Biography

Chen-Yu started his Ph.D. in fall, 2018 at KAUST.

Combining his interests in fundamental systems and the trend of machine learning, Chen-Yu is collaborating with colleagues on developing efficient distributed machine learning systems, to be specific, trying to alleviate network bandwidth bottleneck by offloading aggregation operations to network devices (see DAIET).

During his time at Academia Sinica, Taiwan, Chen-Yu worked on techniques for digitalizing handwriting and ancient Chinese calligraphy.

Interests

  • Distributed Machine Learning Systems

Education

  • B.S. in Engineering Science and Ocean Engineering, 2016

    National Taiwan University

Recent Publications

Natural Compression for Distributed Deep Learning

Due to their hunger for big data, modern deep learning models are trained in parallel, often in distributed environments, where …

Scaling Distributed Machine Learning with In-Network Aggregation

Training complex machine learning models in parallel is an increasingly important workload. We accelerate distributed parallel training …

Projects

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AR-Navigator

JUNCTIONxKAUST 2018 second prize. Integrate Augmented Reality to indoor navigation.

Daiet

DAIET performs data aggregation along network paths using programmable network devices to alleviate communication bottlenecks in …

Shaheen Supercomputer Evaluation

Evaluate different processors architectures and programming environment and to reach the technical specifications provided by the chip …

Chinese Character Extraction

Extract handwritten Chinese characters from manuscripts

handwriting.js

A simple API for the incredible handwriting recognition of Google IME

Font Embedding

efficiently embed Chinese fonts to webpages

Curriculum Vitae

Last Update: November 2019

Contact

  • King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah 23955-6900
  • Enter Building 1 and take the lift to work cell 4409-WS17 on Floor 4
  • Please note that the weekend in Saudi Arabia is Friday and Saturday.