Qizhen Zhang

I am an Assistant Professor of Computer Science at the University of Toronto, where I lead the Far Data Lab (FDL), and am part of the Systems & Networks Group.

qz@cs.toronto.edu
Bahen Center 5234, 40 St. George Street, Toronto, ON M5S 2E4

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.

Research

I am interested broadly in data management and computer systems and networking, particularly in problems that arise and mechanisms that are effective at massive scales. My research has been bridging data processing systems and computer networks to address emerging challenges in large-scale data processing. Some of the projects I work on:

High-performance low-cost cloud databases with DPUs

dpKernels [VLDB '26], computing primitives that harvest DPU accelerators for data-path efficiency

DDS [VLDB '24], a DPU-optimized disaggregated storage architecture

DPDPU [CIDR '25], research initiative for data processing with DPUs

Massive database acceleration in AI data centers

MGI [VLDB '26], a general communication interface for databases to access massive GPU infrastructures

RidgeWalker [HPCA '26], a fully pipelined FPGA architecture for graph random walks

Efficient systems on disaggregated hardware

PD3 [NSDI '26], a DPU prefetcher for disaggregated memory

Cowbird [SIGCOMM '23], an in-network communication offloading system for disaggregated memory

FlexChain [VLDB '23], a disaggregated blockchain architecture

TELEPORT [SIGMOD '22], a compute pushdown framework for disaggregated data centers

Effect of DDCs [VLDB '20], a study of production DBMS behavior on disaggregated resources

Rethinking DDCs [CIDR '20], a call to redesign data systems for disaggregated data centers

Hyperscale networking and data processing

Shuffle Templates [CIDR '23], a portable abstraction for network-aware data shuffling in data centers

CompuCache [CIDR '22], remote caching and compute offloading with spot VMs

Redy [VLDB '22], a system that harvests remote memory for database caching via RDMA

MimicNet [SIGCOMM '21], a scalable simulation framework for data center networks via ML approximation

GraphRex [SIGMOD '19], a declarative network-aware graph processing system

Globally distributed systems

GFedCL [ICML '26], federated continual learning that addresses forgetting and heterogeneity

SaTE [SIGCOMM '25], low-latency traffic engineering for satellite networks

Publications

MGI: A Communication Framework for Data Processing in Massive GPU Infrastructures
Di Wu, Hongshi Tan, Hanzhang Yang, Bingsheng He, Qizhen Zhang
International Conference on Very Large Data Bases, VLDB 2026, to appear

dpKernels: Harvesting DPU Compute Resources for Data-path Efficiency in Cloud Data Processing
Jiasheng Hu, Kaiwen Zheng, Anna Li, Sidharth Sankhe, Philip A. Bernstein, Qizhen Zhang
International Conference on Very Large Data Bases, VLDB 2026, to appear

GFedCL: Graph-Based Federated Continual Learning with Spatial and Temporal Awareness
Qingyang Yu, Yang Hua, Qizhen Zhang, Hao Wang
International Conference on Machine Learning, ICML 2026, to appear

PD3: Prefetching Data with DPUs for Disaggregated Memory
Sidharth Sankhe, Felix Zhang, Umayrah Chonee, Sherman Lim, Jiasheng Hu, Jialin Li, Qizhen Zhang
USENIX Symposium on Networked Systems Design and Implementation, NSDI 2026

RidgeWalker: Perfectly Pipelined Graph Random Walks on FPGAs
Hongshi Tan, Yao Chen, Xinyu Chen, Qizhen Zhang, Cheng Chen, Weng-Fai Wong, Bingsheng He
IEEE International Symposium on High-Performance Computer Architecture, HPCA 2026

Full List

Students

I have been fortunate to work with a group of terrific students.

PhD
Jiasheng Hu
Di Wu
Hanzhang Yang

MSc
Amogh Joshi
Felix Zhang
Brenden Wang (with Niv Dayan)

And other brilliant students at UofT and other places.

Teaching

CSCC43: Introduction to Databases
University of Toronto, Fall 2026

CSCC43: Introduction to Databases
University of Toronto, Fall 2025

CSC2235: Cloud-native Data Management Systems
University of Toronto, Fall 2025

CSCC43: Introduction to Databases
University of Toronto, Winter 2025

CSC2235: Cloud-native Data Management Systems
University of Toronto, Winter 2025

CSCC43: Introduction to Databases
University of Toronto, Summer 2024

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

Professional Activities

Service

Program Committee
SIGMOD 2027, VLDB 2027, CIDR 2027
SIGMOD 2026, VLDB 2026, SIGCOMM 2026, NSDI 2026, EuroSys 2026, HardBD&Active@ICDE 2026 (Chair)
SIGMOD 2025, VLDB 2025, ICDE 2025, WWW 2025, APSys 2025
SIGMOD 2024, EuroSys 2024, EDBT 2024
SoCC 2023, CIKM 2023, ICDE 2023
SoCC 2022, CIKM 2022

Journal Reviewer
ACM Transactions on Database Systems Review Board 2025 - 2026
ACM Transactions on Database Systems 2024
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

Talks

Data Processing with DPUs
Seminar talk, Peking University, Beijing, China, July 2025
Plenary talk, International Congress of Basic Science, Beijing, China, July 2025
Seminar talk, ETH Zürich, Zürich, Switzerland, February 2025

Offloading the Tax of Disaggregation
Seminar 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 June 2026