Luke Hsiao
Luke Hsiao
Principal Engineer
Numbers Station

I am a principal engineer at Numbers Station working on cloud infrastructure and backend services.

Previously, I was a software engineer in the Network Infrastructure Group at Google and worked on TCP in Linux.

I completed my Ph.D. in electrical engineering at Stanford University, advised by Phil Levis and Keith Winstein and with the collaboration of Chris Ré. My dissertation focused on making electronic component information more accessible by using machine learning to build knowledge bases directly from PDF datasheets. While in grad school, I also researched low-latency, foveated video compression for future VR systems, built drivers at NVIDIA, and implemented optimizations for Linux networking at Google.

Before Stanford, I graduated summa cum laude from Brigham Young University with a B.S. in computer engineering and worked mainly on embedded systems and FPGA reliability with Mike Wirthlin.

Research

Select publications, in reverse chronological order.

Peer-Reviewed Papers

Towards Retina-Quality VR Video Streaming: 15ms Could Save You 80% of Your Bandwidth
L. Hsiao, B. Krajancich, P. Levis, G. Wetzstein, and K. Winstein
ACM SIGCOMM Computer Communication Review, Jan. 2022

code press release

Creating Hardware Component Knowledge Bases with Training Data Generation and Multi-task Learning
L. Hsiao, S. Wu, N. Chiang, C. Ré, and P. Levis
ACM Transactions on Embedded Computing Systems (TECS), Sept. 2020

code data

Automating the Generation of Hardware Component Knowledge Bases
L. Hsiao, S. Wu, N. Chiang, C. Ré, and P. Levis
Languages, Compilers, and Tools for Embedded Systems (LCTES), Jun. 2019

code data slides poster

Fonduer: Knowledge Base Construction from Richly Formatted Data
S. Wu, L. Hsiao, X. Cheng, B. Hancock, T. Rekatsinas, P. Levis, and C. Ré
ACM Conference on Management of Data (SIGMOD), May 2018

code slides poster talk

Smart Contracts for Machine-to-Machine Communication: Possibilities and Limitations
Y. Hanada, L. Hsiao, and P. Levis
IEEE Conference on Internet of Things and Intelligence Systems (IOTAIS), Nov. 2018

slides

Estimating Soft Processor Soft Error Sensitivity through Fault Injection
N. Harward, M. Gardiner, L. Hsiao, M. Wirthlin
IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM), May 2015

A Fault Injection System for Measuring Soft Processor Design Sensitivity on Virtex-5 FPGAs
N. Harward, M. Gardiner, L. Hsiao, M. Wirthlin
Workshop on FPGAs for Aerospace Applications (FASA), Sept. 2014

Preprints

The Price of Free Illegal Live Streaming Services
H. Ayers and L. Hsiao
arXiv, Jan. 2019

TCPTuner: Congestion Control Your Way
K. Miller and L. Hsiao
arXiv, May 2016

code

Misc. Projects