Michael E. Glinsky, PhD

... about

• live in Santa Fe, New Mexico, USA
• CEO of BNZ (Beyond Net Zero) Energy Inc. -- a disruptive investment company for the Energy Transition powered by qiTech (quantitative investment technology, supported by AI)

Bio

Focus is on the application of techniques that integrate decision science, deep learning, machine learning, artificial intelligence, data science and Bayesian data analysis to make better business decisions. This includes imbedding physical constraints into the deep learning and outputting of the critical uncertainties need to make the better decisions. Part of this work mandates doing large numbers of parallel computations on large computer clusters, significant Python programming, and software architectural design.

Michael E. Glinsky received a B.S. degree in physics from Case Western Reserve University in 1983 and a Ph.D. degree in physics from the University of California, San Diego in 1991. His doctoral research on magnetized pure electron plasmas was recognized by the American Physical Society as the outstanding thesis in the United States (1993 Simon Ramo Award). Before enrolling in graduate school as a National Science Foundation Graduate Fellow, he worked as a geophysicist for Shell Oil Company. After graduate school, he worked as a Department of Energy Distinguished Postdoctoral Research Fellow at Lawrence Livermore National Laboratory.

His 30 year career has focused on the use of data science, deep learning and Bayesian data analysis to make better business decisions; as a technology creator, strategic thinker, and leader at major companies and laboratories (such as Royal Dutch Shell, BHP Billiton, Halliburton, CSIRO, LLNL, and Sandia National Laboratories), and was an adjunct faculty member in the Physics Department at University of Western Australia. He received the top Australian scientific medal for his research on petroleum reservoir characterization in 2004.

