Uncertainty quantification & data assimilation

Uncertainty quantification (UQ) focuses on characterizing uncertainty in outputs from computational simulations given uncertainty in parameters, data, and model structure.

Data assimilation (DA) combines measurements and model predictions to obtain accurate estimates of the system state and uncertain parameters; it is central to weather and climate analysis and forecasting.

Featured project

Selected journal publications

• Shinhoo Kang and Emil M Constantinescu. Differentiable DG with neural operator source term correction. Submitted, 2025. [arXiv]
• Pi-Yueh Chuang, Ahmed Attia, and Emil M Constantinescu. Distributional sensitivity analysis: Enabling differentiability in sample-based inference. Submitted, 2025. [arXiv]
• Haoyuan Chen, Emil M Constantinescu, Vishwas Rao, and Cristiana Stan. Improving the predictability of the Madden-Julian oscillation at subseasonal scales with Gaussian process models. JAMES - Machine learning application to Earth system modeling, Vol. 17(5); Pages e2023MS004188, 2025. [DOI] [arXiv]
• Arkaprabha Ganguli, Nesar Ramachandra, Julie Bessac, and Emil M Constantinescu. Enhancing interpretability in generative modeling: Statistically disentangled latent spaces guided by generative factors in scientific datasets. Springer Machine Learning, Vol. 114(9); Pages 197, 2025. [DOI] [arXiv]
• Arkaprabha Ganguli, Anirban Samaddar, Florian Kéruzoré, Nesar Ramachandra, Julie Bessac, Sandeep Madireddy, and Emil M Constantinescu. Uncovering physical drivers of dark matter halo structures with auxiliary-variable-guided generative models. Submitted, 2025. [arXiv]
• Shinhoo Kang, Alp Dener, Aidan Hamilton, Hong Zhang, Emil M Constantinescu, and Robert Jacob. Multirate partitioned Runge-Kutta methods for coupled Navier-Stokes equations. Computers & Fluids, Vol. 264(15); Pages 105964, 2023. [DOI] [arXiv] [PDF]
• Shinhoo Kang and Emil M Constantinescu. Learning subgrid-scale models with neural ordinary differential equations. Computers and Fluids, In Press, Vol. 261; Pages 105919, 2023. [DOI] [arXiv]
• Ahmed Attia, D. Adrian Maldonado, Emil M Constantinescu, and Mihai Anitescu. Centralized calibration of power system dynamic models using variational data assimilation. 2023. [arXiv] [PDF]
• Hong Zhang, Emil M Constantinescu, and Barry F. Smith. PETSc TSAdjoint: A discrete adjoint ODE solver for first-order and second-order sensitivity analysis. SIAM Journal of Scientific Computing, Vol. 44; Pages C1-C24, 2022. [DOI] [arXiv] [PDF]
• Ahmed Attia and Emil M Constantinescu. Optimal experimental design for inverse problems in the presence of observation correlations. SIAM Journal on Scientific Computing (SISC), Vol. 44(4); Pages A2808-A2842, 2022. [DOI] [arXiv] [PDF]
• Romit Maulik Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil M Constantinescu, Bethany Lusch, Prasanna Balaprakash, Ian Foster, Rao Kotamarthi. AIEADA 1.0: Efficient high-dimensional variational data assimilation with machine-learned reduced-order models,. GMDD, 2022. [DOI] [arXiv] [PDF]
• Luisa D'amore, Emil M Constantinescu, and Luisa Carracciuolo. A scalable space-time domain decomposition approach for solving large scale non linear regularized inverse ill posed problems in 4D variational data assimilation,. Springer Journal of Scientific Computing, 2022. [DOI]
