Publications


Submitted publications and preprints:

  • Tong G.G., Sing Long C.A., Schiavazzi D.E., InVAErt networks: a data-driven framework for model sythesis and identifiability analysis, Submitted for publication, 2023. Arxiv

  • Wang Y., Cobian E.R., Lee J., Liu F., Hauenstein J.D., Schiavazzi D.E., LINFA: a Python library for variational inference with normalizing flow and annealing, Submitted for publication, 2023. Arxiv

  • Su B., Wang Y., Schiavazzi D.E., Liu F., Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records, Submitted for publication, 2023. Arxiv

Peer-reviewed publications:

  • Partin L., Schiavazzi D.E., Sing Long C.A., An analysis of reconstruction noise from undersampled 4D flow MRI, Biomedical Signal Processing and Control, Accepted, 2023. Link

  • Cobian E.R., Hauenstein J.D., Liu F., Schiavazzi D.E., AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation, International Journal of Uncertainty Quantification, Accepted, 2023. Link

  • Tong G.G., Schiavazzi D.E., Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissue, Computational Mechanics, 71(3):453-479, 2023. Link

  • Partin L., Geraci G., Rushdi A.A., Eldred M.S., Schiavazzi D.E., Multifidelity data fusion in convolutional encoder/decoder networks, Journal of Computational Physics, 472:111666, 2023. Link

  • Wang Y., Liu F., Schiavazzi D.E., Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive Models, Journal of Computational Physics, 467:111454, 2022. Link

  • Partin L., Rushdi A.A., Schiavazzi D.E., Multifidelity data fusion in convolutional encoder/decoder assembly networks for computational fluid dynamics, AIAA SCITECH 2022 Forum, 2022. Link

  • Li X., Schiavazzi D.E., An ensemble solver for segregated cardiovascular FSI, Computational Mechanics, 68(6):1421-1436, 2021. Link

  • Maher G.D., Fleeter C.M., Schiavazzi D.E., Marsden A.L., Geometric Uncertainty in Patient-Specific Cardiovascular Modeling with Convolutional Dropout Networks, Computer Methods in Applied Mechanics and Engineering, 386:114038, 2021. Link

  • Harrod K.K., Rogers J.L., Feinstein J.A., Marsden A. L., Schiavazzi D.E., Predictive modeling of secondary pulmonary hypertension in left ventricular diastolic dysfunction, Frontiers in Computational Physiology, 12:654, 2021. Link

  • Seo J., Fleeter C.M., Kahn A.M., Marsden A.L., Schiavazzi D.E. Multi-fidelity estimators for coronary circulation models under clinically-informed data uncertainty, International Journal for Uncertainty Quantification, 10(5):449-466, 2020. Link

  • Seo J., Schiavazzi D.E., Kahn A.M., Marsden A.L., The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls, International Journal of Numerical Methods in Biomedical Engineering, 36(8):e3351, 2020. Link

  • Fleeter C.M., Geraci G., Schiavazzi D.E., Kahn A.M., Marsden A.L., Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics, Computer Methods in Applied Mechanics and Engineering, 365:113030, 2020. Link

  • Khosravi R., Bangalore Ramachandra A., Szafron J.M., Schiavazzi D.E., Breuer C.K., Humphrey J.D., A computational Bio-Chemo-Mechanical model of in-vivo tissue engineered vascular graft development, Integrative Biology, March 2020. Link

  • Schiavazzi, D.E. and Juliano, T.J., Bayesian Network Inference of Thermal Protection System Failure in Hypersonic Vehicles, AIAA Scitech 2020 Forum, 2020. link

  • Akintunde A.R., Miller K.S., Schiavazzi D.E., Bayesian inference of constitutive model parameters from uncertain uniaxial experiments on murine tendons, Journal of the Mechanical Behavior of Biomedical Materials, 96:285-300, 2019. Link

