Andreas Mang

Andreas Mang is an Associate Professor at the Department of Mathematics of the University of Houston. He received his PhD from the University of Luebeck (DE) in 2013. Subsequently, he joined the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin (US) in 2013 for a postdoctoral fellowship. In 2017, he joined the Department of Mathematics at the University of Houston (US), where he currently holds a position as an Associate Professor of Mathematics. His research interests include statistical and deterministic inverse problems, nonlinear optimal control, numerical optimization, data-enabled sciences, and parallel scientific computing. He works on the design, analysis, and deployment of effective numerical methods and parallel algorithms that deliver optimal performance and scale on high-performance computing platforms. In 2022, he received the NSF CAREER award.

• Principled computational methods informed by Riemannian geometry. Rice University, Houston, TX, 2026.
• Principled algorithms for model- and data-driven discovery. HPE Data Science Institute, University of Houston, 2026.
• Tensor-based surrogate models for digital twin applications in brain cancer dynamics. JMM26, Washington, DC, 2026.
• Scalable and principled algorithms for scientific computing and data-enabled discovery. Tufts University, Medford, MA, 2025.
• Fast algorithms for inverse transport problems. Texas Tech University, Lubbock, TX, 2025.
• A generalized alternating nonlinear GMRES acceleration method. SIAM TX-LA, UT Austin, 2025.
• Numerical methods for PDE-based diffeomorphic image registration. SIAM AN25, Montreal, CA, 2025.
• CLAIRE: Constrained large deformation diffeomorphic image registration. ICCOPT, USC, Los Angeles, CA, 2025.
• Data- and model-driven approaches for solving inverse problems. SciML Summer School, Texas A&M, 2025.
• Bayesian inference for large scale inverse problems governed by hyperbolic dynamical systems. SIAM CSE25, Fort Worth, TX, 2025.
• Efficient numerical methods for inverse problems governed by transport equations. DTE & AICOMAS, Paris, FR, 2025.
• Deep learning for Bayesian inverse problems governed by nonlinear ODEs. SIAM MDS24, Atlanta, GA, 2024.
• Fast iterative methods for large-scale initial value control problems. SIAM TX-LA, Baylor University, Waco, TX, 2024.
• Fast iterative methods for large-scale initial value control problems. MOPTA, Lehigh University, Bethlehem, PA, 2024.
• Efficient numerical schemes for uncertainty quantification in diffeomorphic image registration. CMBE24, Arlington, VA, 2024.
• CLAIRE: Scalable algorithms for diffeomorphic image registration. SIAM IS24, Atlanta, GA, 2024.
• Fast iterative solvers for initial value control problems. INFORMS Optimization Society Conference, Rice University, Houston, TX, 2024.
• CLAIRE: Scalable algorithms for diffeomorphic image registration. SIAM UQ24, Trieste, IT, 2024.
• Efficient algorithms for inverse problems governed by dynamical systems. University of Houston (host: K. B. Nakshatrala), 2023.
• Fast algorithms for nonlinear optimal control of geodesic flows of diffeomorphisms. USNCCM7, Albuquerque, NM, 2023.
• Shape classification through the lens of geodesic flows of diffeomorphisms. BIRS Workshop, BC, CA, 2023.
• Scalable algorithms for inverse problems governed by dynamical systems. HPE Data Science Institute, UH, 2023.
• Deep neural networks for Bayesian inverse problems governed by nonlinear ODEs. INdAM Workshop, Rome, IT, 2023.
• Fast algorithms for PDE-constrained optimization under uncertainty. SIAM OP23, Seattle, US, 2023.
• Efficient numerical methods for optimal control problems governed by geodesic flows of diffeomorphisms. Virginia Tech (host: J. Rudi), 2023.
• Efficient numerical methods for optimal control problems governed by geodesic flows of diffeomorphisms. Texas A&M, CAMDA (host: S. Foucart), 2023.
• Fast algorithms for optimal control problems governed by geodesic flows of diffeomorphisms. University of Kansas (host: S. Shontz), 2023.
• Numerical methods for PDE-constrained optimization problems governed by hyperbolic equations. University of Puerto Rico, Mayaguez (host: J. R. Romero), 2023.
• Fast algorithms for inverse problems governed by transport equations. AMS Southeastern Sectional, Atlanta, GA, 2023.
• CLAIRE: Scalable multi-GPU algorithms for diffeomorphic image registration in 3D. NIST, Boulder, CO (host: G. Dogan), 2023.
• Deep learning for Bayesian inverse problems governed by nonlinear differential equations. SIAM CSE23, Amsterdam, NL, 2023.
• Scalable algorithms for diffeomorphic image registration. Dagstuhl Seminar, Wadern, DE, 2023.
• CLAIRE: Scalable multi-GPU algorithms for diffeomorphic image registration. JMM23, Boston, MA, 2023.
• Fast algorithms for nonlinear optimal control of geodesic flows of diffeomorphisms. George Mason University (host: H. Antil), 2022.
• Fast algorithms for diffeomorphic image registration. SIAM TX-LA, Houston, TX, 2022.
• Randomized algorithms for efficient preconditioning and uncertainty quantification in inverse transport problems. SIAM MDS22, San Diego, CA, 2022.
• Fast algorithms for initial value control problems in diffeomorphic registration. Copper Mountain Conference, 2022.
• Fast algorithms for initial value control problems. SIAM IS22, 2022.