• Shaohui Liu, Adrian Maldonado, and Emil M Constantinescu. Probabilistic analysis of masked loads with aggregated photovoltaic production. Electric Power Systems Research, Vol. 189; Pages 106670, 2020. [DOI] [arXiv]
• Oana Marin, Emil M Constantinescu, and Barry Smith. A scalable matrix-free spectral element approach for unsteady PDE constrained optimization using PETSc/TAO. Vol. 47; Pages 101207, 2020. [DOI] [arXiv]
• Emil M Constantinescu, Noemi Petra, Julie Bessac, and Cosmin G. Petra. Statistical treatment of inverse problems constrained by differential equations-based models with stochastic terms. SIAM Journal on Uncertainty Quantification, Vol. 8(1); Pages 170-197, 2020. [DOI] [arXiv]
• Joseph Hart, Julie Bessac, and Emil M Constantinescu. Global sensitivity analysis for statistical model parameters. SIAM/ASA Journal on Uncertainty Quantification, Vol. 7(1); Pages 67–92, 2019. [DOI] [arXiv] [PDF]
• Hanqi Guo, Wenbin He, Sangmin Seo, Han-Wei Shen, Emil M Constantinescu, Chunhui Liu, and Tom Peterka. Extreme-scale stochastic particle tracing for uncertain unsteady flow visualization and analysis. IEEE Transactions on Visualization and Computer Graphics, Vol. 25(9); Pages 2710-2724, 2019. [DOI]
• Julie Bessac, Emil M Constantinescu, and Mihai Anitescu. Stochastic simulation of predictive space-time scenarios of wind speed using observations and physical models. Annals of Applied Statistics, Vol. 12(1); Pages 432-458, 2018. [DOI] [arXiv]
• Jiali Wang, Julie Bessac, Rao Kotamarthi, Emil M Constantinescu, and Beth Drewniak. Internal variability, regional climate model, spectral nudging, high spatial resolution, climate change. Climate Dynamics, Vol. 50; Pages 4539-4559, 2018. [DOI]
• Noemi Petra, Cosmin G. Petra, Zheng Zhang, Emil M Constantinescu, and Mihai Anitescu. A Bayesian approach for parameter estimation with uncertainty for dynamic power systems. IEEE Transactions on Power Systems, Vol. 32(4); Pages 2735-2743, 2017. [DOI] [arXiv]
• Hong Zhang, Shrirang S. Abhyankar, Emil M Constantinescu, and Mihai Anitescu. Discrete adjoint sensitivity analysis of power system dynamics. {"IEEE Transactions on Circuits and Systems--I"=>"Regular Papers"}, Vol. 64(5); Pages 1247-1259, 2017. [DOI]
• Nan Li, Canan Uckun, Emil M Constantinescu, John Birge, Kory W. Hedman, and Audun Botterud. Flexible operation of batteries in power system scheduling with renewable energy. IEEE Transactions on Sustainable Energy, Vol. 7(2); Pages 685-696, 2016. [DOI]
• Peng Wang, David Barajas-Solano, Emil M Constantinescu, Shrirang S. Abhyankar, Debojyoti Ghosh, Barry Smith, Zhenyu Huang, and Alexandre Tartakovsky. Probabilistic density function method for stochastic ODEs of power systems with uncertain power input. SIAM/ASA Journal on Uncertainty Quantification (JUQ), Vol. 3(1); Pages 873-896, 2015. [DOI]
• Ilias Bilionis, Beth A. Drewniak, and Emil M Constantinescu. Crop physiology calibration in the CLM. Geoscientific Model Development, Vol. 8(4); Pages 1071-1083, 2015. [DOI] [PDF]
• Ilias Bilionis, Emil M Constantinescu, and Mihai Anitescu. Data-driven model for solar irradiation based on satellite observations. Solar Energy, Vol. 110; Pages 22-38, 2014. [DOI]