To contact me

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Links

• Info
  • LinkedIn page
  • YouTube channel
  • short resume
  • full CV
  • BNZ bio
  • Google Scholar
  • Case Alumnus article (Fall 2020)
  • CSIRO EarthMatters interview (March 2010)
  • CSIRO Medal for Research Achievement video (for petroleum and CCUS reservoir characterization, 2004)
• Reviewed papers
  • A. J. Harvey-Thompson et al., “Development of a high performance MagLIF target platform using high aspect ratio coated liners and low-mix laser preheat,” Phys. Plasmas 31, 072711 (2024).
  • Z. Guo et al., “Noise-resilient deep learning for integrated circuit tomography,” Optics Express 31, 15355 (2023). (PDF)
  • M.E. Glinsky and K. Maupin, “Mallat Scattering Transformation based surrogate for Magnetohydrodynamics,” Computational Mechanics 72, 291 (2023). (PDF)
  • B.B. Pollock et al., “Experimental demonstration of >20 kJ laser energy coupling in 1-cm hydrocarbon-filled gas pipe targets via inverse Bremsstrahlung absorption with applications to MagLIF,” Phys. Plasmas 30, 022711 (2023).
  • P.F. Knapp et al., “Optimizing the configuration of plasma radiation detectors in the presence of uncertain instrument response and inadequate physics,” J. Plasma Phys. 89, 895890101 (2022).
  • O.F. Ogoke et al., “Deep-learned generators of porosity distributions produced during metal Additive Manufacturing,” Additive Manufacturing 60, 103250 (2022).
  • Z. Guo et al., “Physics-assisted Generative Adversarial Network for X-Ray Tomography,” Optics Express 30, 23238 (2022).
  • P.F. Knapp et al., “Estimation of Stagnation Performance Metrics in Magnetized Liner Inertial Fusion Experiments using Bayesian Data Assimilation,” Phys. Plasmas 29, 052711 (2022).
  • D.A. Yager-Elorriaga et al., "An overview of magneto-inertial fusion on the Z machine at Sandia National Laboratories,” Nucl. Fusion 62, 042015 (2022).
  • D.B. Sinars et al., “Review of pulsed power-driven high energy density physics research on Z at Sandia,” Phys. Plasmas 27, 070501 (2020).
  • A.J. Harvey-Thompson et al., “The effect of laser entrance hole foil thickness on MagLIF-relevant laser preheat,” Phys. Plasmas 27, 113301 (2020).
  • M.E. Glinsky et al., “Quantification of MagLIF morphology using the Mallat scattering transformation,” Phys. Plasmas 27, 112703 (2020).
  • M.R. Gomez et al., “Performance Scaling in Magnetized Liner Inertial Fusion Experiments,” Phys. Rev. Lett. 125, 155002 (2020).
  • M.R. Gomez et al., “Assessing stagnation conditions and identifying trends in Magnetized Liner Inertial Fusion,” IEEE Trans. Plasma 47, 2081 (2019).
  • A.J. Harvey-Thompson et al., "Constraining preheat energy deposition in MagLIF experiments with multi-frame shadowgraphy," Phys. Plasmas 26, 032707 (2019).
  • P.F. Knapp et al., "Origins and effects of mix on magnetized liner inertial fusion target performance," Phys. Fluids 26, 012704 (2019).
  • D.E. Ruiz, M.E. Glinsky, I.Y. Dodin, “Wave kinetic equation for inhomogeneous drift-wave turbulence beyond the quasilinear approximation,” J. Plasma Phys. 85, 905850101 (2019).
  • M. Geissel et al., “Minimizing scatter-losses during pre-heat for magneto-inertial fusion targets,” Phys. Plasmas 25, 022706 (2018).
  • S. A. Slutz et al., “Enhancing performance of magnetized liner inertial fusion at the Z facility," Phys. Plasmas 25, 122706 (2018).
  • A. J. Harvey-Thompson et al., “Diagnosing and mitigating laser preheat induced mix in MagLIF," Phys. Plasmas 25, 122705 (2018).
  • M.E. Glinsky, A. Cortis, J. Chen, D. Sassen, H. Rael, "Geomechanical property estimation of unconventional reservoirs using seismic data and rock physics," Geophysical Prospecting 63, 1224 (2015).
  • J. Chen, M.E. Glinsky, "Stochastic inversion of seismic PP and PS data for reservoir parameter estimation," Geophysics 79, R233 (2014).
  • D. Myer, S. Constable, K. Key, M.E. Glinsky, G. Lui, "Marine CSEM of the Scarborough gas field, Part 1: Experimental design and data uncertainty," Geophysics 77, E281 (2012).
  • M. Strauss, M.E. Glinsky, "Turbidity current flow over an erodible obstacle and phases of sediment wave generation," J. Geophys. Res. 117, C06007 (2012).
  • M.E. Glinsky, J. Gunning, "Understanding uncertainty in CSEM", World Oil 232, 57 (2011).
  • J. Gunning, M.E. Glinsky, J. Hedditch, "Resolution and uncertainty in 1D CSEM inversion: A Bayesian approach and open-source implementation", Geophysics 75, F151 (2010).
