Davis Liang
Staff Research Scientist at Abridge AI (Formerly Meta AI, Amazon AI)
I am a Staff Research Scientist at Abridge AI, working on applying my research in multilingual large language models to reinvent healthcare one conversation at a time. Previously, I was a Senior Research Scientist at Meta AI, working on natural language processing research. My current academic pursuits involve understanding the underpinnings of how foundation models learn.
Prior to Meta, I worked on information retrieval, machine translation, and speech recognition as an Applied Scientist at Amazon (AWS) AI. At Amazon, I worked with a group of wonderful scientists whose creativity and enthusiasm are the primary reasons why I have not abandoned society to peddle art NFTs from a sizeable digital estate in Fashion Street district, Decentraland.
I also worked as a Software Engineer at Yahoo and obtained my MS degree in Computer Science from UC San Diego, where I was advised by Prof. Gary Cottrell. During my undergrad, I was fortunate enough to work with Prof. Michael J Tarr exploring how humans perceive faces and scenes.
Research Interests
I am interested in:
- Robust Machine Learning, in particular machine learning models that are robust to noises and distribution shift.
- ML for Social Good, in particular tackling issues in fairness, bias, and misinformation.
- Multilingual Systems, with a focus on zero-shot transfer to low-resource languages.
- Foundation Models, Generative AI, and unsupervised methods for representation learning.
Contact
Please send all research and job-related inquiries to davisblaine.liang(at)gmail.com.
News
Sep 2, 2023 | We are releasing the Belebele dataset, a first-of-its-kind multilingual reading comprehension dataset spanning 122 language variants, 27 language families, and 29 scripts. [Paper] [Github] [Tweet] |
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Aug 28, 2023 | I had a great time chatting with the New York Times about generative AI and the role of ML talent in supercharging the field of healthcare. |
Apr 2, 2023 | I’m excited to announce that I’m joining Abridge AI to work on reinventing healthcare for doctors and patients alike! |
Jan 28, 2023 | We are releasing XLM-V, a multilingual model with a 1 million token vocabulary [Link]. The model is also open-sourced in HuggingFace Transformers. |
Feb 22, 2022 | After four years at Amazon, I’ll be moving on to a new role. I’ll officially joining Meta AI (formerly Facebook AI) as a Senior Research Scientist in March! |
Selected Publications
Please refer to my Google Scholar for a full list of publications
(*=equal contribution)