• Mihai Anitescu, Xiaoyan Zeng, and Emil M Constantinescu. A low-memory approach for best-state estimation of hidden Markov models with model error. SIAM Journal on Numerical Analysis (SINUM), Vol. 52(1); Pages 468-495, 2014. [DOI]
• Xiaoyan Zeng, Beth A. Drewniak, and Emil M Constantinescu. Calibration of the crop model in the Community Land Model. Geoscientific Model Development, Vol. 6(1); Pages 379-398, 2013. [DOI]
• Juan M. Salazar, Urmila Diwekar, Emil M Constantinescu, and Victor Zavala. Stochastic optimization approach to water management in cooling-constrained power plants. Applied Energy, Vol. 112; Pages 12-22, 2013. [DOI]
• Emil M Constantinescu and Mihai Anitescu. Physics-based covariance models for Gaussian processes with multiple outputs. International Journal for Uncertainty Quantification, Vol. 3(1); Pages 47-71, 2013. [DOI]
• Ricardo J. Bessa, Vladimiro Miranda, Audun Botterud, Jianhui Wang, and Emil M Constantinescu. Time adaptive conditional kernel density estimation for wind power forecasting. IEEE Transactions on Sustainable Energy (Special Wind Energy issue), Vol. 3(4); Pages 660-669, 2012. [DOI]
• Emil M Constantinescu,Victor Zavala, Matthew Rocklin, Sangmin Lee, and Mihai Anitescu. A computational framework for uncertainty quantification and stochastic optimization in unit commitment with wind power generation. IEEE Transactions on Power Systems, Vol. 26(1); Pages 431-441, 2011. [DOI]
• Adrian Sandu, Emil M Constantinescu, Gregory R. Carmichael, Tianfeng Chai, Dacian Daescu and John Seinfeld. Ensemble methods for dynamic data assimilation of chemical observations in atmospheric models. Journal of Algorithms & Computational Technology, Vol. 5(4); Pages 667-692, 2011.
• Victor Zavala, Emil M Constantinescu, Theodore Krause, and Mihai Anitescu. On-line economic optimization of energy systems using weather forecast information. Journal of Process Control, Vol. 19(10); Pages 1725-1736, 2009. [DOI]
• Lin Zhang, Emil M Constantinescu, Adrian Sandu, Youhua Tang, Tianfeng Chai, Gregory R. Carmichael, Daewon Byun, and Eduardo Olaguer. An adjoint sensitivity analysis and 4D-Var data assimilation study of Texas air quality,. Atmospheric Environment (special ACM issue), Vol. 42(23); Pages 5787 - 5804, 2008. [DOI]
• Gregory R. Carmichael, Adrian Sandu, Tianfeng Chai, Dacian N. Daescu, Emil M Constantinescu, and Youhua Tang. Predicting air quality: Improvements through advanced methods to integrate models and measurements. Journal of Computational Physics Review, Vol. 227(7); Pages 3540-3571, 2007. [DOI]
• Emil M Constantinescu, Tianfeng Chai, Adrian Sandu, and Gregory R. Carmichael. Autoregressive models of background errors for chemical data assimilation. Journal of Geophysical Research, Vol. 112; Pages D12309, 2007. [DOI]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Ensemble-based chemical data assimilation II: Covariance localization. Quarterly Journal of the Royal Meteorological Society, Vol. 133(626); Pages 1245-1256, 2007. [DOI]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Ensemble-based chemical data assimilation I: General approach. Quarterly Journal of the Royal Meteorological Society, Vol. 133(626); Pages 1229-1243, 2007. [DOI]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Assessment of ensemble-based chemical data assimilation in an idealized setting. Atmospheric Environment, Vol. 41(1); Pages 18-36, 2007. [DOI]

