(at Lake Louise, Alberta, Canada)

Hanshi Sun   孙寒石

I am a Master student in Electrical and Computer Engineering at Carnegie Mellon University. Now I am working on LLM inference efficiency with Prof. Beidi Chen. 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. Before, I was a research intern at the University of Alberta, supervised by Prof. Xingyu Li; I was an intern at  Apple.

hanshis [at] andrew [dot] cmu [dot] edu

@preminstrel
GitHub (preminstrel)
LinkedIn
Blog

News

Publications

I'm interested in LLM efficiency, MLSys, generative AI. Selected papers are highlighted.
   
TriForce
*TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

Hanshi Sun, Zhuoming Chen, Xinyu Yang, Yuandong Tian, and Beidi Chen

arXiv, 2024

project page / paper / code / video


Training-free Lossless Long Sequence Generation Acceleration
   
BMAD: Benchmarks for Medical Anomaly Detection

Jinan Bao, Hanshi Sun, Hanqiu Deng, Zhaoxiang Zhang, and Xingyu Li

CVPR Workshop, 2024

paper / code


This benchmark encompasses six reorganized datasets from five medical domains (i.e. brain MRI, liver CT, retinal OCT, chest X-ray, and digital histopathology) and three key evaluation metrics, and includes a total of fourteen state-of-the-art AD algorithms.
   
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

paper


Disentangled distribution learning reduces effect of label uncertainty and ambiguity
   
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
ICAICE, 2021

project page / paper / code


Present a 1-D adaptive loss-aware quantization, achieving a high compression rate that reduces memory consumption by 23.36x

Education

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

M.S. in Electrical & Computer Engineering
  • Overall GPA: 4.0/4.0

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

B.E. in Electronic Science and Technology
  • Overall GPA: 3.96/4.0, 93.69/100
  • 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

Miscellaneous

Videos:

Friends (click to expand, random order)

© Hanshi Sun 2024