  • Seo, J., Schiavazzi D.E., Marsden A., Performance of preconditioned iterative linear solvers for cardiovascular simulations in rigid and deformable vessels, Computational Mechanics, 64(3):717-739,2019. Link

  • Tran J.S., Schiavazzi D.E., Kahn A.M., Marsden A.L., Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts, Computer Methods in Applied Mechanics and Engineering, 345:402-428, 2019. Link

  • Fleeter C. M., Geraci G., Schiavazzi D.E., Kahn A.M., Eldred M.S., Marsden A.L., Multifidelity multilevel approaches for cardiovascular flow under uncertainty, in Center for Computing Research Summer Proceedings 2017, A.D. Baczewski and M.L. Parks, eds., Technical Report SAND2018-2780O, Sandia National Laboratories, pp. 27-50, 2018. Link

  • Amili O., Schiavazzi D.E., Moen S. , Jagadeesan B., Van de Moortele P.F., Coletti F., Hemodynamics in a giant intracranial aneurysm characterized by in vitro 4D flow MRI, PLOS One, 13(1):e0188323, 2018. Link

  • Schiavazzi D.E., Nemes A., Schmitter S. and Coletti F., The Effect of Velocity Filtering in Pressure Estimation, Experiments in Fluids, 58(5):1-21, 2017. Link

  • Schiavazzi D.E., Doostan A., Iaccarino G. and Marsden A.L., A Generalized Multi-resolution Expansion for Uncertainty Propagation with Application to Cardiovascular Modeling, Computer Methods in Applied Mechanics and Engineering, 314(1):196-221, 2017. Link

  • Ward E., Schiavazzi D.E., Sood D., Marsden A., Lane J., Owens E., Barleben A., CT FFR Can Identify Culprit Lesions in Aorto-iliac Occlusive Disease Using Minimally-Invasive Techniques, Annals of Vascular Surgery, 38:151-157, 2017. Link

  • Tran J., Schiavazzi D.E., Ramachandra B.A., Kahn A. and Marsden A.L., Automated tuning for parameter identification in multi-scale coronary simulations, Computer and Fluids, 142(5):128-138, 2017. Link

  • Schiavazzi D.E., Baretta A., Pennati G., Hsia T.Y. and Marsden A.L., Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty, International Journal of Numerical Methods in Biomedical Engineering, 33(3):1-34, 2017. Link

  • Schiavazzi D.E., Hsia T.Y. and Marsden A.L., On a sparse pressure-flow rate condensation of rigid circulation models, Journal of Biomechanics, 49(11):2174-2186, 2016. Link

  • Schiavazzi D.E., Arbia G., Baker C., Hsia T.Y., Marsden A.L. and Vignon-Clementel I.E., Uncertainty quantification in virtual surgery hemodynamics predictions for single ventricle palliation, International Journal of Numerical Methods in Biomedical Engineering, 32(3):1-25, 2016. Link

  • Schiavazzi D.E., Kung E., Marsden A.L., Baker C., Pennati G., Hsia T.Y., Hlavacek A.M. and Dorfman A.L., Hemodynamic effects of left pulmonary artery stenosis following superior cavopulmonary connection: a patient-specific multiscale modeling study, Journal of Thoracic and Cardiovascular Surgery, 149(3):689-696, 2015. Link

  • Banko A.J., Coletti F., K., Schiavazzi D.E., Elkins C.J. and Eaton J.K., Three-dimensional inspiratory flow in the upper and central human airways, Experiments in Fluids, 56(6):1-12, 2015. Link

  • Schiavazzi D.E., Doostan A. and Iaccarino G., Sparse multiresolution regression for uncertainty propagation, International Journal for Uncertainty Quantification, 4(4):303-331, 2014. Link

  • Schiavazzi D.E., Coletti F., Iaccarino G. and Eaton J.K., A matching pursuit approach to solenoidal filtering of three-dimensional velocity measurements, Journal of Computational Physics, 263:206-221, 2014. Link

