Major Reports

  1. National Academies of Sciences, Engineering, and Medicine. Data-Driven Modeling for Additive Manufacturing of Metals: Proceedings of a Workshop. The National Academies Press, Washington D.C., 2019.
  2. Baker, N., Alexander, F., Bremer, T., Hagberg, A., Kevrekidis, Y., Najm, H., Parashar, M., Patra, A., Sethian, J., Wild, S., and Willcox, K. Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence, February 2019. United States. doi:10.2172/1478744. https://www.osti.gov/servlets/purl/1478744.
  3. National Academies of Sciences, Engineering, and Medicine. 2018. Assessing the Risks of Integrating Unmanned Aircraft Systems (UAS) into the National Airspace System. Washington, DC: The National Academies Press. https://doi.org/10.17226/25143.
  4. Willcox, K., Sarma, S., Lippel, P. Online Education: A Catalyst for Higher Education Reforms. Final report of the MIT Online Education Policy Initiative, April 2016.
  5. Final report of the Institute-wide Task Force on the Future of MIT Education, July 2014.
  6. Alexander, F., Anitescu, M., Bell, J., Brown D., Ferris, M., Luskin, M., Mehrotra, S., Moser R., Pinar, A., Tartakovsky, A., Willcox, K., Wright, S., Zavala, V. A Multifaceted Mathematical Approach for Complex Systems, Report of the DOE Workshop on Mathematics for the Analysis, Simulation, and Optimization of Complex Systems, September 2011.
  7. Broderick, A., Bevilaqua, P., Crouch, J., Gregory, F., Hussain, F., Jeffers, B., Newton, D., Nguyen, D.P., Powell, J., Spain, A., Stone, R., Willcox, K., Wake Turbulence, An Obstacle to Increased Air Traffic Capacity, The National Academies Press, Washington D.C., 2008.
  8. Decadal Survey of Civil Aeronautics: Foundation for the Future, The National Academies Press, Washington D.C., 2006. (Aerodynamics and aeroacoustics subpanel.)

Other Interesting Publications

  1. Marzouk, Y. and Willcox, K., Uncertainty Quantification, in The Princeton Companion to Applied Mathematics, N.J. Higham (ed.), Princeton University Press, 2015.
  2. Miller, H., Willcox, K. and Huang, L., Crosslinks: Improving Course Connectivity Using Online Open Educational Resources, in The Bridge, The National Academy of Sciences, Volume 46, Number 3, pp. 38-44, Fall 2016.
  3. Willcox K. and Huang, L., Mapping Unbundled Open Education Resources: Pathways Through the Chaos, in FutuOER, The Future of Open Educational Resources, published October 2016.

Preprints

  1. Chaudhuri, A., Marques, A., and Willcox, K. , mfEGRA: Multifidelity Efficient Global Reliability Analysis. Oden Institute Report 19-16. Submitted.
  2. Kramer, B., and Willcox, K. , Balanced Truncation Model Reduction for Lifted Nonlinear Systems. arXiv:1907.12084. Submitted.

Journal Publications

  1. Qian, E., Kramer, B., Peherstorfer, B., and Willcox, K. , Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems. Physica D: Nonlinear Phenomena, to appear, 2020.
  2. Swischuk, R., Kramer, B., Huang, C., and Willcox, K., Learning physics-based reduced-order models for a single-injector combustion process. AIAA Journal, to appear, 2020. Also in Proceedings of 2020 AIAA SciTech Forum & Exhibition, Orlando FL, January, 2020. Also Oden Institute Report 19-13.
  3. Chaudhuri, A., Kramer, B., and Willcox, K., Information Reuse for Importance Sampling in Reliability-Based Design Optimization, Reliability Engineering and System Safety, to appear, 2020.
  4. Cook, L., Willcox, K., and Jarrett, J., Design Optimization Using Multiple Dominance Relations, International Journal for Numerical Methods in Engineering, to appear, 2020.
  5. Lam, R., Zahm, O., Marzouk, Y. and Willcox, K., Multifidelity Dimension Reduction via Active Subspaces, SIAM Journal on Scientific Computing, to appear, 2020.
  6. Cook, L., Mishra, A., Jarrett, J. Willcox, K., and Iaccarino, G. Optimization under turbulence model uncertainty for aerospace design, Physics of Fluids, Vol. 31, Issue 10, 105111, 2019. See the paper Scilight here. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Physics of Fluids, Vol. 31 and may be found here.
  7. Feldstein, A., Lazzara, D., Princen, N. and Willcox, K., Multifidelity Data Fusion with Application to Blended-Wing-Body Multidisciplinary Analysis Under Uncertainty, AIAA Journal, to appear, 2019.
  8. Opgenoord, M. and Willcox, K., Design Methodology for Aeroelastic Tailoring of Additively-Manufactured Lattice Structures using Low-Order Methods, AIAA Journal, published online 19 Sep 2019.
  9. Kapteyn, M., Willcox, K. and Philpott, A., Distributionally Robust Optimization for Engineering Design under Uncertainty. International Journal for Numerical Methods in Engineering, Vol. 120, Issue 7, pp. 835-859, July 2019. An earlier version of this work appeared in Proceedings of 2018 AIAA Non-Deterministic Approaches Conference, AIAA SciTech Forum, Kissimmee, FL, January, 2018. (AIAA 2018-0666)
  10. Opgenoord, M. and Willcox, K., Design for Additive Manufacturing: Cellular Structures in Early-Stage Aerospace Design, Structural and Multidisciplinary Optimization, Vol. 60, Issue 2, pp 411-428, 2019.