• CLAIRE: Scalable multi-GPU algorithms for diffeomorphic registration in 3D. SIAM OP21, 2021.
• Uncertainty quantification in diffeomorphic image registration. SIAM AN21, 2021.
• Uncertainty quantification for inverse transport problems. SIAM CSE21, 2021.
• Fast algorithms for nonlinear optimal control of geodesic flows of diffeomorphisms. Oden Seminar, UT Austin (host: T. Bui-Thanh), 2021.
• Statistical analysis of shapes and shape deformations in 3D. JMM, 2021.
• Classification of 3D shapes and shape deformations. SIAM TX-LA, 2020.
• Fast GPU-accelerated diffeomorphic image registration in 3D. SIAM IS20, 2020.
• Automatic classification of 3D shapes and shape deformations. SIAM MDS20, 2020.
• Estimating oncogenic parameters via biophysical brain tumor growth modeling. Society for Neuro-Oncology, Phoenix, AZ, 2019.
• Fast GPU-accelerated diffeomorphic image registration in 3D. SIAM TX-LA, SMU, Dallas, TX, 2019.
• Fast algorithms for nonlinear optimal control for diffeomorphic registration. RICAM Workshop, Linz, AT, 2019.
• Uncertainty quantification in nonlinear optimal control problems for diffeomorphic registration. AMS Sectional, UW-Madison, 2019.
• Fast algorithms for nonlinear optimal control for diffeomorphic registration. University of Twente, NL (host: C. Brune), 2019.
• Fast diffeomorphic image registration in 3D. ICIAM, Valencia, ES, 2019.
• Fast algorithms for initial value control problems in diffeomorphic image registration. AIP Conference, Grenoble, FR, 2019.
• Diffeomorphic shape matching: Fast algorithms for non-linear optimal control problems. ENS Paris-Saclay, Cachan, FR, 2019.
• Optimal control of PDEs: Application to brain tumor modeling. AMS Southeastern Sectional, U of Arkansas, 2018.
• Fast algorithms for inverse transport problems. SIAM Annual Meeting, Portland, OR, 2018.
• CLAIRE: A parallel solver for constrained diffeomorphic image registration. Mint Medical GmbH, Heidelberg, DE, 2018.
• Parallel algorithms for hyperbolic PDE-constrained optimization problems. PMAA, ETH Zurich, 2018.
• CLAIRE: A parallel solver for constrained large deformation diffeomorphic image registration. U of Stuttgart (host: M. Schulte), 2018.
• CLAIRE: A parallel solver for constrained large deformation diffeomorphic image registration. SIAM IS, Bologna, IT, 2018.
• Computational mathematics meets medicine: Formulations, numerics, and parallel computing. Emory University (host: J. Nagy), 2018.
• CLAIRE: A distributed-memory solver for constrained diffeomorphic image registration. Rice University (host: J. Chan), 2018.
• Parallel algorithms for optimal control based diffeomorphic image registration. SIAM Houston Imaging Sciences Symposium, 2017.
• Preconditioners for the reduced space Hessian in hyperbolic optimal control problems. Preconditioning Conference, Vancouver, CA, 2017.
• A distributed-memory Newton-Krylov solver for inverse transport problems. USNCCM, Montreal, CA, 2017.
• A distributed-memory Newton-Krylov solver for constrained diffeomorphic image registration. AIP Conference, Hangzhou, CN, 2017.
• Parallel algorithms for PDE-constrained optimization problems with hyperbolic constraints. SIAM CSE, Atlanta, GA, 2017.
• PDE-constrained optimization and high-performance computing meets medicine. University of Houston (host: K. Josic), 2016.
• A parallel solver for inverse transport problems. Emory University (host: L. Ruthotto), 2016.
• Fast solvers for constrained diffeomorphic image registration. SIAM IS, Albuquerque, NM, 2016.
• Fast algorithms for diffeomorphic image registration. OCIP Workshop, TU Munich, 2016.
• Efficient evaluation of Hessian operators arising in large-scale inverse transport problems. SIAM UQ, Lausanne, CH, 2016.
• Numerical simulation and optimization in medical imaging. University of Hamburg (host: A. Iske), 2015.
• Efficient algorithms for optimal control based diffeomorphic image registration. OCIP Workshop, TU Munich, 2015.
• Efficient algorithms for physically constrained diffeomorphic image registration. SIAM CSE, Salt Lake City, UT, 2015.
• Optimal control meets medical imaging sciences. TU Munich (host: B. Menze), 2015.
• Efficient algorithms for inverse transport problems. U of Luebeck (host: T. M. Buzug), 2014.
• Computational tools in neuroimaging. SIEMENS Molecular Imaging, Oxford, UK, 2012.
• Personalised image-based modelling of brain tumour progression. UMC Hamburg-Eppendorf, 2012.
• Image-based modeling of brain tumour progression. SIAM IS, Philadelphia, PA, 2012.
• Image-based modelling of tumor growth. University of Luebeck (host: J. Modersitzki), 2011.
• From image registration to bio-physical modelling. University of Applied Sciences Kiel, DE, 2010.
• A mathematical toolbox for the description of brain cancer dynamics. DKFZ, Heidelberg, DE, 2010.
• Image registration with application to neuroradiology. University of Luebeck, DE, 2008.
• Image registration with application to brain tumour imaging. University of Luebeck (host: B. Fischer), 2007.
• Analysis of brain tumour growth via non-parametric non-rigid image registration. Philips Research Europe, Hamburg, DE, 2007.