  • Coletti, F., Muramatsu K., Schiavazzi D.E., Elkins C.J., Eaton, J.K., Fluid flow and scalar transport through porous fins, Physics of Fluids, 26(5):(055104)1-24, 2014. Link

  • Tachikawa H., Schiavazzi D.E., Arima T. and Iaccarino G., Robust optimization for windmill airfoil design under variable wind conditions, Honda R&D Technical Review, 26(1):160-165, 2014. Link

  • Schiavazzi D.E., Doostan A. and Iaccarino G., Sparse multiresolution stochastic approximation for uncertainty quantification, Recent Advances in Scientific Computing and Applications, 586:295-303, AMS 2013. Link

Technical Reports:

  • Tachikawa H., Schiavazzi D.E., Arima T. and Iaccarino G., Robust optimization for windmill airfoil design under variable wind conditions, Proceedings of the 2012 CTR Summer Program, Stanford University. Link

  • Lucor D., Witteveen, J., Constantine, P., Schiavazzi D.E., and Iaccarino G., Comparison of adaptive uncertainty quantification approaches for shock wave-dominated flows, Proceedings of the 2012 CTR Summer Program, Stanford University. Link

  • Schiavazzi D.E., Doostan A. and Iaccarino G., A Sparse Multiresolution Stochastic approximation for uncertainty quantification, CTR Research Briefs 2012, Stanford University. Link

  • Schiavazzi D.E., Coletti F., Iaccarino G. and Eaton J.K., A matching pursuit approach to solenoidal filtering of three-dimensional velocity measurements, CTR Research Briefs 2012, Stanford University. Link

Conference/Seminar Presentations:

2021
  • Wang Y., Liu F. and Schiavazzi D.E., Adaptive Surrogate Autoregressive Flow for Parameter Estimation with Expensive Computational Models, 16th US National Congress of Computational Mechanics (online), July 25-29 2021, Chicago, Illinois, USA.

  • Schiavazzi D.E., Perspective Talk: New trends in stochastic cardiovascular modeling, 26th Virtual Congress of the European Society of Biomechanics, July 13 2021, Politecnico di Milano, Italy.

  • Hensley Partin L., Sing-Long Collao C.A., Schiavazzi D.E., Noise in 4D flow MRI velocities from undersampled acquisition sequences: characterization and use in machine learning, UNCECOMP 2021 online, June 29 2021, Athens, Greece.

  • Li X., Schiavazzi D.E., A Scalable Ensemble Solver for Uncertain High-Fidelity Cardiovascular Models abstract, SIAM CSE 2021 online, March 3, 2021.

2020
  • Kurihara D., Sakaue H., Blois G. and Schiavazzi D.E., Deep optical flow for experimental fluid dynamics: sensitivity to network training , 73rd Annual Meeting of the APS Division of Fluid Dynamics, online, November 24, 2020.

  • Li X. and Schiavazzi D.E., A Scalable Explicit Finite Element Solver for Cardiovascular Models with Uncertain Material Properties, SIAM PP20, Seattle, WA, USA, Febrary 12, 2020.

  • Schiavazzi D.E., Juliano T.J., Bayesian Network Inference of Thermal Protection System Failure in Hypersonic Vehicles, AIAA Scitech 2020 Forum, 6-10 January 2020, Orlando, Florida, USA.

2019
  • Schiavazzi D.E., Quantifying the uncertainty in cardiovascular digital twins through model reduction, Bayesian inference and propagation using model ensembles, Seminario de Ingenieria Matematica y Computacional, Pontificia Universidad Catolica de Chile, Santiago, Chile, November 27, 2018.

  • Seo J., Schiavazzi D.E., Kahn A.M., Marsden A.L., Forward uncertainty propagation in a patient-specific cardiovascular model with fluid-structure interaction, 6th International Conference on Computational and Mathematical Biomedical Engineering - CMBE2019, 10-12 June 2019, Tohoku University, Katahira Campus, Sendai City, Japan.