  11. Kramer, B., Marques, A., Peherstorfer, B., Villa, U. and Willcox, K., Multifidelity probability estimation via fusion of estimators, Journal of Computational Physics, Vol. 392, pp. 385-402, 2019.
  12. Kramer, B. and Willcox, K., Nonlinear model order reduction via lifting transformations and proper orthogonal decomposition, AIAA Journal, Vol. 57 No. 6, pp. 2297-2307, 2019.
  13. Opgenoord, M., Drela, M. and Willcox, K., Influence of transonic flutter on the conceptual design of next-generation transport aircraft, AIAA Journal, Vol. 57, No. 5, pp. 1973-1987, 2019.
  14. Swischuk, R., Mainini, L., Peherstorfer, B. and Willcox, K., Projection-based model reduction: Formulations for physics-based machine learning, Computers and Fluids, Vol. 179, pp. 704-717, January 2019.
  15. Heinkenschloss, M., Kramer, B., Takhtaganov, T. and Willcox, K., Conditional-Value-at-Risk Estimation via Reduced-Order Models, SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, Issue 4, pp. 1395-1423, 2018.
  16. Cook, L., Jarrett, J. and Willcox, K., Generalized information reuse for optimization under uncertainty with non-sample average estimators, International Journal for Numerical Methods in Engineering, Volume 115, Issue 12, pp. 1457-1476, September 2018.
  17. Qian, E., Peherstorfer, B., O'Malley, D., Vesselinov, V. and Willcox, K., Multifidelity Monte Carlo estimation of variance and sensitivity indices, SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, No. 2, pp. 683-706, 2018.
  18. Singh, V. and Willcox, K., Engineering Design with Digital Thread. AIAA Journal, Vol. 56, No. 11, pp. 4515-4528, 2018. Also in proceedings of 2018 AIAA Scitech Forum, Kissimmee, FL, January, 2018.
  19. Baptista, R., Marzouk, Y., Willcox, K. and Peherstorfer, B., Optimal Approximations of Coupling in Multidisciplinary Models. AIAA Journal, Vol. 56, No. 6, pp. 2412-2428, 2018. (An earlier version of this work appeared in AIAA paper 2017-1935, 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (AIAA Scitech), Grapevine, TX, January 2017.)
  20. Peherstorfer, B., Kramer, B. and Willcox, K., Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation. SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, No. 2, pp. 737-761, 2018.
  21. Li, H., Garg, V. and Willcox, K. Model adaptivity for goal-oriented inference using adjoints, Computer Methods in Applied Mechanics and Engineering, Vol. 331, pp. 1-22, April 2018.
  22. Rude, U., Willcox, K., McInnes, L.C., De Sterck, H., Biros, G., Bungartz, H., Corones, J., Cramer, E., Crowley, J., Ghattas, O., Gunzburger, M., Hanke, M., Harrison, R., Heroux, M., Hesthaven, J., Jimack, P., Johnson, C., Jordan, K.E., Keyes, D.E., Krause, R., Kumar, V., Mayer, S., Meza, J., Mørken, K.M., Oden, J.T., Petzold, L., Raghavan, P., Shontz, S.M., Trefethen, A., Turner, P., Voevodin, V., Wohlmuth, B., and Woodward, C.S. Research and Education in Computational Science and Engineering, SIAM Review, Vol. 60, No. 3, pp. 707–754, 2018.
  23. Curran, C., Allaire, D. and Willcox, K., Sensitivity Analysis Methods for Mitigating Uncertainty in Engineering System Design, Systems Engineering, published online January 2018. (Also AIAA Paper 2015-0899, 56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimee, FL, January 5-9 2015.)
  24. Opgenoord, M., Drela, M. and Willcox, K., Physics-Based Low-Order Model for Transonic Flutter Prediction, AIAA Journal, Vol. 56, No. 4, pp. 1519-1531, 2018. (Also AIAA Paper 2017-4340, AIAA Theoretical Fluid Mechanics Conference Best Paper.)
  25. Peherstorfer, B., Gunzburger, M. and Willcox, K., Convergence analysis of multifidelity Monte Carlo estimation, Numerische Mathematik, 139(3):683-707, 2018. https://doi.org/10.1007/s00211-018-0945-7.
  26. Zimmermann, R., Peherstorfer, B. and Willcox, K., Geometric Subspace Updates with Applications to Online Adaptive Nonlinear Model Reduction, SIAM Journal on Matrix Analysis and Applications, Vol. 39, No. 1, pp. 234-261, 2018.
  27. Peherstorfer, B., Willcox, K. and Gunzburger, M., Survey of multifidelity methods in uncertainty propagation, inference, and optimization, SIAM Review, Vol. 60, No. 3, pp. 550-591, 2018.
  28. Willcox K. and Huang, L., Network models for mapping educational data, Design Science, Vol. 3, e18, 2017.
  29. Peherstorfer, B., Gugercin, S. and Willcox, K., Data-driven reduced model construction with time-domain Loewner models, SIAM Journal on Scientific Computing, Vol. 39, No. 5, pp. A2152-A2178, 2017.
  30. Cook, L., Jarrett, J. and Willcox, K., Extending Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties, AIAA Journal, Vol. 56, No. 2, pp. 849-861, 2018.
