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[1] "Inverse Problems in Engineering: Theory and Practice", N. Zabaras, M. Raynaud and K. Woodbury (edts.), 1993 (proceedings of the First International Conference on Inverse Problems in Engineering: Theory and Practice, held at Palm Coast, Florida, June 13-18, 1993), published by ASME (November 1993).

[2] "The Integration of Material, Process and Product Design", N. Zabaras, R. Becker, S. Ghosh and L. Lalli (edts.), 1998 (proceedings of the symposium on the 70th birthday of Dr. Owen Richmond, held at Seven Springs, October 19--20, 1998), published by Balkema, Rotterdam, Netherlands (September 1999).

[3] "Stochastic Modeling of Multiscale and Multiphysics Problems", N. Zabaras and D. Xiu (edts.), 2008 (special issue of Computer Methods in Applied Mechanics and Engineering, August 2008), published by Elsevier.

[4] "USA/South America Symposium on Stochastic Modeling and Uncertanity Quantification", Leblon Beach, Rio de Janeiro, Brazil, August 1-5, 2011, N. Zabaras (edt.), 2012 (special issues of the Int. J. Uncertainty Quantification, March 12), published by Begell House.

[5] "Big Data and Predictive Computational Modeling", Institute for Advanced Study, Technical University of Munich, Munich, Germany, May 18-21, 2015, P.S. Koutsourelakis, N. Zabaras and M. Girolami (Editors) (special issue at the Journal of Computational Physics), published by Elsevier. 

[6] "Predictive Multiscale Materials Modeling", Isaac Netwon Institute for Mathematical Sciences, The Gateway to Mathematics (TGM), University of Cambridge, December Technical University of Munich, Munich, Germany, December 1-4, 2015, M. Katsoulakis and N. Zabaras (Editors) (special issue at the Journal of Computational Physics), published by Elsevier. 


[1] N. Zabaras, "An object-oriented approach to the finite element analysis and design of material processes", chapter 8, pp. 239--282, in Advances in Software Tools for Scientific Computing, Lecture Notes in Computational Science and Engineering, Vol. 10 (edts. H.P. Langtangen, A.M. Bruaset and E. Quak) Springer Verlag, 2000.

[2] N. Zabaras, "Inverse problems in heat transfer", chapter 17, in the Handbook of Numerical Heat Transfer, 2nd Edt., John Wiley & Sons, January 2004 (W.J. Minkowycz, E.M. Sparrow, J. Y. Murthy, edts.)

[3] N. Zabaras, "Solving Stochastic Inverse Problems: A Sparse Grid Collocation Approach", chapter 14, pp. 291--317, in Computational Methods for Large-Scale Inverse Problems and Quantification of Uncertainity (edts. Bart van Bloemen Waanders et al.), published by John Wiley & Sons, January 11, 2011.

[4] Ilias Bilionis and N. Zabaras, "Bayesian Uncertainty Propagation Using Gaussian Processes", In R. Ghanem, D. Higdon and H. Owhadi (edts.), Handbook of Uncertainty Quantification, Springer International Publishing, pp. 1-45, 2017. 

[5] Jesper Kristensen, Ilias Bilionis and N. Zabaras, "Adaptive Simulation Selection for the Discovery of the Ground State Line of Binary Alloys with a Limited Computational Budget", In R. Melnik et al. (eds.), Recent Progress and Modern Challenges in Applied Mathematics, Modeling and Computational Science, Fields Institute Communications Vol. 79, 2017. 

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