  • Li X., Schiavazzi D.E., Explicit Solution of Cardiovascular Model Ensembles with Random Field Material Properties, FEF19, Chicago, IL, USA, March 31 - April 3, 2019.

  • Breckling S.R., Juliano T.J., Schiavazzi D.E., Characterising Failure in Hypersonic Vehicles using Unified Bayesian Networks, SIAM CSE, Spokane, WA, USA, February 25 - March 1, 2019.

  • Harrod K., Marsden A.L., Schiavazzi D.E., Data Assimilation on Lumped Parameter Models for Diastolic Heart Failure, SIAM CSE, Spokane, WA, USA, February 25 - March 1, 2019.

  • Fleeter C.M., Geraci G., Schiavazzi D.E., Kahn A.M., Marsden A.L., Multilevel Multifidelity Approaches for Uncertainty Quantification in Cardiovascular Modeling, SIAM CSE, Spokane, WA, USA, February 25 - March 1, 2019.

  • Fleeter C.M., Schiavazzi D.E., Marsden A.L., Multi-fidelity UQ Strategies, Thermal \& Fluid Sciences Affiliates and Sponsors Conference, Stanford University, CA, USA, February 5-6, 2019.

  • Seo J., Schiavazzi D.E., Kahn A.M., Marsden A.L., \textit{Uncertainty quantification in patient-specific cardiovascular simulations}, Thermal \& Fluid Sciences Affiliates and Sponsors Conference, Stanford University, CA, USA, February 5-6, 2019.

2018
  • Schiavazzi D.E., Quantifying the uncertainty in cardiovascular digital twins through model reduction, Bayesian inference and propagation using model ensembles, LANS Informal Seminar, Argonne National Laboratory, November 13, 2018.

  • Seo J., Schiavazzi D.E., Marsden A., Uncertainty Quantification Methodologies and Linear Solvers in Cardiovascular Simulations in High-performance Computing, 13th World Congress on Computational Mechanics, Jul. 22-27, New York, NY, 2018.

  • Akintunde A.R., Miller K.S., Schiavazzi D.E., Constitutive modeling for tendon aging and healing under uncertain uniaxial stress-stretch response, WCB18, July 8-12, Dublin, Ireland, 2018.

  • Schiavazzi D.E., Fleeter C.M., Geraci G., Marsden A.L., Multifidelity Approaches for Cardiovascular Hemodynamics, ECCM ECFD, June 11-15, Glasgow, Scotland, 2018.

  • Tran J., Schiavazzi D.E., Marsden A.L., Stochastic Sub-modeling under Heterogeneous Input Uncertainty with Application to Coronary Artery Disease, SIAM UQ18, April 16-19, Gardern Cove, California, 2018.

  • Seo J., Schiavazzi D.E., Marsden A., Performance of linear solvers and preconditioning techniques in cardiovascular simulations in high-performance computing, ICME CME300 First Year Seminar Series, Apr. 17, Stanford, CA, 2018.

  • Tran, J., Schiavazzi, D.E., Ramachandra, A., Kahn, A., Marsden, A., Uncertainty Quantification in blood flow simulations of coronary bypass graft surgery, Thermal and Fluid Sciences Affiliates and Sponsors Program, Feb. 1-2, Stanford, CA, 2018.

  • Tran, J., Schiavazzi, D.E., Ramachandra, A., Kahn, A., Marsden, A., Uncertainty Quantification in Cardiovascular Simulations, Stanford ICME 300 First Year Seminar Series, Jan. 23, Stanford, CA, 2018.

2017
  • Schiavazzi D.E., Stochastic Cardiovascular Modeling: Possibilities and Challenges, Bio/Applied Mathematics Seminar, IUPUI, December 8, 2017.