  31. Chaudhuri, A., Lam, R. and Willcox, K., Multifidelity uncertainty propagation via adaptive surrogates in coupled multidisciplinary systems. AIAA Journal, Vol. 56, No. 1, pp. 235-249, 2018.
  32. Nguyen V.B., Dou HS., Willcox K., Khoo BC., Model Order Reduction for Reacting Flows: Laminar Gaussian Flame Applications. In: Ben-Dor G., Sadot O., Igra O. (eds) 30th International Symposium on Shock Waves. Springer, 2017.
  33. Peherstorfer, B., Kramer, B. and Willcox, K., Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models, Journal of Computational Physics, Vol. 341, pp. 61-75, 2017.
  34. Kramer, B., Peherstorfer, B. and Willcox, K., Feedback control for systems with uncertain parameters using online-adaptive reduced models, SIAM Journal on Applied Dynamical Systems, Vol. 16, No. 3, pp. 1563-1586, 2017.
  35. Qian, E., Grepl, M., Veroy, K., and Willcox, K., A certified trust region reduced basis approach to PDE-constrained optimization, SIAM Journal on Scientific Computing, Vol. 39, No. 5 pp. S434-S460, 2017.
  36. Singh, V. and Willcox, K., Methodology for path planning with dynamic data-driven flight capability estimation, AIAA Journal, Vol. 55, No. 8, pp. 2727-2738, 2017.
  37. Spantini, A., Cui, T., Willcox, K., Tenorio, L. and Marzouk, Y. Goal-oriented optimal approximations of Bayesian linear inverse problems, SIAM Journal on Scientific Computing, Vol. 39, No. 5 pp. S167-S196, 2017.
  38. Amaral, S., Allaire, D., Willcox, K. and de la Rosa Blanco, E., A decomposition-based uncertainty quantification approach for environmental impacts of aviation technology and operation, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Volume 31, Issue 3 (Uncertainty Quantification for Engineering Design), pp. 251-264, August 2017.
  39. Mainini, L. and Willcox, K., Data to decisions: Real-time structural assessment from sparse measurements affected by uncertainty, Computers and Structures, Vol. 182, pp. 296-312, 2017.
  40. Amaral, S., Allaire, D. and Willcox, K. Optimal L2-norm empirical importance weights for the change of probability measure, Statistics and Computing, 27 (3), 625-643, May 2017.
  41. Ulker, F., Allaire, D. and Willcox, K., Sensitivity Guided Decision Making for Wind Farm Micro-Siting, International Journal for Numerical Methods in Fluids, Vol. 83, Iss. 1, pp. 52-72, 2017.
  42. Garg, V., Tenorio, L. and Willcox, K. Minimum local distance density estimation, Communications in Statistics -- Theory and Methods, Vol. 46, No. 1, pp. 148-164, 2017.
  43. Peherstorfer, B., Willcox, K. and Gunzburger, M., Optimal model management for multifidelity Monte Carlo estimation, SIAM Journal on Scientific Computing, Vol. 38, No. 5, pp. A3163-A3194, 2016.
  44. Opgenoord, M., Allaire, D. and Willcox, K., Variance-based sensitivity analysis to support simulation-based design under uncertainty, Journal of Mechanical Design, Vol. 138, No. 11, pp. 111410-111410-12, 2016. (Top 10 most accessed articles in Journal of Mechanical Design in 2019.)
  45. Zimmermann, R. and Willcox, K., An accelerated greedy missing point estimation procedure, SIAM Journal on Scientific Computing, Vol. 38, Issue 5, pp. A2827–A2850, 2016.
  46. Peherstorfer, B. and Willcox, K., Data-driven operator inference for nonintrusive projection-based model reduction, Computer Methods in Applied Mechanics and Engineering, Vol. 306, pp. 196-215, 2016.
  47. Cui, T., Marzouk, Y. and Willcox, K., Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction , Journal of Computational Physics, Vol. 315, pp. 363-387, June 2016.
  48. Peherstorfer, B. and Willcox, K., Dynamic data-driven model reduction: Adapting reduced models from incomplete data, Advanced Modeling and Simulation in Engineering Sciences , Vol. 3, Issue 1, 2016.
  49. Opgenoord, M. and Willcox, K., Sensitivity analysis methods for uncertainty budgeting in system design, AIAA Journal, Volume 54, Issue 10, pp. 3134-3148, 2016.
  50. Peherstorfer, B., Cui, T., Marzouk, Y. and Willcox, K., Multifidelity importance sampling, Computer Methods in Applied Mechanics and Engineering , Vol. 300, pp. 490-509, 2016.
  51. Ng, L. and Willcox, K. Monte Carlo information-reuse approach to aircraft conceptual design optimization under uncertainty, AIAA Journal of Aircraft, Vol. 53, No. 2, pp. 427-438, 2016. (An earlier version of this work appeared in AIAA Paper 2014-0802, January 2014.)
  52. Benner, P., Gugercin, S. and Willcox, K., A survey of projection-based model reduction methods for parametric dynamical systems, SIAM Review, Vol. 57, No. 4, pp. 483–531, 2015.
  53. Peherstorfer, B. and Willcox, K., Online adaptive model reduction for nonlinear systems via low-rank updates, SIAM Journal on Scientific Computing , Vol. 37, No. 4, pp. A2123-A2150, 2015.
  54. Peherstorfer, B. and Willcox, K., Dynamic data-driven reduced-order models, Computer Methods in Applied Mechanics and Engineering , Vol. 291, pp. 21-41, 2015.
