(at Lake Louise, Alberta, Canada)

Hanshi Sun   孙寒石

I am an incoming Master in Electrical and Computer Engineering at Carnegie Mellon University. I obtained my bachelor degree at Southeast University. I was a member of the PAttern Learning and Mining (PALM) Lab , where I am fortunate to be advised by Prof. Yi Zhou. I was a research intern at the University of Alberta before, supervised by Prof. Xingyu Li. I am an intern at  Apple now.

Research Interest: Machine Learning
hanshis [at] andrew [dot] cmu [dot] edu
hanshi.sun [at] outlook [dot] com

GitHub (preminstrel)
Curriculum Vitae



Carnegie Mellon University, Pittsburgh, United States (Aug 2023 - Dec 2024)

M.S. in Electrical & Computer Engineering

Southeast University, Nanjing, China (Sep 2019 - Jul 2023)

B.E. in Electronic Science and Technology
  • Overall GPA: 3.98/4.0, 94.04/100
  • 2021 & 2022 China National Scholarship

Research Experience

University of Alberta, Edmonton, Canada (Jul 2022 - Oct 2022)

Mitacs Globalink Research Internship

Southeast University, Nanjing, China (Oct 2020 - Jul 2022)

Research Assitant in PALM Lab and National Engineering Research Center For ASIC
  • Supervisor: Prof. Yi Zhou, Prof. Hao Liu
  • Project 1: Energy-efficient DNN Algorithm for ECG Classification
  • Project 2: Multi-Modal Multi-task Transformer on Disease Detection
  • Project 2: Multi-task Learning For Multi-disease Classification

Professional Experience

Apple Inc., Shenzhen, China (Nov 2022 - Jun 2023)

R&D Intern in iPad System EE
  • Built a python automation test frame that can run on multiple units, collect and analyze logs
  • Issue reproduction, symptom capture, and hands-on debugging for coexistence testing
  • Created web pages with diverse visualization of the analyzed data using Flask


BMAD: Benchmarks for Medical Anomaly Detection

Jinan Bao, Hanshi Sun, Hanqiu Deng, Yinsheng He, Zhaoxiang Zhang, and Xingyu Li
arXiv:2306.11876, 2023

[paper] [code]

Combating Medical Noisy Labels by Disentangled Distribution Learning and Consistency Regularization

Yi Zhou, Lei Huang, Tao Zhou and Hanshi Sun
Future Generation Computer Systems, (FGCS), 2022.


Arrhythmia Classifier Using Convolutional Neural Network with Adaptive Loss-aware Multi-bit Networks Quantization

Hanshi Sun, Ao Wang, Ninghao Pu, Zhiqing Li, Junguang Huang, Hao Liu and Zhi Qi
International Conference on Artificial Intelligence and Computer Engineering, (ICAICE), 2021.

[project page] [paper] [code]



Friends (click to expand, random order)

© Hanshi Sun 2023