Chundi Liu

I am a machine learning scientist at Layer6 AI, where I work on computer vision, biomedical image analysis and machine learning applications in capital market.

I obtained my master's degree from University of Toronto in 2018 and honors bachelor's degree from China Agricultural University in 2015.

We are hiring Machine Learning Scientists and Data Engineers. Feel free to reach out to me or directly apply from here.

Email  /  Google Scholar  /  Kaggle  /  Github  /  LinkedIn

I have always been passionate about machine learning competitions. Currently, I am a Kaggle master with best rank 70/125,000. Here are some highlights:

My research interests broadly lie in machine learning, computer vision and natural language processing, with a recent focus on image retrieval, graph modelling and unsupervised learning. I'm also into machine learning applications in biomedical area.

Guided Similarity Separation for Image Retrieval
Chundi Liu, Guangwei Yu, Cheng Chang, Himanshu Rai, Junwei Ma,
Satya Krishna Gorti, Maksims Volkovs
Neural Information Processing Systems (NeurIPS), 2019 (Oral 2.5%)
[code][poster][slides][video]

A new unsupervised model for image retrieval based on graph neural network neighbor encoding and a novel guided similarity separation loss. Results on public benchmarks show highly competitive performance with up to 25% relative improvement.

Explore-Exploit Graph Traversal for Image Retrieval
Cheng Chang*, Guangwei Yu*, Chundi Liu, Maksims Volkovs
Computer Vision and Pattern Recognition (CVPR), 2019
[code][poster]

A new approach for image retrieval based on graph traversal by alternating between explore and exploit steps to capture the data manifold.

Unsupervised Document Embedding With CNNs
Chundi Liu*, Shunan Zhao*, Maksims Volkovs
arXiv, 2017
[code]

A CNN model for learning document embedding in an unsupervised fashion.