Ece.rice.edu

• Large-scale optimization for “big data” systems, machine learning, and image processing Software Engineering & Scientific Computing • Parallel and distributed computing, GPU accelerated algorithms, programmable • MRI and CT image reconstruction, quantitative perfusion imaging, PDE-based segmentation and registration, image-guided radiation therapy planning • PDE-based segmentation, registration, object identification Numerical Partial Differential Equations: • Multigrid methods, non-linear finite elements • Thesis Topic: Numerical Methods for 1 Minimization• Advisor: Professor Stanley Osher• Emphasis: Numerical optimization Department of Electrical & Computer EngineeringRice University • Advisor: Richard Baraniuk• Group: Digital Signal Processing• Emphasis: Optimization and image processing Department of Electrical EngineeringStanford University • Advisor: Stephen Boyd• Group: Information Systems Laboratory• Emphasis: Large scale distributed and parallel optimization • Awarded to one person every two years by the Society for Industrial and Applied Mathematics (SIAM) for outstanding research in applied mathematics Thomson Reuters Essential Science Indicators • Hot new paper in computer science: “The Split Bregman Method for 1 Regularized Problems,” Siam Journal on Imaging Sciences • This award recognizes highly cited work (over 1000 citations) • Mathematical Sciences Postdoctoral Research Fellowship• Graduate Research Fellowship • Developed real-time reconstruction algorithms for coded aperture digital cameras• Developed optimized implementations of image processing codes in C++ and • Designed prototype algorithms to be ported to FPGA Algorithm Design and Data Analysis Consultant • Developed new algorithms for the analysis of flow cytometry data• Designed regression methods to be compatible with hardware specific noise models • Performed data analysis and statistical consulting for Malinkrodt Institute for • Developed and maintained Perfusion Imaging Toolkit • Developed software tools for Monte Carlo simulation and uncertainty quantification Goldstein T, Esser E, Baraniuk R. “Adaptive Primal Dual Optimization for Image Advances in Neural Information Processing Systems Hueper K, Parikh MA, Prince MR, Schoenfeld C, Liu C, Bluemke DA, Dashnaw SM, Goldstein TA, Hoffman EA, Lima JA, Skrok J, Zheng J, Barr RG, Vogel-Claussen J.
“Quantitative and Semiquantitative Measures of Regional Pulmonary MicrovascularPerfusion by Magnetic Resonance Imaging and their Relationships to Global LungPerfusion and Lung Diffusing Capacity: the Multiethnic Study of AtherosclerosisChronic Obstructive Pulmonary Disease Study.” Investigative Radiology, 48(4):223-30 (2013).
Ayremlou A, Calderon D, Goldstein T. “Adaptive Step Size Selection for Optimization via the Ski Rental Problem.” IEEE International Conference on Acoustics, Speechand Signal Processing (ICASSP) (2013).
Goldstein T, Bresson X, Osher S. “Global Minimization of Markov Random Fields with Applications to Optical Flow.” Inverse Problems in Imaging, 6(4):623-644 (2012) Kim H, Li R, Lee R, Goldstein T, Boyd S, Candes E, Xing L. “Dose Optimization with First-Order Total-Variation Minimization for Dense Angularly Sampled and SparseIntensity Modulated Radiation Therapy (DASSIM-RT).” Medical Physics 39(7):4316-27 (2012).
Hueper K, Zapf A, Skrok J, Pinheiro A, Goldstein T, Zheng J, Zimmerman SL, Kamel I, Abraham R, Wacker F, Bluemke DA, Abraham T, Vogel-Claussen J. “In HypertrophicCardiomyopathy Reduction of Relative Resting Myocardial Blood Flow is Relatedto Late Enhancement, T2-Signal and LV Wall Thickness.” PLoS One, 7(7):e41974(2012).
Mohler G, Bertozzi A, Goldstein T, Osher S. “Fast TV Regularization for 2D Maximum Penalized Likelihood Estimation.” Graphical Statistics, 20(2): 479-491 (2011).
Vogel-Claussen J, Skrok J, Shehata ML, Singh S, Sibley CT, Boyce DM, Lechtzin N, Girgis RE, Mathai SC, Goldstein TA, Zheng J, Lima JA, Bluemke DA, HassounPM. “Right and Left Ventricular Myocardial Perfusion Reserves Correlate with RightVentricular Function and Pulmonary Hemodynamics in Patients with PulmonaryArterial Hypertension.” Radiology. 258(1):119-27 (2011).
Goldstein T, Bresson X, Osher S. “Geometric Applications of the Split Bregman Segmentation and Surface Reconstruction.” McCommis KS, Goldstein T, Abendschein DR, Herrero P, Misselwitz B., Gropler RJ, Zheng J. “Quantification of Regional Myocardial Oxygenation by MagneticResonance Imaging: Validation with Positron Emission Tomography.” Circulation:Cardiovascular Imaging, 3(1):41-6 (2010).
McCommis KS, Koktzoglou I, Zhang H, Goldstein TA, Northrup BE, Li D, Gropler RJ, Zheng J. “Improvement of Hyperemic Myocardial Oxygen Extraction FractionEstimation by a Diffusion-Prepared Sequence.” Magnetic Resonance in Medicine,63(6):1675-82 (2010).
