Qizhen Zhang

I am an Assistant Professor of Computer Science at the University of Toronto, where I lead the Far Data Lab (FDL). I am broadly interested in data management and computer systems. My research has been bridging cloud data processing systems and data center networks to address emerging challenges in hyperscale data processing.

Email, CV, Google Scholar, LinkedIn

I am actively looking for motivated students to work on cloud data systems, data center networking, and interactions between ML and systems. Come join us at FDL. If you are interested, please apply to UofT CS and mention my name. Feel free to drop me an email.

News

Oct. 2024DPDPU is accepted at CIDR 2025
Sep. 2024I finally moved to Toronto
Jul. 2024Vision paper on data processing with DPUs is available on arXiv
Jun. 2024DDS is accepted at VLDB 2024
Feb. 2024I am visiting the National University of Singapore
Feb. 2024Vision paper on cloud-native LMs is available on arXiv
May  2023Cowbird is accepted at SIGCOMM 2023
Mar. 2023I will teach memory-disaggregated DBMSs at SIGMOD 2023
Oct. 2022TeShu is accepted at CIDR 2023
Aug. 2022I am now at Microsoft Research
Aug. 2022FlexChain is accepted at VLDB 2023
Aug. 2022I defended my dissertation and received my Ph.D.
Jun. 2022I will join the University of Toronto as an Assistant Professor in Fall 2023
Mar. 2022My work is recognized with Penn's best CS dissertation award (Rubinoff Award)
Dec. 2021TELEPORT is accepted at SIGMOD 2022 (happening in Philly next year!)
Oct. 2021Redy is accepted at VLDB 2022
Oct. 2021CompuCache is accepted at CIDR 2022
Apr. 2021MimicNet is accepted at SIGCOMM 2021
Apr. 2020Understanding DBMSs in DDCs is accepted at VLDB 2020
Oct. 2019Rethinking data processing systems in DDCs is accepted at CIDR 2020
Mar. 2019I am selected as the 2019-2020 Jonathan M. Smith Fellow
Nov. 2018GraphRex is accepted at SIGMOD 2019
Aug. 2017Predicting startup crowdfunding success is accepted at CIKM 2017
Jul. 2017Analyzing the performance and cost of graph systems is accepted at SoCC 2017
Aug. 2016I started Ph.D. studies at the University of Pennsylvania

Research

Today's largest data processing workloads are hosted in cloud data centers. Due to unprecedented data growth, these workloads have ballooned to hyperscale level, encompassing billions to trillions of data items and hundreds to thousands of machines per query. Enabling and expanding with these workloads are highly scalable data center networks that connect up to hundreds of thousands of networked servers. At hyperscale, the classic layered designs are no longer sustainable: without knowing how their data is transferred in the network, applications can make egregious decisions in executions; the cloud infrastructure also performs poorly without rethinking the interfaces and services exposed to its applications. Rather than optimize these massive layers in silos, I build systems across them with principled network-centric designs for efficient hyperscale data processing.

  • In current networks, we design data processing systems by adopting network awareness. Considering data center network characteristics in optimizing distributed operations effectively reduces communication cost at hyperscale. We built GraphRex [SIGMOD '19], the first system that systematically adopts network awareness for large-scale graph processing. We also proposed TeShu [CIDR '23], a shuffle layer that encompasses network-aware optimizations and offers them to a variety of distributed data processing systems with templates.

I have also worked on other aspects of data processing, including data science application with machine learning [CIKM '17], and data processing cost efficiency [SoCC '17]. Recently, I proposed CompuCache [CIDR '22], a new cloud service that exploits spot VMs for remote caching and memory-intensive compute offloading.

