Haiyan Cheng

Associate Professor and Department Chair
Specialty: Computer Science

Education

  • PhD, Computer Science and Applications, Virginia Tech, 2009
  • MS, Computer Science, University of Windsor, 2003
  • MS, Applied Mathematics, Michigan Technological University, 2000

Research Interests

  • Scientific computing
  • Data Science and machine learning
  • Computational sustainability 
  • Data assimilation techniques: Kalman filter, 4D-Var, Particle filter
  • Hybrid numerical methods for data assimilation
  • Uncertainty quantification and reduction techniques for large-scale simulations
  • Polynomial chaos method
  • Uncertainty apportionment

Courses

  • IDS 101 Ethics in Information Technology
  • CS 125 Problem Solving with MATLAB
  • CS 141 Introduction to Programming (JAVA)
  • CS 203X Problem Solving for the ACM Programming Contest
  • CS 343 Analysis of Algorithms
  • CS 393 Computer Science Junior Seminar
  • CS 470 Introduction to Data Science
  • CS 451 Topics in Computer Science (World Wide Web Programming) (Issues in Scientific Computing)
  • CS 435 Computational Science and Applications
  • CS 495W, CS 496W Computer Science Senior Seminar (1)(2)
  • GSMDS 5002 Practical Applications of Python for Data Science

I'm using the Willamette WISE system for course management and course material, if you are interested in the course content, please contact me to obtain a guest permission.

All course descriptions are listed in the CLA Course Catalog.

We are offering a new Data Science program, for more information, please click here.

Publications

Invited Talks and Tutorials

  • "The best of both worlds: Computational Science and Data Science." Mathematics and Computer Science Colloquium talk, Lewis and Clark College, Oct 24, 2019.
  • "Adaptive Data Assimilation Scheme for Shallow Water Simulation." Data Assimilation Techniques for High-dimensional and Nonlinear Problems Minisymposia, SIAM Conference on Uncertainty Quantification (SIAM-UQ), Lausanne, Switzerland, April 5-8, 2016.
  • "Uncertainty Quantification with Polynomial Chaos Method for Practitioners." Institute of Applied Physics and Computational Mathematics, Beijing, China, Aug 11, 2015.
  • "Today's Forecast-A Better Forecast." Institute for Continued Learning at the Willamette University, Salem, Oregon, Oct 28, 2014.
  • "Data Assimilation with Particle Filter Methods." Applied and Computational Mathematics Seminar, Portland State University, Portland, Oregon, May 12, 2014.
  • "Quantify and Reduce Uncertainties to Improve the Model Predictability." CASCADE Computational and Applied Mathematics Seminar, Oregon State University, Corvallis, Oregon, April 5, 2014.
  • "Hybrid Data Assimilation Method", Colloquium Talk, Department of Mathematics, Statistics and Computer Science, Marquette University, April 26, 2013.
  • "Variational Data Assimilation and Particle Filters." Data Assimilation and PDE-Constrained Optimization, SIAM Conference on Computational Science and Engineering (SIAM-CSE) Feb 25-Mar 1, 2013.
  • "Hybrid Methods for Data Assimilation." Data Assimilation and Inverse Problem Minisymposia, SIAM Conference on Uncertainty Quantification (SIAM-UQ), Raleigh, North Carolina, April 2-5, 2012.
  • "New Hybrid EnKF and 4D-Var Method." Applied Mathematics and Computational Seminar, Mathematics Department, Oregon State University, Corvallis, Oregon, November 18, 2011.
  • "Investigation of Advanced Data Assimilation Schemes for Nonlinear and Non-Gaussian Problems." Invited talk at National Oceanic and Atmospheric Administration, Earth Science Research Lab, Global System Division, Forecast Application Branch (NOAA/ESRL/GSD/FAB), Boulder, Colorado, July 27, 2011.
  • "Uncertainty Quantification and Uncertainty Reduction Techniques in Scientific Simulations." Invited talk at NOAA/ESRL/GSD/FAB, Boulder, Colorado, June 23, 2010.
  • "Uncertainty Quantification and Uncertainty Reduction Techniques for Scientific Simulations." Half-day tutorial at ACM-SAC conference, Sierre, Switzerland, March 22-26, 2010.
  • "Parameter Estimation and Uncertainty Apportionment using a Polynomial Chaos Approach." Invited talk at SIAM Conference on Computational Science and Engineering (SIAM-CSE-09), Miami, Florida, March 2-6, 2009.

Fundings and Awards