Undergraduate Student, School of Mathematics and System Science, Beihang University
Merit Student of 2014
I am computational mathematician working on uncertainty quantification. We combines mathematical theory and state-of-the-art computational tools to solve scientific and engineering problems with domain scientists.
Email: wang.peng AT buaa DOT edu DOT cn
2011 🇺🇸 Ph.D in Computational Science - University of California, San Diego
2010 🇺🇸 M.Sc in Engineering Science - University of California, San Diego
2007 🇬🇧 M.Eng 1st honor in Mechanical Engineering - University of Durham
2014–Now Professor of Mathematics, Beihang University
2011–2013 Post Doctorate Research Associate, Pacific Northwest National Laboratory
2013 Staff Scientist, Pacific Northwest National Laboratory
2013 Teaching Fellow, Oundle School
2015–now Editorial Board — International Journal for Uncertainty Quantification
2016–now Board Member - 4th Reformation Committee for Scientific Policy of China
Our goal is to develop mathematical tools to quantify uncertainty in nature, engineering systems and our society, and thus provide more accurate and comprehensive predictions of these system states. Applications of our work include environmental protection (flood prediction), ecology (algae blooms), oil recovery and renewable energy systems.
Quantification of predictive uncertainty in models of FtsZ ring assembly in Escherichia coli pdf
Y. Ye, A. Ruiz-Martinez, P. Wang* and D. M. Tartakovsky* (2019)
Journal of Theoretical Biology, vol. 484, pp. 110006
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Data assimilation for models with parametric uncertainty pdf
L. Yang, Y. Qin, A. Narayan and P. Wang* (2019)
Journal of Computational Physics, 2019, vol. 396, pp. 785-798.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis pdf
X. Sun, J. Bright*, C. A. Gueymard, B. Acord, P. Wang* and N. Engerer (2019)
Renewable and Sustainable Energy Reviews, 2019, vol. 111, pp. 550-570.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
A new method for an old topic: Efficient and reliable estimation of material bulk modulus pdf
P. Wang*, Y. Qin, M. Cheng, G. Wang, D. Xiu and Z. Sun* (2019)
Computational Materials Science, 2019, vol. 165, pp. 7-12.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
An Efficient Solver for Cumulative Density Function-based Solutions of Uncertain Kinematic Wave Models pdf
M. Cheng#, A. Narayan#, Y. Qin#, P. Wang#*, X. Zhong# and X. Zhu# (2019)
Journal of Computational Physics, 2019, vol. 382, pp.138-151
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Uncertainty quantification on macroscopic properties of random porous media pdf
P. Wang, H. Chen, X. Meng, X. Jiang, D. Xiu and X. Yang* (2018)
Physical Review E, 2018, vol. 98, no. 3, pp. 033306.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
X. Shi, B. Acord, P. Wang* pdf
Incorporating ground measured pollution observations to improve temporally downscaled solar irradiance simulations (2018)
Solar Energy, 2018, vol. 171, 293-301.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Sequential data assimilation with multiple nonlinear models and applications to subsurface flow pdf
L. Yang, A. Narayan and P. Wang* (2017)
Journal of Computational Physics, 2017, vol. 346, pp. 356-368.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Software reliability growth model with temporal correlation in a network environment pdf
J. Xu, S. Yao, S. Yang and P. Wang* (2016)
International Journal for Uncertainty Quantification, 2016, vol. 6, no. 2, pp.141-156.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Uncertainty quantification of scientific proposal evaluations pdf
X. Shi, P. Wang and D. Xiu (2016)
International Journal for Uncertainty Quantification, 2016, vol. 6, no. 2, pp.167-173.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Probabilistic density function method for stochastic ODEs of power systems with uncertain power input pdf
P. Wang, D. A. Barajas-Solano, E. Constantinescu, S. Abhyankar, D. Ghosh, B. F. Smith, Z. Huang and A. M. Tartakovsky* (2015)
SIAM/ASA Journal on Uncertainty Quantification, 2015, vol. 3, no. 1, pp. 873-896.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
PDF method for dynamic system with colored noise pdf
P. Wang*, A. M. Tartakovsky and D. M. Tartakovsky (2013)
Physical Review Letters, 2013, vol. 110, no. 14, pp. 140602.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
CDF solutions of Buckley-Leverett equation with uncertain parameters pdf
P. Wang, D. M. Tartakovsky, K. Jarman Jr. and A. M. Tartakovsky* (2013)
SIAM Journal of multiscale modeling and simulation, 2013, vol. 11, no. 1, pp. 118-133.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Uncertainty quantification in kinematic-wave models pdf
P. Wang and D. M. Tartakovsky* (2012)
Journal of Computational Physics, 2012, vol. 231, no. 23, pp. 7868-7880.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Reduced complexity models for probabilistic forecasting of infiltration rate pdf
P. Wang and D. M. Tartakovsky* (2011)
Advances in Water Resources, 2011, vol. 34, pp. 375-382.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Probabilistic predictions of infiltration into heterogeneous media with uncertain hydraulic parameters pdf
P. Wang and D. M. Tartakovsky* (2011)
Internal Journal for Uncertainty Quantification, 2011, vol. 1, no. 1, pp. 35-47.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface
Effects of spatio-temporal variability of precipitation on contaminant migration in the vadose zone pdf
P. Wang, P. Quinlan and D. M. Tartakovsky* (2009)
Geophysical Research Letters, 2009, vol. 36, L12404.
Keyword: uncertainty quantification, model uncertainty, Kalman filter, particle filter, subsurface