  • Tran J., Schiavazzi D.E., Bangalore Ramachandra A., Kahn A., Marsden A., Uncertainty Quantification in Multi-scale Simulations of Coronary Artery Bypass Grafts, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, Denver, Colorado, 2017.

  • Seo J., Schiavazzi D.E., Marsden A., Performance of uncertainty quantification methodologies and linear solvers in cardiovascular simulations, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, Denver, Colorado, 2017.

  • Fleeter C., Geraci G., Schiavazzi D.E., Kahn A., Marsden A., Multi-Fidelity Uncertainty Propagation for Cardiovascular Modeling, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, Denver, Colorado, 2017.

  • Schiavazzi D.E., Amili O., Coletti F., 4D pressure MRI: validation through in-vitro experiments and simulations, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, Denver, Colorado, 2017.

  • Fleeter C.M., Schiavazzi D.E., Marsden A.L., Towards a Multi-Fidelity Hemodynamic Model Pipeline for the Analysis of Cardiovascular Flow Under Uncertainty, USNCCM14, June 19, Montreal, Canada, 2017.

  • Tran J.S., Schiavazzi D.E., Bangalore Ramachandra A., Kahn A.M., Marsden A.L., Uncertainty Quantification in Multi-Scale Simulations of Coronary Artery Bypass Grafts using Multi-Resolution Expansion, USNCCM14, June 19, Montreal, Canada, 2017.

  • Schiavazzi D.E., Tutorials and Examples of UQ/SA in Cardiovascular Modeling, Berkeley-NTNU UQ-SA Workshop, June 28, University of California, Berkeley, CA, 2017.

  • Tran, J., Schiavazzi, D.E., Ramachandra, A., Kahn, A., Marsden, A., Uncertainty Quantification in Multi-scale Simulations of Coronary Artery Bypass Grafts, Summer Biomechanics, Bioengineering, and Biotransport Conference, June 21-24, Tucson, AZ, 2017.

  • Schiavazzi D.E., Stochastic Cardiovascular Modeling: Possibilities and Challenges, Computer Science Research Institute Seminar, Sandia National Laboratories, June 1, Albuquerque, NM, 2017.

  • Schiavazzi D.E., Tran J. and Marsden A., Stochastic Multiscale Cardiovascular Modeling under Combined Boundary Condition and Material Property Uncertainty, CMBE17, April 10-12, Pittsburgh, PA, 2017.

  • Schiavazzi D.E., A Generalized Multi-resolution Expansion for Uncertainty Propagation with Application to Cardiovascular Modeling, Workshop on Uncertainty Quantification and Data-Driven Modeling, March 23-24, UT Austin, TX, 2017.

  • Schiavazzi D.E., Measurement Noise Reduction and Uncertainty Quantification for Predictive Simulation in Cardiovascular Flow, AME Department Seminar, February 7, University of Notre Dame, IN, 2017.

  • Schiavazzi D.E., Circuit Analogy in Cardiovascular Hemodynamics: Formulation, Identifiability & Clinical Data Assimilation for Personalized Medicine, Solid State Seminar (S3) Series, EE Department, February 3, University of Notre Dame, IN, 2017.

2016
  • Schiavazzi D.E., Measurement Noise Reduction and Uncertainty Quantification for Predictive Simulation in Cardiovascular Flow, Mechanical Engineering Department Seminar, December 1, Purdue University, IN, 2016.

  • Schiavazzi D.E., Tran J. and Marsden A., Stochastic Multiscale Modeling for Cardiovascular Flow, WCCM16, July 28, Seoul, South Korea, 2016.

  • Schiavazzi D.E., Tran J. and Marsden A., Assimilation of Patient Data in Circulation Networks for Precision Medicine in Adults and Children, SIAM Conference on Life Sciences, July 14, Boston, MA, 2016.

  • Schiavazzi D.E., Noise Reduction and Uncertainty Quantification for Predictive Cardiovascular Flow Simulation, Fluid Dynamics Seminar, April 26, Stanford University, Stanford, 2016.