Proceedings / presentations

• Piyush Garg, Emil M Constantinescu, Bethany Lusch, Troy Arcomano, Jiali Wang, and Rao Kotamarthi. Physics-informed domain-aware atmospheric radiative transfer emulator for all sky conditions. 2023 Tackling Climate Change with Machine Learning Workshop, part of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
• Haoyuan Chen, Emil M Constantinescu, Vishwas Rao, and Cristiana Stan. Uncertainty quantification of the Madden-Julian oscillation with Gaussian processes. 2023 Tackling Climate Change with Machine Learning Workshop, part of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
• Sungho Shin, François Pacaud, Emil M Constantinescu, and Mihai Anitescu. Constrained policy optimization for stochastic optimal control under nonstationary uncertainties. Advances in Automotive Control, Pages 634-639, 2022. [DOI] [arXiv]
• Vishwas Hebbur Venkata Subba Rao, Romit Maulik, Emil M Constantinescu, and Mihai Anitescu. A machine learning method for computing rare event probabilities. ICCS 2020 (International Conference on Computational Science 2020), Vol. LNCS 12142; Pages 169–182, 2020. [DOI] [arXiv]
• Ricardo J. Bessa, J. Sumaili, Vladimiro Miranda, Audun Botterud, Jianhui Wang, and Emil M Constantinescu. Time-adaptive kernel density forecast: A new method for wind power uncertainty modeling. 17th Power Systems Computation Conference (PSCC'11), Stockholm, Sweden, August 22-26, 2011, 2011.
• Alexandru Cioaca, Victor Zavala, and Emil M Constantinescu. Adjoint sensitivity analysis for numerical weather prediction: Applications to power grid optimization. Proceedings of the first international workshop on high performance computingnetworking and analytics for the power gridSeattleWANovember 13, 2011.
• Victor Zavala, Emil M Constantinescu, and Mihai Anitescu. Economic impacts of advanced weather forecasting in energy system operations. IEEE PES Conference on Innovative Smart Grid Technologies, 2010.
• Victor M. Zavala, Jianhui Wang, Sven Leyffer, Emil M Constantinescu, Mihai Anitescu, and Guenter Conzelmann. Proactive energy management for next-generation building systems. SimBuild 2010, 2010.
• Victor M. Zavala, Audun Botterud, Emil M Constantinescu, and Jianhui Wang. Computational and economic limitations of dispatch operations in the next-generation power grid. IEEE Conference on Innovative Technologies for an Efficient and Reliable Energy Supply, 2010.
• Juan M. Salazar, Urmila Diwekar, Emil M Constantinescu, and Victor M. Zavala. Real-time water management in power plants and implications in electricity markets. AIChE meetingSalt Lake CityUT, 2010.
• Adrian Sandu, Emil M Constantinescu, Gregory R. Carmichael, Tianfeng Chai, John H. Seinfeld, and Dacian Daescu. Localized ensemble Kalman dynamic data assimilation for atmospheric chemistry. International Conference on Computational Science (ICCS), Pages 1018-1025, 2007.
• Adrian Sandu, Emil M Constantinescu, Wenyuan Liao, Gregory R. Carmichael, Tianfeng Chai, John H. Seinfeld, and Dacian Daescu. Ensemble-based filter data assimilation for atmospheric chemical transport models. International Conference on Computational Science (ICCS), Atlanta, GA, May 22-25, 2005, Springer-Verlag in Lecture Notes in Computer Science, Pages 648-655, 2005.

Technical reports

• Hong Zhang, Shrirang S. Abhyankar, Emil M Constantinescu, and Mihai Anitescu. Efficient adjoint computation of hybrid systems of differential algebraic equations with applications in power systems. 2017. [PDF]
• Franck Cappello, Emil M Constantinescu, Paul Hovland, Tom Peterka, Carolyn Phillips, Marc Snir, Stefan Wild. Improving the trust in results of numerical simulations and scientific data analytics. 2015. [PDF]
• Victor Zavala, Emil M Constantinescu, Theodore Krause, and Mihai Anitescu. Exploiting weather forecast information in the operation of integrated energy systems. 2009.
• Emil M Constantinescu,Victor Zavala, Matthew Rocklin, Sangmin Lee, and Mihai Anitescu. Unit commitment with wind power generation: Integrating wind forecast uncertainty and stochastic programming. 2009.
• Emil M Constantinescu, Tianfeng Chai, Adrian Sandu, and Gregory R. Carmichael. Autoregressive models of background errors for chemical data assimilation. 2006. [PDF]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Ensemble-based chemical data assimilation III: Filter localization. 2006. [PDF]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Ensemble-based chemical data assimilation II: Real observations. 2006. [PDF]
• Emil M Constantinescu, Adrian Sandu, Tianfeng Chai, and Gregory R. Carmichael. Ensemble-based chemical data assimilation I: An idealized setting. 2006. [PDF]