My primary research interest is building efficient systems for machine learning. I have recently started my role as an Applied Scientist at Amazon Web Services.

You may access my CV here.

Contact me at chohyu01 (at) cs.washington.edu.

Open-source Involvement

• Contributor and Maintainer of XGBoost
  XGBoost is an efficient, scalable framework for gradient boosting. We are always looking to recruit new contributors.
• Owner and Maintainer of Treelite
  Treelite is a model compiler for easy and efficient deployment of decision tree ensembles.
• My GitHub account

Experience

• Applied Scientist
  Amazon Web Services. January 2018—Present.
• Applied Scientist Intern
  Amazon Web Services. June—December 2017.
• M.S. in Computer Science
  Paul G. Allen School of Computer Science and Engineering, University of Washington. September 2015—March 2018.
• B.S. in Computer Science and Mathematics
  Trinity College. 2012—2015.

Peer-reviewed publications

• Treelite: toolbox for decision tree deployment
  with Mu Li
  Poster presented at SysML 2018 (2018)
• An accelerated procedure for hypergraph coarsening on the GPU
  with Lin Cheng and Peter Yoon
  Paper presented at IEEE HPEC (2015)
• A memory-efficient algorithm for large-scale symmetric tridiagonal eigenvalue problem on multi-GPU systems
  with Peter Yoon
  Paper presented at WorldComp 2014: PDPTA (2014)
  Poster presented at GPU Technology Conference (2014)
• GPU accelerated vessel segmentation using Laplacian eigenmaps
  with Lin Cheng, Peter Yoon and Jiajia Zhao
  Paper presented at IASTED PDCN (2014)
  Poster presented at GPU Technology Conference (2013)
• An efficient out-of-core implementation of block Cholesky decomposition on a multi-GPU system
  with Lin Cheng, Peter Yoon and Jiajia Zhao
  Paper presented at IASTED PDCS (2012), best paper award
  Poster presented at IEEE EMBS (2012)

Awards and Honors

• Winner of Outstanding Undergraduate Researcher Award, Computing Research Association, 2015.
• Recipient of the Goldwater Scholarship, The United States Congress, 2014.
• Best Paper Award, The 24th IASTED International Conference on Parallel and Distributed Computing and System, Las Vegas, NV, November 13, 2012.