I am at Google Brain, working on large-scale systems for machine learning.
Before Google, I worked at Bytedance as a senior research scientist.
I received my Ph.D from UC Berkeley (2018) and my bachelor's degree from Tsinghua (2013) in computer science.
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Papers
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A Unified Architecture for Accelerating Distributed DNN Training in Heterogeneous GPU/CPU Clusters
Yimin Jiang, Yibo Zhu, Chang Lan, Bairen Yi, Yong Cui, and Chuanxiong Guo
OSDI 2020
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A Generic Communication Scheduler for Distributed DNN Training Acceleration
Yanghua Peng, Yibo Zhu, Yangrui Chen, Yixin Bao, Bairen Yi, Chang Lan, Chuan Wu, and Chuanxiong Guo
SOSP 2019
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SafeBricks: Shielding Network Functions in the Cloud
Rishabh Poddar, Chang Lan, Raluca Ada Popa, and Sylvia Ratnasamy
NSDI 2018
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ResQ: Enabling SLOs in Network Function Virtualization
Amin Tootoonchian, Aurojit Panda, Chang Lan, Melvin Walls, Katerina Argyraki, Sylvia Ratnasamy, and Scott Shenker
NSDI 2018
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Embark: Securely Outsourcing Middleboxes to the Cloud
Chang Lan, Justine Sherry, Raluca Ada Popa, Sylvia Ratnasamy, and Zhi Liu
NSDI 2016
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BlindBox: Deep Packet Inspection over Encrypted Traffic
Justine Sherry, Chang Lan, Raluca Ada Popa, and Sylvia Ratnasamy
SIGCOMM 2015
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Blocking-resistant Communication through Domain Fronting
David Fifield, Chang Lan, Rod Hynes, Percy Wegmann, and Vern Paxson
PoPETs 2015
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E2: A Framework for NFV Applications
Shoumik Palkar*, Chang Lan*, Sangjin Han, Keon Jang, Aurojit Panda, Sylvia Ratnasamy, Luigi Rizzo, and Scott Shenker
SOSP 2015
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Explicit Path Control in Commodity Data Centers: Design and Applications
Shuihai Hu, Kai Chen, Haitao Wu, Wei Bai, Chang Lan, Hao Wang, Hongze Zhao, and Chuanxiong Guo
NSDI 2015
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Secure and Scalable Fault Localization under Dynamic Traffic Patterns
Xin Zhang, Chang Lan, and Adrian Perrig
S&P 2012