  • S.L. Byant, C. Lerch, M.E. Glinsky, "Critical grain size parameters for predicting framework and floating grains in sediments", Journal of Sedimentary Research 79, 817 (2009).
  • S. Kalla, C.D. White, J. Gunning, M.E. Glinsky, "Downscaling multiple seismic inversion constraints to fine-scale flow models", SPE Journal 14, 746 (2009).
  • S. Kalla, C.D. White, J. Gunning, M.E. Glinsky, "Consistent downscaling of seismic inversion thicknesses to cornerpoint flow models", SPE Journal 13, 412 (2008).
  • M.E. Glinsky, M.C. Haase, V. Charoing, G. Duncan, R. Hill, G. O'Halloran, L. Dang, J. Gunning, "Bayesian inversion whispers", The Leading Edge 27, 642 (2008).
  • M.E. Glinsky, J. Gunning, R. Pascoe, B. Asher, G. Duncan, "The value of using relative amplitude changes", The Leading Edge 26, 562 (2007).
  • J. Gunning, M.E. Glinsky, C. White, "Delivery Massager: A tool for propagating seismic inversion information into reservoir models", Computers & Geosciences 33, 630 (2007).
  • J. Gunning, M.E. Glinsky, "Detection of reservoir quality using Bayesian seismic inversion", Geophysics 72, R37 (2007).
  • D.C. DeMartini, M.E. Glinsky, "A model for variation of velocity versus density trends in porous sedimentary rocks ," J. Appl. Phys. 100, 014910 (2006).
  • J. Gunning, M.E. Glinsky, "Wavelet extractor: a Bayesian well-tie wavelet derivation program ," Computers & Geosciences 32, 681 (2006). (electronic appendices)
  • F. Blanchette, M. Strauss, E. Meiburg, B. Kneller, M.E. Glinsky, "High-resolution numerical simulations of resuspending gravity currents: Conditions for self-sustainment," J. Geophys. Res. 110, C12022 (2005).
  • M.E. Glinsky, B. Asher, R. Hill, M. Flynn, M. Stanley, J. Gunning, T. Thompson, J. Kalifa, S. Mallat, C. White, D. Renard, "Integration of uncertain subsurface information into multiple reservoir simulation models ," The Leading Edge 24, 990 (October 2005).
  • J. Gunning, M.E. Glinsky, "Delivery: an open-sourced model-based Bayesian seismic inversion program ," Computers & Geosciences 30, 619 (2004). (electronic appendices)
  • S.G. Kuzmin, T.M. O'Neil, M.E. Glinsky, "Guiding center drift atoms," Phys. Plasmas 11, 2382 (2004).
  • M. Strauss, M. Sapir, M.E. Glinsky, J.J. Melick, "Reflected seismic 'color' pulse defines lithology with 10 Hz seismic," Offshore. 118 (April 2003).
  • M. Strauss, M. Sapir, M.E. Glinsky, J.J. Melick, "Geologic lithofacies identification using the multiscale character of seismic reflections," J. Appl. Phys. 94, 5350 (2003).
  • M. Strauss, Y. Kaufman, M. Sapir, P. Amendt, R. A. London, M.E. Glinsky, "Self-consistent coupling of cavitation bubbles in aqueous systems," J. Appl. Phys. 91, 4720 (2002).
  • M. Friedman, M. Strauss, P. Amendt, R.A. London and M.E. Glinsky, "Two-dimensional Rayleigh model for bubble evolution in soft tissue," Phys. Fluids 14, 1768 (2002).
  • M.E. Glinsky, D.S. Bailey, R.A. London, P.A. Amendt, A.M. Rubenchik, M. Strauss, "An Extended Raleigh model of bubble evolution," Phys. Fluids 13, 20 (2001).
  • M.E. Glinsky, G.A. Clark, P.K.Z. Cheng, K.R.S. Devi, J.H. Robinson, G.E. Ford, "Automatic event picking in prestack migrated gathers using a probabilistic neural network," Geophysics 66, 1488 (2001). presentation
  • F.N. Beg, A.R. Bell, A.E. Dangor, C.N. Danson, AP. Fews, M.E. Glinsky, B.A. Hammel, P. Lee, P.A. Norreys and M. Tatarakis, "A study of picosecond laser-solid interactions up to 1019 W cm-2," Phys. Plasmas 4, 447 (1997).
  • R.A. London, M.E. Glinsky, G.B. Zimmerman, D.S. Bailey, D.C. Eder, "Laser-tissue interaction modeling with LATIS," Applied Optics 36, 9068 (1997).
  • M.E. Glinsky, "A Simple Model of Suprathermal Electron Transport," Physics of Plasmas 2, 2796 (1995).
  • M. Tabak, J. Hammer, M.E. Glinsky, W.L. Kruer, S.C. Wilks, J. Woodworth, E.M. Campbell, M.D. Perry, and R.J. Mason, "Ignition and High Gain with Ultra-Powerful Lasers," Phys. of Plasmas 1, 1626 (1994).
  • M.E. Glinsky, T.M. O'Neil, M.N. Rosenbluth, K. Tsuruta and S. Ichimaru, "Collisional Equipartition Rate for a Magnetized Pure Electron Plasma," Phys. Fluids B 4, 1156 (1992).
  • M.E. Glinsky and T. M. O'Neil, "Guiding Center Atoms: Three-body Recombination in a Strong Magnetic Field," Phys. Fluids B 3, 1279 (1991).
• Technical papers
  • wavelet based reservoir ID
    • SEG extended abstract (September 2002) presentation (October 2002)
    • Journal of Applied Physics paper (October 2003)