McCommis KS, Goldstein TA, Abendschein DR, Misselwitz B, Pilgram T, Gropler RJ, Zheng J. “Roles of Myocardial Blood Volume and Flow in Coronary Artery Disease:an Experimental MRI Study at Rest and During Hyperemia.” Eur Radiol, 20(8):2005-12 (2010).
Goldstein T, Osher S. “The Split Bregman Method for 1 Regularized Problems.” SIAM Journal on Imaging Sciences, 2(2): 323–343 (2009).
McCommis KS, Zhang H, Goldstein TA, Misselwitz B, Abendschein DR, Gropler RJ, Zheng J. “Myocardial Blood Volume is Associated with Myocardial OxygenConsumption: an Experimental Study with Cardiac Magnetic Resonance in a CanineModel.” JACC Cardiovasc Imaging. 2(11):1313-20 (2009).
Goldstein T, Jerosch-Herold M, Misselwitz B, Zhang H, Gropler R, Zheng J. “Fast Mapping of Myocardial Blood Flow with MR First-Pass Perfusion Imaging.”Magnetic Resonance in Medicine, 59(6):1394-400 (2008).
McCommis KS, Goldstein TA, Zhang H, Misselwitz B, Gropler RJ, Zheng J.
“Quantification of Myocardial Blood Volume During Dipyridamole and DoubtamineStress: a Perfusion CMR Study.” J Cardiovasc Magn Reson, 9(5):785-92 (2007).
Goldstein T, Zhang H, Jerosch-Herold M, Gropler R, Zheng J. “Improvement of Quantification of Myocardial First-Pass Perfusion Mapping: A Temporal and SpatialWavelet Denoising Method.” Magnetic Resonance in Medicine, 56(2):439-45 (2006).
Goldstein T, Xu L, Kelly K, Baraniuk R. “The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video.” Goldstein T, Esser E, Baraniuk R. “Adaptive Primal-Dual Hybrid Gradient Methods for Saddle-Point Problems.” SIAM Journal of Imaging. Submitted 2013.
Ayremlou A, Goldstein T, Veeraraghavan A.“Fast Sublinear Sparse Representations using Shallow Tree Matching Pursuit.” Computer Vision and Pattern Recognition(CVPR). Submitted 2013.
Goldstein T, Studer C, Baraniuk R. “Efficient Computation of Democratic Representations For Peak-Ro-Average Power Ratio Reduction.” 2014 IEEE International Conferenceon Acoustics, Speech and Signal Processing (ICASSP). Submitted 2014.
Cantarero A, Goldstein T, Teran J. “A Fast Method for Interface and Parameter Estimation in Linear Elliptic PDEs with Piecewise Constant Coefficients.” InverseProblems in Imaging. Submitted 2013.
Goldstein T, N, Brendan O’Donogue, Setzer S, Baraniuk R. “Fast Alternating Direction Optimization Methods.” SIMA Journal of Imaging. Submitted 2012.
Goldstein T, Setzer S. “High-Order Methods for Sparse Signal Recovery.” Problems in Imaging. Submitted 2012.
Goldstein T, Jacobson J. “A Multilevel Decomposition Method for Sparse Signal Recovery in a Fourier Basis.” IEEE Transactions on Image Processing. Submitted 2012.
• SIAM Journal of Imaging Sciences• SIAM Journal on Optimization (SIOPT)• IEEE Transactions on Signal Processing• IEEE Transactions on Geoscience and Remote Sensing• IEEE Signal Processing Letters• AIMS Inverse Problems in Imaging• Magnetic Resonance in Medicine• Image Processing Online (IPOL)• Springer Journal of Mathematical Programming Goldstein T. Fast Alternating Direction Methods.
Mathematics (IPAM) program on Convex Relaxation Methods for Geometric Problemsin Scientific Computing (2013).
Goldstein T. Fast Alternating Direction Methods. Rice University Computational and Applied Mathematics Seminar Series (2013).
Goldstein T. Real-Time Compressive Video Using Coded Aperture Cameras. UCLA Electrical Engineering Seminar Series (2013).
Goldstein T. Accelerated Splitting Methods for L1 Institute for Digital Research and Education (IDRE) Workshop on Compressive Sensing (2012).
Goldstein T. Theory and Applications in MR Imaging of Compressive Sensing. American Association of Physicists in Medicine (AAPM) Lectures on Compressed Sensing inImage Reconstruction and Dose Optimization (2010).
Goldstein T. Fast Alternating Direction Methods.
Mathematics (IPAM) Workshop on Modern Trends in Optimization and Its Application(2010).
Goldstein T. What is Compressed Sensing? Institute for Pure and Applied Mathematics (IPAM) Workshop on Mathematical Problems, Models, and Methods in BiomedicalImaging (2010).
Goldstein T. Fast Alternating Direction Methods.
Mathematics (IPAM) Summer Program on Mathematics in Brain Imaging (2008).

Source: http://www.ece.rice.edu/~tag7/Tom_Goldstein/Welcome_files/TomGoldstein_cv.pdf