Jihao Xin

Jihao Xin

Ph.D. Student in Machine Learning Systems

KAUST, Saudi Arabia

👋 I’m a PhD student in computer science, working with Prof. Marco Canini at SANDS Lab. My research interests lie between computer systems and machine learning, devoting to speedup deep learning training and inference via efficient communication. My recent work focuses on gradient compression and optimized GPU communication.

Paper

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(2025). Assassyn: A Unified Abstraction for Architectural Simulation and Implementation. ISCA'25.

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(2025). Global QSGD: Allreduce-Compatible Quantization for Distributed Learning with Theoretical Guarantees. EuroMLSys'25.

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(2024). Immediate Communication for Distributed AI Tasks. HotInfra'24.

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(2023). Kimad: Adaptive Gradient Compression with Bandwidth Awareness. DistributedML'23.

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(2022). A Convolutional Neural Network Based Maximum Power Point Voltage Forecasting Method for Pavement PV Array. TIM'22 (JCR Q1).

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Education

 
 
 
 
 
KAUST
Ph.D. student in Computer Science
January 2023 – Present Thuwal, Saudi Arabia
  • KAUST Graduate Student Council Representative (12/1683) (2024-2025)
  • TA-KAUST CS240: Computing Systems and Concurrency (2022 Fall, 2024Fall)
  • TA-Saudi Ministry of Interior Program CS229: Machine Learning (2023 Spring)
  • TA-UESTC Boot Camp (2022 Summer, 2023 Summer)
  • TA-CS398 Graduate Seminar (2025 Spring)
 
 
 
 
 
KAUST
Master of Science in Computer Science
August 2021 – December 2022 Thuwal, Saudi Arabia
  • Dean’s List Award (2023)
  • GPA = 3.88/4.0
 
 
 
 
 
Imperial College London
Master of Science in Applied Computational Science and Engineering (Distinction)
October 2020 – October 2021 London, UK
 
 
 
 
 
Shandong University
Bachelor of Engineering in Computer Science and Technology (GPA = 89.34/100)
September 2016 – June 2020 Weihai, China

Internship

 
 
 
 
 
Microsoft Research Asia
Research Intern
Microsoft Research Asia
September 2023 – March 2024 Beijing, China
 
 
 
 
 
ISTAustria
Research Intern
ISTAustria
May 2022 – August 2022 Klosterneuburg, Austria
TopK gradient compression with efficient threshold selection by CUDA/C++.
 
 
 
 
 
Tencent Cloud
Engineering Intern
Tencent Cloud
August 2019 – November 2019 Shenzhen, China
Tencent international website backend developer by GoLang.
 
 
 
 
 
The University of Western Australia
Research Intern
The University of Western Australia
June 2019 – August 2019 Remote
YOLO-based splash detection of Western Australia’s coastal highway by Python.

Experience

uwa
Summer Research Program - The University of Western Australia
ICL
Robotics & AI Winter School - Imperial College London Hamlyn Center

I’m into …

Linux
C++/CUDA
Python/PyTorch

Gallery of KAUST

Contact

  • 966560569149
  • KAUST Campus, Thuwal, Mekka Province 23955
  • 4307-WS18, 4th Floor, Building 1