Run Wang

Run Wang

PhD Student at Integrated Systems Laboratory (IIS), ETH Zürich

ETH Zurich

Biography

I am currently pursuing a Ph.D. at the Integrated Systems Laboratory (IIS), ETH Zurich, under the supervision of Prof. Luca Benini. My research focuses on hardware/software co-design for efficient computing architectures, with an emphasis on accelerating machine learning workloads through tightly coupled hardware and compiler optimizations.

Before starting my Ph.D., I completed my Master’s degree in Electrical Engineering at ETH Zurich, where I specialized in digital IC architecture design and explored machine learning applications in hardware-efficient systems. I received my Bachelor’s degree in Electrical Engineering from Fudan University (2018–2022), with a focus on biomedical engineering.

Interests

  • Hardware & Software Codesign
  • TinyML
  • ML Compiler

Education

  • M.S. Information Technology and Electrical Engineering, 2022

    ETH Zurich

  • B.E. electrical engineering (Honours), 2018

    Fudan University

Experience

 
 
 
 
 

PhD Student

IIS ETH

Oct 2025 – Oct 2029
On-Device LLM Fine-Tuning and Hardware-Software Co-Design
 
 
 
 
 

Master Thesis

IIS ETH

Jan 2025 – Jul 2025
On-Device Learning on Heterogeneous SoCs with Software-Managed Caches
 
 
 
 
 

Compiler Intern

Buddy Compiler

Jul 2024 – Oct 2024
Development of a Performance Test Suite for LLVM MLIR Compiler on RISC-V Vector Platform for LLM
 
 
 
 
 

Semester Project

IIS ETH

Feb 2024 – Jul 2024
Transformer Hareware Software Codesign for NeuroSoc
 
 
 
 
 

Research Intern

EAST-MICAS, KUL

Jun 2023 – Sep 2022
Design and Implementation of an Electronic Skin for Prosthetics Applications
 
 
 
 
 

Ospp@Alibaba RocketMQ Project Intern

Alibaba

Jun 2022 – Sep 2022
Apache RocketMQ Documentation Manager & Website Development
 
 
 
 
 

Undergraduate Researcher

Fudan University, Prof. Zhongzhi Zhang

Nov 2020 – May 2021
 
 
 
 
 

Undergraduate Researcher

Fudan University, Prof. Wei Chen and Prof. Hui Feng

Aug 2019 – Feb 2020
Work on pain classification problem with deep learning method