I am a second year PhD Student at Georgia tech, advised by Xu Chu. I am interested in the intersection of machine learning and systems. I currently work on building a declarative system for improving fairness in machine learning. Also, I am interested in using machine learning techniques to accelerate database engines. Prior to joining Georgia Tech 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.
- Feb, 2021: Our work "OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning" is accepted at SIGMOD 2021.
- Aug, 2019: I finished my internship at Alibaba and joined Gerogia Tech as a PhD student.
- Ph.D. Student, Georgia Insititute of Technology, 2019.8 - Current
- M.S., ETH Zurich, 2014.9 - 2017.4
- B.S., Peking University, 2010.9 - 2014.6
OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning [paper to appear later]
Hantian Zhang, Xu Chu, Abolfazl Asudeh, Sham Navathe
ALEX: An Updatable Adaptive Learned Index [paper]
Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Jaeyoung Do, Yinan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David Lomet, Tim Kraska
Accelerating generalized linear models with MLWeaving: a one-size-fits-all system for any-precision learning [paper]
Zeke Wang, Kaan Kara, Hantian Zhang, Gustavo Alonso, Onur Mutlu, Ce Zhang
Speeding up Percolator [paper]
John T Halloran, Hantian Zhang, Kaan Kara, Cedric Renggli, Matthew The, Ce Zhang, David M Rocke, Lukas Käll, William Stafford Noble
Journal of Proteome Research 2019
MLBench: Benchmarking Machine Learning Services Against Human Experts [paper]
Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data [paper]
Min Su, Hantian Zhang, Kevin Schawinski, Ce Zhang, Michael A Cianfrocco
PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light [paper][project]
Dominic Stark, Barthelemy Launet, Kevin Schawinski, Ce Zhang, Michael Koss, M Dennis Turp, Lia F Sartori, Hantian Zhang, Yiru Chen, Anna K Weigel.
ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning [paper]
Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang
Generative adversarial networks recover features in astrophysical images of galaxies beyond the deconvolution limit. [paper] [project]
Ce Zhang, Kevin Schawinski,Hantian Zhang, Lucas Fowler, Gokula Krishnan Santhanam
Scalable Inference of Decision Tree Ensembles: Flexible Design for CPU-FPGA Platforms [paper]
Muhsen Owaida, Hantian Zhang, Ce Zhang, Gustavo Alonso