(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 also worked with Prof. Hao Liu before.

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

@preminstrel
GitHub (preminstrel)
Google Scholar
LinkedIn
Blog

News

[2024/07/09] Our TriForce has been accepted by COLM 2024 🦙! See you in Philadelphia!

[2024/06/03] Work as a MLSys Research Intern in Seed-Foundation team at ByteDance (Seattle Office) .

[2023/11/06] Join Prof. Beidi Chen's group at CMU .

[2023/06/20] Graduate from Southeast University with a bachelor degree .

[2022/11/15] I am working at Apple as an intern in EE/SW team for eight months.

[2022/07/06] I am working as a research intern during summer 2022 in Prof. Xingyu Li’s group at the University of Alberta .

Publications

/ . Selected papers are highlighted.

*TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

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

Conference on Language Modeling (COLM), 2024

arXiv / website / code / demo / bibtex

Training-free Lossless Long Sequence Generation Acceleration

BMAD: Benchmarks for Medical Anomaly Detection

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

Computer Vision and Pattern Recognition (CVPR) Workshop, 2024

arXiv / code / bibtex

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.

*TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

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

Conference on Language Modeling (COLM), 2024

arXiv / website / code / demo / bibtex

Training-free Lossless Long Sequence Generation Acceleration

BMAD: Benchmarks for Medical Anomaly Detection

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

Computer Vision and Pattern Recognition (CVPR) Workshop, 2024

arXiv / code / bibtex

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), 2023

paper / bibtex

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

website / paper / code / bibtex

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
Teaching Assistant @ Introduction to Deep Learning, Introduction to Machine Learning

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

Professional Experience

ByteDance Inc., Seattle, United States (Jun 2024 - Present)

Machine Learning System Research Intern in Seed-Foundation Team

Placeholder

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