Zewei Mo


Bio

I am a Senior Deep Learning Performance Engineer at Baidu, and I was a CS PhD student in the Department of Computer Science at University of Pittsburgh from 2023 to 2024. From July 2022 to July 2023, I worked at Intel as a GCC compiler engineer. Prior to that, I gained my M.Eng. degree with Professor Xianwei Zhang as my graduate advisor in arcSYSu at Sun Yat-sen University. And I received my B.Eng. degree in Software Engineering at South China University of Technology in 2020.

News

Publications

#: equal contribution

FMCC: Flexible Measurement-based Quantum Computation over Cluster State

Yingheng Li, Aditya Pawar, Zewei Mo, Youtao Zhang, Jun Yang, Xulong Tang

ASPLOS 2024 (appeared in ASPLOS 2025)

QRCC: Evaluating Large Quantum Circuits on Small Quantum Computers through Integrated Qubit Reuse and Circuit Cutting

Aditya Pawar, Yingheng Li, Zewei Mo, Yanan Guo, Xulong Tang, Youtao Zhang, Jun Yang

ASPLOS 2024 (appeared in ASPLOS 2025)

FCM: A Fusion-aware Wire Cutting Approach for Measurement-based Quantum Computing

Zewei Mo, Yingheng Li, Aditya Pawar, Xulong Tang, Jun Yang and Youtao Zhang

DAC 2024

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

Zejia Lin#, Zewei Mo#, Xuanteng Huang, Xianwei Zhang, Yutong Lu

ICCD 2023

RollBin: reducing code-size via loop rerolling at binary level

Tianao Ge, Zewei Mo, Kan Wu, Xianwei Zhang, Yutong Lu

LCTES 2022

moTuner: a compiler-based auto-tuning approach for mixed-precision operators

Zewei Mo, Zejia Lin, Xianwei Zhang, Yutong Lu

CF 2022

Experience

Baidu Corporation, China                                Dec 2024 - Now
Senior Deep Learning Performance Engineer Intel Corporation, China                                Jun 2022 - Jul 2023
GCC Compiler Engineer

Teaching

Awards

MISC