doi.bio/davis_liang
Davis Liang
Early Life and Education
Davis Liang is a Staff Research Scientist at Abridge AI (formerly Meta AI and Amazon AI). Liang obtained his MS degree in Computer Science from the University of California, San Diego (UCSD), where he was advised by Prof. Gary Cottrell. During his undergraduate studies, Liang worked with Prof. Michael J Tarr exploring how humans perceive faces and scenes.
Career
Liang is currently working on applying his research in multilingual large language models to healthcare. Previously, he was a Senior Research Scientist at Meta AI, working on natural language processing research. Before that, he worked on information retrieval, machine translation, and speech recognition as an Applied Scientist at Amazon (AWS) AI. Liang has also worked as a Software Engineer at Yahoo.
Research
Liang's research interests include:
- Robust Machine Learning, particularly models that are robust to noises and distribution shifts
- ML for Social Good, tackling issues such as 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
Publications
Liang has numerous publications in the field of machine learning and natural language processing, including:
- "XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models" (2023)
- "The BELEBELE Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants" (2023)
- "Attention-guided generative models for extractive question answering" (2021)
- "Embedding-based Zero-shot Retrieval through Query Generation" (2020)
- "Masked language model scoring" (2020)
- "Improve transformer models with better relative position embeddings" (2020)
- "Learning noise-invariant representations for robust speech recognition" (2018)
- "Deep automated multi-task learning" (2017)
Davis Liang
Early Life and Education
Davis Liang is a researcher and Staff Research Scientist at Abridge AI (formerly Meta AI and Amazon AI). Liang obtained his Master's degree in Computer Science from the University of California, San Diego (UCSD), where he was advised by Prof. Gary Cottrell. During his undergraduate studies, Liang worked with Prof. Michael J Tarr to explore how humans perceive faces and scenes.
Career
Liang has held various roles in the tech industry, including:
- Staff Research Scientist at Abridge AI
- Senior Research Scientist at Meta AI
- Applied Scientist at Amazon AWS AI
- Software Engineer at Yahoo
Research Focus
Liang's research interests include:
- Robust Machine Learning: Developing machine learning models that are robust to noises and distribution shifts.
- ML for Social Good: Tackling issues related to fairness, bias, and misinformation.
- Multilingual Systems: Focusing on zero-shot transfer to low-resource languages.
- Foundation Models, Generative AI, and unsupervised methods for representation learning.
Notable Publications
Liang has numerous publications in the field of AI and machine learning. Some of his notable works include:
- "XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models" (2023): Liang et al. propose a new approach to scaling large multilingual vocabularies by de-emphasizing token sharing between languages with minimal lexical overlap.
- "The BELEBELE Benchmark: A Parallel Reading Comprehension Dataset in 122 Language Variants" (2023): Bandarkar et al. highlight the benefits of smaller MLMs pretrained on balanced multilingual data for understanding a broader range of languages.
- "Attention-guided Generative Models for Extractive Question Answering" (2021): Xu et al. propose a simple strategy to obtain extractive answer spans from generative models, leveraging decoder cross-attention patterns.
- "Improve Transformer Models with Better Relative Position Embeddings" (2020): Huang et al. propose new methods to encourage increased interaction between query, key, and relative position embeddings in the self-attention mechanism.
- "Learning Noise-Invariant Representations for Robust Speech Recognition" (2018): Liang, Huang, and Lipton introduce invariant-representation-learning (IRL) to improve speech recognition models' robustness against noise.