  55. Lecerf, M., Allaire, D. and Willcox, K. Methodology for dynamic data-driven online flight capability estimation, AIAA Journal , Vol. 53, No. 10, pp. 3073-3087, October 2015. (An earlier version of this work appeared in AIAA Paper 2014-1175, January 2014.)
  56. Peherstorfer, B. and Willcox, K., Detecting and adapting to parameter changes for reduced models of dynamic data-driven application systems, Procedia Computer Science , Vol. 51, pp. 2553-2562, 2015.
  57. Mainini, L. and Willcox, K. A surrogate modeling approach to support real-time structural assessment and decision-making, AIAA Journal, Vol. 53, No. 6, pp. 1612-1626, 2015. (An earlier version of this work appeared in AIAA Paper 2014-1488, presented at 10th AIAA Multidisciplinary Design Optimization Conference, National Harbor, MD, January 2014.)
  58. Liao, Q. and Willcox, K. A domain decomposition approach for uncertainty analysis, SIAM Journal on Scientific Computing, Vol. 37, No. 1, pp. A103-A133, 2015.
  59. Amaral, S., Allaire, D. and Willcox, K. A decomposition-based approach to uncertainty analysis of feed-forward multicomponent systems, International Journal for Numerical Methods in Engineering, Volume 100, Issue 13, pages 982-1005, December 2014.
  60. Ng, L. and Willcox, K. Multifidelity approaches for optimization under uncertainty, International Journal for Numerical Methods in Engineering, Volume 100 Issue 10, pp. 746-772, published online 17 September, 2014, DOI: 10.1002/nme.4761. (An earlier version of this work appeared in AIAA Paper 2012-5602, September 2012.)
  61. Cui, T., Marzouk, Y. and Willcox, K. Data-driven model reduction for the Bayesian solution of inverse problems, International Journal for Numerical Methods in Engineering, Vol. 102, No. 5, pp. 966-990, published online 15 August, 2014, DOI: 10.1002/nme.4748.
  62. Allaire, D., Kordonowy, D.,Lecerf, M., Mainini, L. and Willcox, K. Multifidelity DDDAS Methods with Application to a Self-Aware Aerospace Vehicle, Procedia Computer Science, Vol. 29, pp. 1182-1192, 2014.
  63. Allaire, D. and Willcox, K. Uncertainty assessment of complex models with application to aviation environmental policy-making, Transport Policy , Volume 34, July 2014, pp. 109-113. Available online 20 March 2014, ISSN 0967-070X, http://dx.doi.org/10.1016/j.tranpol.2014.02.022.
  64. Allaire, D., Noel, G., Willcox, K. and Cointin, R. Uncertainty quantification of an aviation environmental toolsuite, Reliability Engineering & System Safety , Volume 126, June 2014, pp. 14-24. Available online 15 January 2014.
  65. Nguyen, V.B., Buffoni, M., Willcox, K. and Khoo, B.C. Model reduction for reacting flow applications, International Journal of Computational Fluid Dynamics , Volume 28, Issue 3-4, May 2014.
  66. Nguyen, N.C., Khoo, B.C. and Willcox, K. Model order reduction for Bayesian approach to inverse problems, Asia Pacific Journal on Computational Engineering Vol. 1, No. 2, April 2014.
  67. Lieberman, C. and Willcox, K. Nonlinear Goal-Oriented Bayesian Inference: Application to Carbon Capture and Storage, SIAM Journal on Scientific Computing Vol. 36, No. 3, pp. B427-B449.
  68. Peherstorfer, B., Butnaru, D., Willcox, K. and Bungartz, H.-J., Localized discrete empirical interpolation method, SIAM J. Scientific Computing , Vol. 36, No. 1, pp. A168-A192, 2014.
  69. Allaire, D. and Willcox, K. A mathematical and computational framework for multifidelity design and analysis with computer models, International Journal on Uncertainty Quantification , Vol. 4, Issue 1, pp. 1-20, January 2014.
  70. Burgiel, H., Lieberman, C., Miller, H. and Willcox, K. Interactive applets in calculus and engineering courses, chapter in Enhancing Mathematics Understanding through Visualization: The Role of Dynamical Software , S. Habre (Ed.), IGI Global, December 2013.
  71. Kaijima, S., Bouffanais, R., Willcox, K. and Naidu, S. Computational fluid dynamics for architectural design, in Computation Works: The Building of Algorithmic Thought, Architectural Design, X. De Kestelier, B. Peters (eds), March 2013.
  72. Lieberman, C. and Willcox, K. Goal-oriented inference: Approach, linear theory, and application to advection-diffusion , SIAM Review , Vol. 55, No. 3, pp. 493-519, 2013. (SIGEST award)
  73. Lieberman, C., Fidkowski, K, Willcox, K. and van Bloemen Waanders, B. Hessian-based model reduction: Large-scale inversion and prediction, International Journal of Numerical Methods in Fluids , Vol. 71, pp. 135-150, January 2013.
  74. Lieberman, C. and Willcox, K. Goal-oriented inference: Approach, linear theory, and application to advection-diffusion, SIAM Journal on Scientific Computing , Vol. 34, No.4, pp. 1880-1904, 2012.
  75. Allaire, D, He, Q., Deyst, J. and Willcox, K. An Information-theoretic Metric of System Complexity with Application to Engineering System Design, Journal of Mechanical Design , Vol. 134, Issue 10, October, 2012.