  • Schiavazzi D.E., Marsden A.L., Assimilation and Propagation of Clinical Data Uncertainty in Cardiovascular Modeling, SIAM UQ16, April 6, EPFL, Switzerland, 2016.

  • Schiavazzi D.E., Marsden A.L., Data Assimilation and Propagation of Uncertainty in Multiscale Cardiovascular Simulation, TFSA16, February 4, Stanford University, Stanford, 2016.

2015
  • Schiavazzi D.E., Assimilation and Propagation of Clinical Data Uncertainty in Cardiovascular Modeling, Bay Area Scientific Computing Day, December 11, Berkeley Lab, Berkeley, 2015.

  • Schiavazzi D.E., Marsden A.L., Data Assimilation and Propagation of Uncertainty in Multiscale Cardiovascular Simulation, 68th Annual Meeting of the APS Division of Fluid Dynamics, November 22-24, Boston, 2015.

  • Tran J., Schiavazzi D.E., Ramachandra A. B., Kahn A., Marsden A.L., Automated Tuning for Parameter Identification in Multi-Scale Coronary Simulations, 68th Annual Meeting of the APS Division of Fluid Dynamics, November 22-24, Boston, 2015.

  • Lan H., Merkow J., Updegrove A., Schiavazzi D.E., Wilson N., Shadden S., Marsden A.L., SimVascular 2.0: an Integrated Open Source Pipeline for Image-Based Cardiovascular Modeling and Simulation, 68th Annual Meeting of the APS Division of Fluid Dynamics, November 22-24, Boston, 2015.

  • Schiavazzi D.E., Assimilation and propagation of clinical data uncertainty in cardiovascular modeling, ACMS Colloquium, November 18, Notre Dame University, 2015.

  • Schiavazzi D.E., Assimilation and Propagation of Clinical Data Uncertainty In Cardiovascular Modeling, CME 500 Departmental Seminar, November 2, Stanford University, 2015.

  • Schiavazzi D.E., Hsia T.Y. and Marsden A.L., On pressure-flow condensation in cardiovascular modeling, Computational Fluid Dynamics in Medicine and Biology II, August 30-September 4, Albufeira, Portugal, 2015.

  • Schiavazzi D.E., Tran J.S., Ramachandra A.B., Hsia T.Y. and Marsden A.L., Clinical Data-Aware Uncertainty Analysis of Multiscale Cardiovascular Models, USNCCM13, July 26-30, San Diego, 2015.

  • Tran J., Schiavazzi D.E., Ramachandra A., Kahn A. and Marsden A.L., Automated tuning for parameter identification in multi-scale coronary simulations, USNCCM13, July 26-30, San Diego, 2015.

  • Schiavazzi D.E., Tran J.S., Bangalore Ramachandra A., Hsia T.Y., Marsden A.L., Data-aware Uncertainty Analysis Of Multiscale Cardiovascular Models, Society for Mathematical Biology 2015 Conference, June 30 - July 3, Atlanta, GA, USA, 2015.

  • Schiavazzi D.E., Doostan A. and Iaccarino G., A sparse multiresolution regression framework for uncertainty quantification, SIAM Conference on Computational Science and Engineering (CSE15), March 14-18, Salt Lake City, UT, USA, 2015.

  • Lan H., Wilson N.M., Schiavazzi D.E., Merkow J., Updegrove A., Shadden S.C. and Marsden A.L., SimVascular 2.0: an open source pipeline for cardiovascular modeling and simulation, The 9th Southern California Flow Physics Symposium (So Cal Fluids IX), April 18, SDSU, 2015.

  • Schiavazzi D.E., Tran J.S., Bangalore Ramachandra A., Hsia T.Y., Marsden A. L., Combining data assimilation and stochastic propagation in multiscale cardiovascular modelling, The 9th Southern California Flow Physics Symposium (So Cal Fluids IX), April 18, SDSU, 2015.