Youtube Videos
Youtube Title: Davis Liang endorses Kyle Heiskala on Change Politics
Youtube Link: link
Youtube Channel Name: Change Politics
Youtube Channel Link: https://www.youtube.com/@changepolitics4169
Davis Liang endorses Kyle Heiskala on Change Politics
Youtube Title: Bryson Davis vs Liang Ding Zhong Luo Cage Fighting Series 06 on 11.12.2022
Youtube Link: link
Youtube Channel Name: Dragon House MMA
Youtube Channel Link: https://www.youtube.com/@Dragonhousemma
Bryson Davis vs Liang Ding Zhong Luo Cage Fighting Series 06 on 11.12.2022
Youtube Title: Edwaard Liang's The Veil Between Worlds excerpt | Pacific Northwest Ballet
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Youtube Channel Name: Pacific Northwest Ballet
Youtube Channel Link: https://www.youtube.com/@pacificnorthwestballet
Edwaard Liang's The Veil Between Worlds excerpt | Pacific Northwest Ballet
Youtube Title: Spark Science from Home Ep. 10: Grow from Plant Clippings
Youtube Link: link
Youtube Channel Name: TELUS Spark
Youtube Channel Link: https://www.youtube.com/@TELUSSparkscience
Spark Science from Home Ep. 10: Grow from Plant Clippings
Youtube Title: Alisha Weir's reaction to learning she got the part of Matilda 🥹 #shorts
Youtube Link: link
Youtube Channel Name: Netflix After School
Youtube Channel Link: https://www.youtube.com/@netflixafterschool
Alisha Weir's reaction to learning she got the part of Matilda 🥹 #shorts
Youtube Title: Spark Science from Home Ep. 8 – What makes us human?
Youtube Link: link
Youtube Channel Name: TELUS Spark
Youtube Channel Link: https://www.youtube.com/@TELUSSparkscience
Spark Science from Home Ep. 8 – What makes us human?
Youtube Title: LIVE from Spark in BODY WORLDS: ANIMAL INSIDE OUT - Plastionation Facts with Davis
Youtube Link: link
Youtube Channel Name: TELUS Spark
Youtube Channel Link: https://www.youtube.com/@TELUSSparkscience
LIVE from Spark in BODY WORLDS: ANIMAL INSIDE OUT - Plastionation Facts with Davis
Youtube Title: Curtis on Tour String Sextet at Mondavi Center UC Davis California 3/3/2024
Youtube Link: link
Youtube Channel Name: Pennia California
Youtube Channel Link: https://www.youtube.com/@penniacalifornia9128
Curtis on Tour String Sextet at Mondavi Center UC Davis California 3/3/2024
Youtube Title: Steve Davis „Interesting" Snooker Shot versus Joe Swail !
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Youtube Channel Name: snookasus
Youtube Channel Link: https://www.youtube.com/@snookasus
Steve Davis „Interesting" Snooker Shot versus Joe Swail !
Youtube Title: Finding Janet's Perfect Match at UC Davis
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Youtube Channel Name: lowfat422
Youtube Channel Link: https://www.youtube.com/@lowfat422
Finding Janet's Perfect Match at UC Davis
Youtube Title: Final Round — NAMC National Tournament (2023)
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Youtube Channel Name: National Association of Moot Court
Youtube Channel Link: https://www.youtube.com/@NAMCMootCourt
Final Round — NAMC National Tournament (2023)
Youtube Title: 15 MOST EMOTIONAL SNOOKER MOMENTS
Youtube Link: link
Youtube Channel Name: SNOOKR
Youtube Channel Link: https://www.youtube.com/@SNOOKR
15 MOST EMOTIONAL SNOOKER MOMENTS
Youtube Title: The Wonder Bucket: What are clouds made of?
Youtube Link: link
Youtube Channel Name: TELUS Spark
Youtube Channel Link: https://www.youtube.com/@TELUSSparkscience
The Wonder Bucket: What are clouds made of?
Youtube Title: Mark King Suspended from World Snooker Tour: What Happened ?
Youtube Link: link
Youtube Channel Name: The Cueist
Youtube Channel Link: https://www.youtube.com/@TheCueist
Mark King Suspended from World Snooker Tour: What Happened ?
Youtube Title: When Steve Davis Faced A 17-Year-Old Ronnie O'Sullivan…
Youtube Link: link
Youtube Channel Name: WST
Youtube Channel Link: https://www.youtube.com/@worldsnookertour
When Steve Davis Faced A 17-Year-Old Ronnie O'Sullivan...
Youtube Title: Moments That Made O'Sullivan & Ding Laugh
Youtube Link: link
Youtube Channel Name: WST
Youtube Channel Link: https://www.youtube.com/@worldsnookertour
Moments That Made O'Sullivan & Ding Laugh
Youtube Title: Times Referees RUINED The Snooker Matches..
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Youtube Channel Name: SNOOKR
Youtube Channel Link: https://www.youtube.com/@SNOOKR
Times Referees RUINED The Snooker Matches..