  76. March, A. and Willcox, K. A Provably Convergent Multifidelity Optimization Algorithm not Requiring High-Fidelity Derivatives, AIAA Journal , Vol. 50, No. 5, pp. 1079-1089, 2012.
  77. March, A. and Willcox, K. Constrained multifidelity optimization using model calibration, Structural and Multidisciplinary Optimization , Vol. 46, pp. 93-109, 2012.
  78. March, A., Wang, Q. and Willcox, K. Gradient-based Multifidelity Optimization for Aircraft Design using Bayesian Model Calibration, The Aeronautical Journal , Vol. 115, No. 1174, December, 2011.
  79. Allaire, D. and Willcox, K. A Variance-Based Sensitivity Index Function for Factor Prioritization, Reliability Engineering and System Safety, Vol. 107, November 2012, pp. 107-114.
  80. Allaire, D. and Willcox, K. Distributional Sensitivity Analysis, Procedia -- Social and Behavioral Sciences , Vol. 2, Issue 6, pp. 7595-7596, 2010.
  81. Stirling, L., Willcox, K. and Newman, D., Development of a Computational Model for Astronaut Reorientation, Journal of Biomechanics , Vol. 43, Issue 12, pp. 2309-2314, August 2010.
  82. Lieberman, C., Willcox, K. and Ghattas, O., Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems, SIAM Journal on Scientific Computing , Vol. 32, No.5, pp. 2523-2542, August 2010.
  83. Frangos, M., Marzouk, Y., Willcox, K. and van Bloemen Waanders, B., Surrogate and reduced-order modeling: a comparison of approaches for large-scale statistical inverse problems, in Computational Methods for Large-Scale Inverse Problems and Quantification of Uncertainty , Biegler et al. (Eds.), Wiley, 2010.
  84. Allaire, D. and Willcox, K., Surrogate Modeling for Uncertainty Assessment with Application to Aviation Environmental System Models, AIAA Journal, Vol. 48, No. 8, August 2010.
  85. Galbally, D., Fidkowski, K., Willcox, K. and Ghattas, O., Nonlinear Model Reduction for Uncertainty Quantification in Large-Scale Inverse Problems, International Journal for Numerical Methods in Engineering, Volume 81, Issue 12, March 2010, pp. 1581-1608.
  86. Degroote, J., Vierendeels, J. and Willcox, K., Interpolation among reduced-order matrices to obtain parametrized models for design, optimization and probabilistic analysis, International Journal for Numerical Methods in Fluids, Vol. 63, No. 2, pp. 207-230, May 2010.
  87. Stirling, L., Ferguson, P., Willcox, K. and Newman, D., Kinetics and Kinematics for Translational Motions in Microgravity During Parabolic Flight. Journal of Aviation, Space, and Environmental Medicine, Vol. 80, No. 6, pp 522-531, June 2009.
  88. Stirling, L., Newman, D. and Willcox, K., Self-Rotations in Simulated Microgravity: Performance Effects of Strategy Training, Journal of Aviation, Space and Environmental Medicine, Vol. 80, No. 1, pp. 5-14, January 2009.
  89. Robinson, T., Willcox, K., Eldred, M., and Haimes, R. Multifidelity Optimization for Variable-Complexity Design, AIAA Journal, Vol. 46, No. 11, pp. 2814-2822, 2008.
  90. Bui-Thanh, T., Willcox, K., and Ghattas, O., Parametric Reduced-Order Models for Probabilistic Analysis of Unsteady Aerodynamic Applications, AIAA Journal, Vol. 46, No. 10, pp. 2520-2529, 2008.
  91. Bui-Thanh, T., Willcox, K., and Ghattas, O., Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space, SIAM Journal on Scientific Computing, Vol. 30, No. 6, pp. 3270-3288, 2008.
  92. Hovland, S., Gravdahl, J., and Willcox, K., Explicit Model Predictive Control for Large-Scale Systems via Model Reduction, AIAA Journal for Guidance, Control, and Dynamics, Vol. 31, No. 4, July-August, 2008.
  93. Astrid, P., Weiland, S., Willcox, K., and Backx, T., Missing Point Estimation in Models Described by Proper Orthogonal Decomposition, IEEE Transactions on Automatic Control, Vol. 53, Issue 10, pp. 2237-2251, 2008. Also presented at 43rd IEEE Conference on Decision and Control, Paradise Island, Bahamas, December 2004.
  94. Bashir, O., Willcox, K., Ghattas, O., van Bloemen Waanders, B., and Hill, J., Hessian-Based Model Reduction for Large-Scale Systems with Initial Condition Inputs, International Journal for Numerical Methods in Engineering, Vol. 73, Issue 6, pp. 844-868, 2008.
  95. Gugercin, S. and Willcox, K., Krylov Projection Framework for Fourier Model Reduction, Automatica, Vol. 44, No. 1, pp. 209-215, 2008.
  96. Willcox, K. Model Reduction for Large-Scale Applications in Computational Fluid Dynamics, in Real-Time PDE-Constrained Optimization, Biegler, L., Ghattas, O., Heinkenschloss, M., Keyes, D., and van Bloemen Waanders, B. (Eds.), SIAM Book Series, pp. 217-233, 2007.
  97. Bui-Thanh, T., Willcox, K., Ghattas, O., and van Bloemen Waanders, B., Goal-Oriented, Model-Constrained Optimization for Reduction of Large-Scale Systems, Journal of Computational Physics, Vol. 224, No. 2, pp. 880-896, June 2007.