Publications

* students I advise

DPDPU: Data Processing with DPUs [arXiv]
Jiasheng Hu*, Philip Bernstein, Jialin Li, Qizhen Zhang
Conference on Innovative Data Systems Research, CIDR 2025, to appear

DDS: DPU-optimized Disaggregated Storage
Qizhen Zhang, Philip Bernstein, Badrish Chandramouli, Jiasheng Hu*, Yiming Zheng*
International Conference on Very Large Data Bases, VLDB 2024

Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native
Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo
CoRR, arXiv:2401.12230, 2024

Cowbird: Freeing CPUs to Compute by Offloading the Disaggregation of Memory
Xinyi Chen, Liangcheng Yu, Vincent Liu, Qizhen Zhang
Annual Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2023

Disaggregated Database Systems
Jianguo Wang, Qizhen Zhang
ACM International Conference on Management of Data, SIGMOD 2023 Tutorial

FlexChain: An Elastic Disaggregated Blockchain
Chenyuan Wu, Mohammad Javad Amiri, Jared Asch, Heena Nagda, Qizhen Zhang, Boon Thau Loo
International Conference on Very Large Data Bases, VLDB 2023

Templating Shuffles
Qizhen Zhang, Jiacheng Wu, Ang Chen, Vincent Liu, Boon Thau Loo
Conference on Innovative Data Systems Research, CIDR 2023

Optimizing Data-intensive Systems in Disaggregated Data Centers with TELEPORT
Qizhen Zhang, Xinyi Chen, Sidharth Sankhe, Zhilei Zheng, Ke Zhong, Sebastian Angel, Ang Chen, Vincent Liu, Boon Thau Loo
ACM International Conference on Management of Data, SIGMOD 2022

Redy: Remote Dynamic Memory Cache
Qizhen Zhang, Philip Bernstein, Daniel Berger, Badrish Chandramouli
International Conference on Very Large Data Bases, VLDB 2022

CompuCache: Remote Computable Caching using Spot VMs
Qizhen Zhang, Philip Bernstein, Daniel Berger, Badrish Chandramouli, Vincent Liu, Boon Thau Loo
Conference on Innovative Data Systems Research, CIDR 2022

MimicNet: Fast Performance Estimates for Data Center Networks with Machine Learning
Qizhen Zhang, Kelvin K.W. Ng, Charles W. Kazer, Shen Yan, João Sedoc, Vincent Liu
Annual Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2021

Understanding the Effect of Data Center Resource Disaggregation on Production DBMSs
Qizhen Zhang, Yifan Cai, Xinyi Chen, Sebastian Angel, Ang Chen, Vincent Liu, Boon Thau Loo
International Conference on Very Large Data Bases, VLDB 2020

Rethinking Data Management Systems for Disaggregated Data Centers
Qizhen Zhang, Yifan Cai, Sebastian Angel, Ang Chen, Vincent Liu, Boon Thau Loo
Conference on Innovative Data Systems Research, CIDR 2020

Optimizing Declarative Graph Queries at Large Scale
Qizhen Zhang, Akash Acharya, Hongzhi Chen, Simran Arora, Ang Chen, Vincent Liu, Boon Thau Loo
ACM International Conference on Management of Data, SIGMOD 2019

Predicting Startup Crowdfunding Success through Longitudinal Social Engagement Analysis
Qizhen Zhang, Tengyuan Ye, Meryem Essaidi, Shivani Agarwal, Vincent Liu, Boon Thau Loo
ACM International Conference on Information and Knowledge Management, CIKM 2017

Architectural Implications on the Performance and Cost of Graph Analytics Systems
Qizhen Zhang, Hongzhi Chen, Da Yan, James Cheng, Boon Thau Loo, Purushotham Bangalore
ACM Symposium on Cloud Computing, SoCC 2017

Earlier Publications

Quegel: A General-Purpose System for Querying Big Graphs
Qizhen Zhang, Da Yan, James Cheng
Proceedings of the 2016 International Conference on Management of Data, SIGMOD 2016 Demo

A General-Purpose Query-Centric Framework for Querying Big Graphs
Da Yan, James Cheng, M. Tamer Özsu, Fan Yang, Yi Lu, John C. S. Lui, Qizhen Zhang, Wilfred Ng
International Conference on Very Large Data Bases, VLDB 2016

