About Me

I am a first year Ph.D student advised by Ce Zhang at ETH Zurich. My research focus on speeding up machine learning systems and making them more accessible to users. Prior to joining ETH as a Ph.D student, I got my Master's degree in Computer Science at ETH Zurich in 2017 and my Bachelor's degree in Machine Intelligence at Peking University in 2014.


  • May.18th, 2018: Our work "MLBench: Benchmarking Machine Learning Services Against Human Experts" is accepted at VLDB 2018.
  • Mar.20th, 2018: Our work "PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light" is accepted by Monthly Notices of the Royal Astronomical Society (MNRAS).
  • Aug.10th, 2017: I presented our ZipML paper at ICML 2017.
  • Jun.26th, 2017: Our work "Scalable Inference of Decision Tree Ensembles: Flexible Design for CPU-FPGA Platforms" is accepted at FPL 2017.
  • Jun.20th, 2017: I got ICML travel award for this year. Big thank you to ICML commitee!
  • May.12th, 2017: Our ZipML work "The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning" is accepted at ICML 2017
  • May.10th, 2017: I gave a talk "Faster Machine Learning via Low-Precision Communication and Computation" with Dan Alistarh at Nvidia GPU Technology Conference (GTC) 2017.


Scalable Inference of Decision Tree Ensembles: Flexible Design for CPU-FPGA Platforms
Muhsen Owaida, Hantian Zhang, Ce Zhang, Gustavo Alonso
FPL 2017

MLBench: Benchmarking Machine Learning Services Against Human Experts
Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
VLDB 2018

Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data
Min Su, Hantian Zhang, Kevin Schawinski, Ce Zhang, Michael A Cianfrocco
bioRxiv 2018


  • Ph.D. Student, ETH Zurich, 2017.5 - Present
  • M.S., ETH Zurich, 2014.9 - 2017.4
  • B.S., Peking University, 2010.9 - 2014.6