  98. My-Ha, D., Lim, K.M., Khoo, B.C. and Willcox, K., Real-Time Optimization Using Proper Orthogonal Decomposition: Free Surface Shape Prediction due to Underwater Bubble Dynamics, Computers and Fluids, Vol. 36, No. 3, March 2007, pp. 499-512.
  99. Peoples, R. and Willcox, K., Value-Based Multidisciplinary Optimization for Commercial Aircraft Design and Business Risk Assessment, Journal of Aircraft, Vol. 43, No. 4, July-August, 2006, pp. 913-921.
  100. Willcox, K., Unsteady Flow Sensing and Estimation via the Gappy Proper Orthogonal Decomposition, Computers & Fluids, Volume 35, Issue 2, February 2006, pp. 208-226.
  101. Willcox, K. and Lassaux, G., Model Reduction of an Actively Controlled Supersonic Diffuser, in Dimension Reduction of Large-Scale Systems, Springer Series on Lecture Notes in Computational Science and Engineering, Vol. 45, Benner, P. Mehrmann, V. and Sorensen, D. (Eds.), 2005, pp. 357-361.
  102. Willcox, K. and Megretski, A., Fourier Series for Accurate, Stable, Reduced-Order Models in Large-Scale Applications, SIAM Journal for Scientific Computing, Vol. 26, No. 3, 2005, pp. 944-962.
  103. Bui-Thanh, T., Damodaran, M. and Willcox, K., Aerodynamic Data Reconstruction and Inverse Design using Proper Orthogonal Decomposition, AIAA Journal, Vol. 42, No. 8, August 2004, pp. 1505-16.
  104. Markish, J. and Willcox, K., Value-Based Multidisciplinary Techniques for Commercial Aircraft System Design, AIAA Journal, Vol. 41, No. 10, October 2003, pp. 2004-12.
  105. Willcox, K. and Wakayama, S., Simultaneous Optimization of a Multiple-Aircraft Family, Journal of Aircraft, Vol. 40, No. 4, July 2003, pp. 616-622.
  106. Shapiro, B. and Willcox, K., Analyzing the Mistuning of Bladed Disks by Symmetry and Reduced-Order Aerodynamic Modeling. Journal of Power and Propulsion, Vol. 19, No. 2, March-April 2003, pp. 307-311.
  107. Willcox, K. and Peraire J., Balanced Model Reduction via the Proper Orthogonal Decomposition. AIAA Journal, Vol. 40, No. 11, November 2002, pp. 2323-30.
  108. Willcox, K., Peraire J. and White, J., An Arnoldi approach for generation of reduced-order models for turbomachinery. Computers and Fluids, Vol. 31, No. 3, pp. 369-89, March 2002.
  109. Willcox, K., Peraire J. and Paduano, J., Application of Model Order Reduction to Compressor Aeroelastic Models. Paper 2000-GT-0377, presented at the ASME International Gas Turbine and Aeroengine Technical Conference, May 2000, Munich, Germany. Journal of Engineering for Gas Turbines and Power, Vol. 124, No. 2, pp. 332-39, April 2002.
  110. Willcox, K. and Peraire J., Aeroelastic computations in the time domain using unstructured meshes, International Journal for Numerical Methods in Engineering, Vol. 40, No. 13, pp. 2413-31, July 1997.

Proceedings of Refereed Conferences
(Selected)

  1. Kapteyn, M., Knezevic, D., and Willcox, K., Toward predictive digital twins via component-based reduced-order models and interpretable machine learning. In Proceedings of 2020 AIAA SciTech Forum & Exhibition, Orlando FL, January, 2020.
  2. Chaudhuri, A., Peherstorfer, B., and Willcox, K., Multifidelity Cross-Entropy Estimation of Conditional Value-at-Risk for Risk-Averse Design Optimization. In Proceedings of 2020 AIAA SciTech Forum & Exhibition, Orlando FL, January, 2020.
  3. Qian, E., Kramer, B., Marques, A. and Willcox, K., Transform & Learn: A data-driven approach to nonlinear model reduction. In Proceedings of AIAA Aviation Forum & Exhibition, Dallas, TX, June 2019.
  4. Marques, A., Lam, R., Chaudhuri, A., Opgenoord, M. and Willcox, K., A multifidelity method for locating aeroelastic flutter boundaries. 21st AIAA Non-Deterministic Approaches Conference (AIAA Scitech), San Diego, CA, January 2019. DOI 10.2514/6.2019-0438.
  5. Chaudhuri, A., Marques, A., Lam, R., and Willcox, K., Reusing information for multifidelity active learning in reliability-based design optimization. 21st AIAA Non-Deterministic Approaches Conference (AIAA Scitech), San Diego, CA, January 2019. DOI 10.2514/6.2019-1222.
  6. Marques, A., Lam, R. and Willcox, K., Contour location via entropy reduction leveraging multiple information sources. Advances In Neural Information Processing Systems (NeurIPS) 31, pp. 5223-5233, 2018. Supplementary material.
  7. Peherstorfer, B., Beran, P.S., and Willcox, K., Multifidelity Monte Carlo Estimation for Large-scale Uncertainty Propagation. In proceedings of 2018 AIAA Scitech Forum, Kissimmee, FL, January, 2018.