A Shapley Value Approach for Cost Allocation in the Cloud
Qizhen Zhang, Haoran Wang, Yang Chen, Tao Qin, Ying Yan, Thomas Moscibroda
ACM Symposium on Cloud Computing, SoCC 2015 Poster

Teaching

CSCC43: Introduction to Databases
University of Toronto, Winter 2025 / Summer 2024

CSC2531: Cloud-native Data Management Systems
University of Toronto, Winter 2025

CSC2229: Topics in Computer Networks: Cloud Computing
University of Toronto, Winter 2024

Professional Activities

Service

Program Committee: SIGMOD 2025, VLDB 2025, ICDE 2025, SIGMOD 2024, EuroSys 2024, EDBT 2024, SoCC 2023, CIKM 2023, ICDE 2023, SoCC 2022, CIKM 2022

Session Chair: VLDB 2023, Northwest Database Society (NWDS) Annual Meeting 2023, SoCC 2022, SIGMOD 2022

Journal Reviewer:
IEEE/ACM Transactions on Networking 2023
IEEE Transactions on Knowledge and Data Engineering 2023
IEEE/ACM Transactions on Networking 2022
IEEE Transactions on Parallel and Distributed Systems 2022
IEEE Transactions on Knowledge and Data Engineering 2022

Organizer:
FDL Reading Group, University of Toronto, Fall 2024
DSL Seminar, University of Pennsylvania, Spring 2017 and Fall 2017

Talks

Offloading the Tax of Disaggregation
Invited talk, National University of Singapore, Singapore, March 2024

Memory-disaggregated Database Systems
SIGMOD 2023, Seattle, Washington, United States, June 2023

Templating Shuffles
Northwest Database Society (NWDS) Annual Meeting 2023, Redmond, Washington, United States, May 2023

Redy: Remote Dynamic Memory Cache
VLDB 2022, Virtual, September 2022

Optimizing Data-intensive Systems in Disaggregated Data Centers with TELEPORT
SIGMOD 2022, Philadelphia, Pennsylvania, United States, June 2022

Hyperscale Data Processing with Network-centric Designs
Job talk, February - April 2022
CMU, HKUST, NUS, Ohio State U., Simon Fraser U., UC Irvine, UIUC, U. Minnesota Twin Cities, U. Toronto, U. Virginia, U. Waterloo

CompuCache: Remote Computable Caching using Spot VMs
CIDR 2022, Virtual, January 2022

MimicNet: Fast Performance Estimates for Data Center Networks with Machine Learning
SIGCOMM 2021, Virtual, August 2021

Understanding the Effect of Data Center Resource Disaggregation on Production DBMSs
VLDB 2020, Virtual, September 2020
Microsoft Research, Virtual, August 2020

Rethinking Data Management Systems for Disaggregated Data Centers
CIDR 2020, Amsterdam, Netherlands, January 2020

Optimizing Declarative Graph Queries at Large Scale
Microsoft Research, Redmond, Washington, United States, August 2019
SIGMOD 2019, Amsterdam, Netherlands, July 2019

Predicting Startup Crowdfunding Success through Longitudinal Social Engagement Analysis
CIKM 2017, Singapore, November 2017

Architectural Implications on the Performance and Cost of Graph Analytics Systems
SoCC 2017, Santa Clara, California, United States, September 2017

Industrial Experiences

Microsoft Research, Redmond, August 2022 - August 2023
Cloud data management

Microsoft Research, Redmond, Summer 2021
CompuCache: fast and cheap compute offloading for remote memory caching with spot VMs

Microsoft Research, Redmond, Summer 2020
Redy: high-performance RDMA-accessible caching with remote dynamic memory

Microsoft Research, Redmond, Summer 2019
Large-scale SQL query optimization with a focus on search completeness and efficiency

NEC Labs, America, Summer 2018
Software behavior analysis based on provenance graphs for anomaly detection

Microsoft Research Asia, September 2014 - June 2015
Resource cost allocation for multi-tenant clouds with game theory

Last edit in October 2024