Feiyang Huang

Machine Learning @ Weill Cornell Medicine



About


I build software and algorithms with an impact on human health. I have done work in 1) spatial transcriptomics analysis (e.g.  STdeconvolve) and 2) machine learning applied to electronic health records (EHR) time series and medical images.

I am fortunate to have been advised by Jean Fan, Nicholas Durr, and Jeff Wang, and I have the pleasure of collaborating with Dr. Jim Fackler and Dr. Sapna Kudchadkar

Other things I have enjoyed doing include:
  • building productivity dashboards as a software engineer intern at Hologic
  • working on every aspect of a low-cost rapid PCR machine (now Prompt Diagnostics)
  • co-founding a student venture working on molecular diagnostics in internal hemorrhage 

Publications




Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data


Brendan F Miller, Feiyang Huang, Lyla Atta, Arpan Sahoo, Jean Fan

Nature communications, vol. 13, Nature Publishing Group, 2022, pp. 1--13




Artificial intelligence- enhanced white-light colonoscopy with attention guidance predicts colorectal cancer invasion depth


Xiaobei Luo, Jiahao Wang, Zelong Han, Yang Yu, Zhenyu Chen, Feiyang Huang, Yumeng Xu, Jianqun Cai, Qiang Zhang, Weiguang Qiao, others

Gastrointestinal Endoscopy, vol. 94, Mosby, 2021, pp. 627--638




Roles and regulation of long noncoding RNAs in hepatocellular carcinoma


Lee Jin Lim, Samuel YS Wong, Feiyang Huang, Sheng Lim, Samuel S Chong, London Lucien Ooi, Oi Lian Kon, Caroline G Lee

Cancer research, vol. 79, AACR, 2019, pp. 5131--5139

Projects




Genome Set-Sketch


Fast reference-free genome comparison using Set-Sketch, written in C++ and MATLAB

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