- PhD, Computer Science and Applications, Virginia Polytechnic Institute and State University
- MS, Computer Science, University of Windsor
- MS, Applied Mathematics, Michigan Technological University
- Scientific computing
- 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
- 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 451 Topics in Computer Science (World Wide Web Programming) (Issues in Scientific Computing)
- CS 435 Computational Science and Applications
- CS 495W, CS 496W Senior Seminar (1)(2)
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All course descriptions are listed in the CLA Course Catalog.
- Sandu, A. and Cheng, H. An error subspace perspective on data assimilation. Accepted for publication. International Journal for Uncertainty Quantification, 2014.
- Cheng, H. and Sandu, A. Collocation least-squares polynomial chaos method (PDF). In Proceedings of the 2010 Spring Simulation Multiconference, pages 94-99, April, 2010.
- Cheng, H., Jardak, M., Alexe, M., and Sandu, A. A hybrid approach to estimating error covariances in variational data assimilation. Tellus Series A: Dynamic Meteorology and Oceanography, 62(3):288-297, May 2010.
- Cheng, H. and Sandu, A. Uncertainty quantification and apportionment in air quality models using the polynomial chaos method. Environmental Modelling & Software: 24(8):917-925, August 2009.
- Cheng, H. and Sandu, A. Efficient uncertainty quantification with the polynomial chaos method for stiff systems, Mathematics and Computers in Simulation, 79(11):3278-3295, July 2009.
- Cheng, H and Sandu, A. Uncertainty apportionment for air quality forecast models (PDF). In proceeding of the 24th Annual ACM Symposium on Applied Computing (ACM-SAC), pages 956-960, March, 2009.
- Cheng, H. and Sandu, A. Numerical study of uncertainty quantification techniques for implicit stiff systems. In Proceeding of the 45th Annual ACM Southeast Regional (ACMSE) Conference, pages 367-372, 2007.
- Cheng, H and Bertram, B. On the stopping criteria for conjugate gradient solutions of first-kind integral equations in two variables. Integral Methods in Science and Engineering, Springer, 2002.
- Bertram, B and Cheng, H. On the use of the conjugate gradient method for the numerical solution of first-kind integral equations in two variables. Integral Methods in Science and Engineering, Springer, 2002.
Invited Talks and Tutorials
- "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.
- "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
- Willamette Atkinson Grant, 2014.
- NSF Grant: NSF DMS-1217073 "Uncertainty reduction through better nonlinear particle filters," 2012-2015.
- SIAM Travel Award, SIAM-UQ, 2012.
- Willamette Atkinson Grant, 2011.
- Willamette Science Collaboration Research Program (SCRP), 2010, 2011, 2013, 2014.
- Willamette CS/Math Lilly Project.