-Rfou received his PhD in Computer Science at Stony Brook University under the supervision of Prof. Steven Skiena in 2015. He investigated how to utilize deep learning representations to build truly massive multilingual NLP pipeline that supports +100 languages. Massively multilingual modeling significantly gained momentum in the recent years since then. Al-Rfou’s experience in sequential modeling and crosslingual applications span 10 years of academic and industrial research with applications that touched the lives of millions of users and open sourced code that helped thousands of students.