  8. Feldstein, A., Lazzara, D., Princen, N., and Willcox, K., Model Uncertainty: A Challenge in Nonlinear Coupled Multidisciplinary System Design. In proceedings of 2018 AIAA Scitech Forum, Kissimmee, FL, January, 2018.
  9. Lam, R. and Willcox, K. , Lookahead Bayesian Optimization with Inequality Constraints. Advances In Neural Information Processing Systems (NIPS), pp. 1888-1898, 2017.
  10. Willcox K. and Huang, L., Mapping the CDIO Curriculum with Network Models, in Proceedings of the 13th International CDIO Conference, University of Calgary, Calgary, Canada, June 18-22, 2017.
  11. Cook, L., Jarrett, J. and Willcox, K., Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties. 19th AIAA Non-deterministic Approaches Conference (AIAA Scitech), Grapevine, TX, January 2017.
  12. Lam, R., Willcox, K. and Wolpert, D., Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach. In Advances In Neural Information Processing Systems (NIPS) 29, pp. 883-891, 2016.
  13. Seering, J., Huang, L. and Willcox, K., Mapping Outcomes in an Undergraduate Aerospace Engineering Program. American Society for Engineering Education, 12th Annual Conference & Exposition, June 2015.
  14. Ng, L., Huynh, D.B.P. and Willcox, K., Multifidelity Uncertainty Propagation for Optimization Under Uncertainty, AIAA Paper 2012-5602, 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Indianapolis, IN, September 2012.
  15. Allaire, D. and Willcox, K., "A Bayesian-Based Approach to Multi-Fidelity Multidisciplinary Design Optimization," AIAA-2010-9183, presented at 13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Fort Worth, TX, September 13-15, 2010.
  16. Buffoni, M. and Willcox, K., Projection-Based Model Reduction for Reacting Flows, AIAA-2010-5008, presented at 40th Fluid Dynamics Conference and Exhibit, Chicago, IL, June 28-July 1, 2010
  17. Lehner, S., Lurati, L., Bower, G., Cramer, E., Crossley, W., Engelsen, F., Kroo, I., Smith, S., Willcox, K., "Advanced Multidisciplinary Optimization Techniques for Efficient Subsonic Aircraft Design," AIAA-2010-1321, presented at 48th AIAA Aerospace Sciences Meeting, Orlando, FL, Jan. 4-7, 2010.
  18. Noel, G., Allaire, D., Jacobsen, S., Willcox, K., and Cointin, R., "Assessing the Uncertainty in FAA's Noise and Emissions Compliance Model," Inter-Noise Conference, Ottawa, Canada, August 23-26, 2009.
  19. Noel, G., Allaire, D., Jacobsen, S., Willcox, K., and Cointin, R., "Assessment of the Aviation Environmental Design Tool," Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009), Napa, CA, June 29 - July 2, 2009.
  20. March, A., Waitz, I., and Willcox, K. "A Methodology for Integrated Conceptual Design of Aircraft Configuration and Operation to Reduce Environmental Impact," AIAA-2009-7026, presented at 9th AIAA Aviation Technology, Integration, and Operations Conference, Hilton Head, SC, September 21-23, 2009.
  21. Lazzara, D., Haimes, R. and Willcox, K. "Multifidelity Geometry and Analysis in Aircraft Conceptual Design," AIAA-2009-3806, presented at 27th AIAA Applied Aerodynamics Conference, San Antonio, TX, June 22-25, 2009.
  22. Fidkowski, K., Engelsen, F., Willcox, K., and Kroo, I. "Stochastic Gust Analysis Techniques for Aircraft Conceptual Design," AIAA-2008-5848, presented at 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, British Columbia, September 10-12, 2008.
  23. Robinson, T., Ooi, B.H., Taff, B., Willcox, K. and Voldman, J., "Surrogate-Based Optimization of a Microfluidic Weir Structure for Single-Cell Manipulation," AIAA-2008-5889, presented at 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, British Columbia, September 10-12, 2008.
  24. Stirling, L., Arsie, A., Willcox, K., Frazzoli, E. and Newman, D., "Application of Quantized Control to Self-Rotation Maneuvers," 46th IEEE Conference on Decision and Control, New Orleans, LA, December 2007.
  25. Allaire, D., Waitz, I. And Willcox, K., "A Comparison of Two Methods for Predicting Emissions from Aircraft Gas Turbine Engine Combustors," ASME Paper GT2007-28346, presented at the ASME International Gas Turbine and Aeroengine Technical Conference, Montreal, Canada, June 2007.
  26. Allaire, D., Waitz, I. And Willcox, K., "A Comparison of Two Methods for Predicting Emissions from Aircraft Gas Turbine Engine Combustors," ASME Paper GT2007-28346, presented at the ASME International Gas Turbine and Aeroengine Technical Conference, Montreal, Canada, June 2007.
  27. Bashir, O., Ghattas, O., Hill, J., van Bloemen Waanders, B., and Willcox, K., "Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems," Proceedings of International Conference on Computational Science, Beijing, China, Y. Shi et al. (Eds.): ICCS 2007, Part I, LNCS 4487, pp. 1010-1017, Springer-Verlag, May 2007.
  28. Stirling, L., Willcox, K. and Newman, D., "Development of Astronaut Orientation Strategies using Optimization Methodologies," Multibody Dynamics 2007, ECCOMAS Thematic Conference, Milan, Italy, June 2007.
  29. Bui-Thanh, T., Willcox, K., and Ghattas, O., "Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space," AIAA Paper 2007-2049, presented at the 48th AIAA Structures, Structural Dynamics and Materials Conference, Waikiki, HI, April 2007.