  • Tran J.S., Schiavazzi D.E., Bangalore Ramachandra A., Kahn A.M. and Marsden A.L., Automatic tuning for parameter identification in multi-scale coronary simulations, The 9th Southern California Flow Physics Symposium (So Cal Fluids IX), April 18, SDSU, 2015.

2014
  • Updegrove D., Merkow J., Schiavazzi D.E., Wilson N., Marsden A. and Shadden S., Development of an Open Source Image-Based Flow Modeling Software - SimVascular, 67th Annual Meeting of the APS Division of Fluid Dynamics, November 23-25, San Francisco, 2014.

  • Tran J., Schiavazzi D.E., Bangalore Ramachandra A., Kahn A. and Marsden A.L., Automated tuning for parameter identification in multiscale coronary simulations, 67th Annual Meeting of the APS Division of Fluid Dynamics, November 23-25, San Francisco, 2014.

  • Schiavazzi D.E. and Marsden A., Uncertainty quantification in virtual surgery predictions for single ventricle palliation, 67th Annual Meeting of the APS Division of Fluid Dynamics, November 23-25, San Francisco, 2014.

  • Schiavazzi D.E. and Coletti F., Solenoidal filtering of three-dimensional velocity measurements using vortex frames, The 8th Southern California Flow Physics Symposium (So Cal Fluids VIII), April 12,UCLA, 2014.

2013
  • Schiavazzi D.E., Doostan A. and Iaccarino G., Sparse multiresolution regression for uncertainty propagation, BOQUSE 2013, International workshop on Uncertainty Quantification in fluids Simulation, December 16-18, Bordeaux, France, 2013.

  • Schiavazzi D.E., Kung E., Dorfman A., Hsia T.Y., Baretta A., Arbia G. and Marsden A.L., Hemodynamic consequences of LPA stenosis in single ventricle stage 2 LPN circulation with automatic registration, 66th Annual Meeting of the APS Division of Fluid Dynamics, November 24–26, Pittsburgh, 2013.

  • Banko A., Coletti F., Schiavazzi D.E., Elkins C.J. and Eaton J.K., Steady Flow in Subject-Specific Human Airways from Mouth to Sixth Bronchial Generation, 66th Annual Meeting of the APS Division of Fluid Dynamics, November 24–26, Pittsburgh, 2013.

  • Schiavazzi D.E., Coletti F., Bodart J. and Eaton J.K., Divergence-free filtering and pressure determination from 3D velocimetry: applications to flows of industrial and biomedical relevance, 66th Annual Meeting of the APS Division of Fluid Dynamics, November 24–26, Pittsburgh, 2013.

  • Schiavazzi D.E. and Marsden A.L., A mesh morphing approach to patient-specific model parameterization for human circulation, 14th UC Systemwide Bioengeneering Symposium, June 19-21, UC San Diego, 2013.

Other Pubblications:

  • Perillo M., Schiavazzi D.E., Primavera V. and Sacchi D., Virtual prototyping for safer product development: integrated marine propulsion and steering system example, 12th International LS-DYNA Conference, 3-5 June 2012, Detroit, USA.

  • Cucino P., Fanti D., Omizzolo, A. and Schiavazzi D.E., A finite element insight on reinforced concrete tunnels under fire conditions, Handling Exceptions in Structural Engineering, Ed. 2010, Universit'a di Roma "La Sapienza". Link

  • Garcia Lorente F., Lovison A., and Schiavazzi D.E., Flutter of long-span suspended bridges: a numerical investigation, Thesis, Universidad de Sevilla.

  • Locardi P. and Schiavazzi D.E., Expert system for the optimization of bridge orthotropic deck plates, Thesis, Universita' degli Studi di Padova.

  • Furlan L. and Schiavazzi D.E., The Calatrava bridge in Reggio Emilia. From numerical simulation to construction.