We are a computer science research group led by Ce Zhang with help from many close collaborators and friends.

Members Publications

One-pager Research Statement

Research Blog

Our research blog contains the latest updates of our research projects.

Research Projects (Blog)



  • space.ml is featured in a News article in the Science magazine [link].
  • GalaxyGAN is selected as the Editor’s Choice in the Science magazine [link].

VLDB 2017 (Munich Aug 28 – Sep 1)

  • Come by our two talks: Lele Yu on building Bayesian Inference as a new service with hundreds of machines; Zhipeng Zhang on a comparative study on different SimRank algorithms [paper]. 
  • Also don’t miss the demo session: Xupeng Li on ease.ml version 1 — declarative in-database machine learning with a cute homomorphism between relational algebra and linear algebra [paper].

ICML 2017 (Sydney Aug 6 – Aug 11)

  • Hantian Zhang is going to give a talk about ZipML — low precision machine learning on modern hardware [paper].

SIGMOD 2017 (Chicago May 14 – May 19)

  • Jiawei Jiang gave the talk about a distributed machine learning system designed for heterogeneous infrastructure where straggler is expected [paper].
  • HILDA: Come by to hear our vision about ease.ml — Deep Learning in four lines to serve ETH scientists [paper].

Machine Learning on Modern Hardware

  • Kaan Kara: training linear models on FPGA with low precision [FCCM paper]
  • Ewaida Mohsen: Xgboost inference on FPGA that can deal with up to 20M tuples per second [FPL]!

space.ml (with Kevin Schawinski) gets covered by Science (Editor’s Choice), the Atlantic, and WIRED Science.

An ETH Globe article about DS3Lab.

Ce gives talks at ETH Meets New York and his Inaugural Lecture at ETH.
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Hantian and Dan give the ZipML session at NVIDIA GTC 2017