  30. Jones, A., Willcox, K., and Hileman, J., "Distributed Multidisciplinary Optimization of Aircraft Design and Takeoff Operations for Low Noise," AIAA Paper 2007-1856, presented at the 2nd AIAA Multidisciplinary Design Optimization Specialist Conference, Waikiki, HI, April 2007.
  31. Hovland, S., Willcox, K., and Gravdahl, J., "MPC for large-scale systems via model reduction and multiparametric quadratic programming," 45th IEEE Conference on Decision and Control, San Diego, CA, December 2006.
  32. Robinson, T., Eldred, M., Willcox, K. and Haimes, R. "Strategies for Multi-fidelity Optimization with Variable Dimensional Hierarchical Models," AIAA paper 2006-1819, presented at the 1st Multidisciplinary Design Optimization Specialist Conference, Newport, RI, April 2006.
  33. Diedrich, A., Hileman, J., Tan, D., Willcox, K. and Spakovszky, Z. "Multidisciplinary Design and Optimization of the Silent Aircraft," AIAA paper 2006-1323, presented at the 44th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, January 2006.
  34. Willcox, K., Ghattas, O., van Bloemen Waanders, B., and Bader, B., "A Goal-Oriented Optimization Framework for Model Reduction of Large-scale Systems," 44th IEEE Conference on Decision and Control, Seville, Spain, December 2005.
  35. Bui-Thanh, T. and Willcox, K., "Model Reduction for Large-Scale CFD Applications Using the Balanced Proper Orthogonal Decomposition," AIAA Paper 2005-4617, presented at the 16th AIAA Computational Fluid Dynamics Conference, Toronto, Canada, June 2005.
  36. Astrid, P., Weiland, S. and Willcox, K., "On the acceleration of a POD-based model reduction technique," Proceedings of the 16th International Symposium on Mathematical Theory of Networks and Systems, Leuven, Belgium 5-9 July 2004.
  37. Willcox, K. and Bounova, G., "Mathematics in Engineering: Identifying, Enhancing and Linking the Implicit Mathematics Curriculum," presented at ASEE Annual Conference, Salt Lake City, UT, June 2004.
  38. Antoine, N., Kroo, I., Willcox, K. and Barter, G. "A Framework for Aircraft Conceptual Design and Environmental Performance Studies," AIAA Paper 2004-4314, presented at the 10th AIAA Multidisciplinary Analysis and Optimization Conference, Albany, NY, August 2004.
  39. Peoples, R. and Willcox, K., "A Value-Based MDO Approach to Assess Business Risk for Commercial Aircraft Design," AIAA Paper 2004-4438, presented at the 10th AIAA Multidisciplinary Analysis and Optimization Conference, Albany, NY, August 2004.
  40. Gratton, D. and Willcox, K., "Reduced-Order, Trajectory Piecewise-Linear Models for Nonlinear Computational Fluid Dynamics," in Proceedings of the 5th SMA Symposium, January 2004, also AIAA Paper 2004-2329, presented at 34th AIAA Fluid Dynamics conference, Portland, OR, June 2004.
  41. Peoples, R. and Willcox, K., "Value-Based Multidisciplinary Optimization for Commercial Aircraft Design," AIAA paper 2004-1542, presented at the 45th AIAA Structures, Structural Dynamics and Materials conference, Palm Springs, CA, April 2004.
  42. Willcox, K. and Megretski, A., "Model Reduction for Large-Scale Linear Applications", presented at the 13th IFAC Symposium on System Identification, Rotterdam, The Netherlands, August 2003.
  43. Bui-Thanh, T., Damodaran, M. and Willcox, K., "Applications of Proper Orthogonal Decomposition for Inviscid Transonic Aerodynamics", AIAA Paper 2003-4213, presented at 15th Computational Fluid Dynamics Conference, Orlando, FL, June 2003.
  44. Deremaux, Y. and Willcox, K., "Real-Time Visualization and Constraint Analysis in Multidisciplinary Design Optimization", AIAA Paper 2003-3876, presented at 15th Computational Fluid Dynamics Conference, Orlando, FL, June 2003.
  45. Lassaux, G. and Willcox, K., "Model reduction for active control design using multiple-point Arnoldi methods", AIAA Paper 2003-0616, presented at 41st Aerospace Sciences Meeting & Exhibit, Reno, NV, January 2003.
  46. Willcox, K., "Controllable and Observable Subspaces in Computational Fluid Dynamics", in Computational fluid dynamics, 2002 (Sydney), pp. 159-164, Springer, Berlin, 2003.
  47. Markish, J. and Willcox, K., "A Value-Based Approach for Commercial Aircraft Conceptual Design," in Proceedings of the ICAS2002 Congress, Toronto, Canada, September 2002.
  48. Willcox, K. and Peraire, J., "Application of Reduced-Order Aerodynamic Modeling to the Analysis of Structural Uncertainty in Bladed Disks". ASME Paper GT-30680, presented at the ASME International Gas Turbine and Aeroengine Technical Conference, Amsterdam, The Netherlands, June 2002.
  49. Willcox, K., Paduano, J., Peraire J. and Hall, K., "Low Order Aerodynamic Models for Aeroelastic Control of Turbomachines". AIAA paper 99-1467, presented at the 40th AIAA Structures, Structural Dynamics and Materials conference, April 1999, St Louis, MO.