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Recent News

I am recruiting Master's and PhD students working on distributed systems, with a focus on the intersection of blockchains, machine learning, cloud computing, and data management. If you're interested, please contact me at gengrui.zhang@concordia.ca

> [Nov, 24] I will be serving as a PC member at Middleware'25

> [Oct, 24] Janus, making CRDTs not so eventual, is accepted by VLDB'25

> [Aug, 24] I will be serving as a PC member at ICDE'25

> [Mar, 24] I will be serving as a PC member at DAPPS'24

> [Dec, 24] PrestigeBFT, a novel reputation-based BFT consensus algorithm, is accepted by ICDE'24

> [Oct, 23] Drone, a resource orchestration framework for containerized clouds, is accepted by SoCC'23

Short Bio

​I am a tenure-track Assistant Professor in the Department of Electrical & Computer Engineering at Concordia University, where I lead the Research Group of Distributed Computing and Systems (DISCOS).

 

Prior to joining Concordia, I received my PhD from the University of Toronto in 2024, advised by Hans-Arno Jacobsen.​​ My full CV is available here.
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My research focuses on designing and developing distributed systems with three core attributes: high performance, high scalability, and high availability (3H properties). Specifically,

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  • How can we obtain higher performance with respect to increasing throughput and reducing latency?

  • How can we efficiently scale distributed applications while minimizing performance degradation?

  • How can we improve system availability bolstering robustness such that operation is least interrupted under a wide range of failures?​

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My research encompasses the entire spectrum from theoretical foundations to practical implementation. This includes rigorous mathematical modeling and analysis, the design of new algorithms and architecture, formal proofs, implementation, deployment, and evaluation. 

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​By advancing the 3H properties, my work contributes to both the theoretical foundations and the development of various distributed applications such as blockchains, cloud computing, data management, and distributed machine learning.​​

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DISCOS​

Research Group of Distributed Computing and Systems

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