Hao Wang in

Hao Wang

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Research Scientist at RedHat AI Innovation Team
📍 Cambridge, Massachusetts, United States

Hao Wang is an information theorist and research scientist at RedHats AI Innovation Team and the MIT-IBM Watson AI Lab. A Harvard PhD graduate, his work centers on building reliable and accessible machine learning systems, specializing in efficient foundation models, AI privacy, and trustworthy algorithms.

He developed a method that allows large language models to identify and skip redundant internal blocks during inference, which improves efficiency without requiring any retraining of the original model.

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Experience
3 Years
Current Role
Research Scientist
Location
Cambridge, Massachusetts, United States
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Priorities

Topics Hao cares about

Efficient LLM Inference
His recent work, including SQuat and methods for skipping attention blocks, aims to improve the scalability and memory efficiency of large language models during inference.
AI Privacy
He is actively developing solutions for contextual privacy when communicating with LLMs, ensuring only necessary, non-sensitive information is shared with large models.
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Career

Work history

12-2024
Research Scientist
RedHat AI Innovation Team
9-2022
Research Staff Member
MIT-IBM Watson AI Lab
5-2019 - 8-2019
Research Intern
IBM Thomas J. Watson Research Center
In the press

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Education
8-2016 - 5-2022
Doctor of Philosophy - PhD
Harvard John A. Paulson School of Engineering and Applied Sciences
9-2012 - 7-2016
Bachelor of Science - BS
University of Science and Technology of China
Social presence
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Behavioral profile

DISC profile (public)

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