    • Offshore Magazine article (April 2003)
    • Wavelet reservoir ID – calibration and application (June 2003)
    • Spectral Decomposition: Case Studies (March 2004)
    • Matching pursuit spectral decomposition of seismic data (July 2007)
  • stochastic model based Bayesian inversion
    • EAGE extended abstract (January 2003) presentation (June 2003)
    • Gordon conference poster (July 2002)
    • Computers & Geosciences preprint on inversion (February 2003)
    • SEG extended abstract on wavelet derivation (April 2004)
    • Computers & Geosciences preprint on wavelet derivation (February 2005) presentation (February 2006)
    • EAGE Geostat paper on wavelet derivation and model selection (September 2007) presentation
    • The Leading Edge preprint on Stybarrow (April 2005) presentation (September 2005)
    • Computers & Geosciences preprint on massaging (March 2006)
    • EAGE extended abstract on massaging (June 2006) presentation
    • SPE article on decorating (July 2006) presentation
    • SPE article on decorating, part 2 (August 2007)
    • EAGE Geostat paper on decorating (September 2007) presentation
    • AGU poster on decorating (December 2007)
    • Geophysics preprint on application of floating grain model in DELIVERY (August 2006) presentation A presentation B
    • The Leading Edge preprint on Bayesian Inversion Whispers (December 2007) presentation
    • UWA Physics Department Seminar on "Metropolis methods applied to Bayesian geologic inversions" (September 2010)
  • new paradigm for rapid technology onboarding
    • SEG extended abstract (April 2003) presentation (October 2003)
    • Los Alamos presentation (October 2002)
    • EAGE business of open standards (June 2006)
    • EAGE qiWorkbench (June 2006) poster
    • EAGE openSource DELIVERY software (June 2006)
    • stochastic model based inversion software and XMLeditor interface, CSIRO DELIVERY website
  • basic quantitative interpretation technology
    • ASEG extended abstract on stochastic amplitude analysis (March 2004)
    • EAGE extended abstract on QI risking (January 2004) presentation (June 2004)
    • ASEG extended abstract on Boris QI (April 2004)
    • ASEG extended abstract on neural network picking (April 2004)
    • Floating Grain model, submitted to Journal of Applied Physics (December 2005)
    • The value of relative amplitude changes, submitted to The Leading Edge (November 2006) presentation
    • Numerical simulations of floating grain packings, submitted to Journal of Sedimentary Research (January 2008)
    • EAGE extended abstract on Detection of reservoir sorting characteristics from seismic data (June 2010) presentation
  • numerical turbidite simulation
    • Journal of Geophysical Research preprint on self sustainment (February 2005)
    • Computational Fluid Dynamics preprint on simulating gravity currents on slopes (February 2005)
    • poster of 40 flow simulation (April 2005)
    • Workshop on Numerical Simulation of Turbidites
    • geoPhysics to petroleumEngineering
  • Guiding Center Atoms (theory of formation of antihydrogen at CERN)
    • Guiding Center Drift Atoms
    • Comment on production of antihydrogen (C.F. Driscoll, Phys. Rev. Lett. 92, 149303 (2004))
    • Energy loss of GCDA (submitted to Physics of Plasmas, October 2003)
  • CSEM
    • EAGE extended abstract on Bayesian approaches to resolution in CSEM (June 2009) poster
    • Resolution and uncertainty in 1D CSEM inversion, submitted to Geophysics (October 2009) (final version with extra appendices)
    • EAGE extended abstract on Error Modelling in Bayesian CSEM Inversion (June 2010) presentation
  • Geologic self organization and data assimilation
    • note on "A new perspective on renormalization: invariant actions, a dynamical DNA" submitted to arXiv (June 2011) (arXiv) (presentation)
    • SFI seminar on "Dynamical DNA: a possible metric of complexity" (May 2011) (video)
    • SFI seminar on "Geology and Physics Working Together" (April 2010) (video)
    • "Turbidity current flow over an obstacle and phases of sediment wave generation" submitted to JGR (August 2011) (arXiv) (presentation)
    • note on "A new perspective on renormalization: the scattering transformation" (June 2012) (arXiv)
    • KITP at UCSB talk on "Stratigraphic facies from the physics perspective of emergent phases of self organization" (December 2013) (video) (YouTube)
  • Quantitative Interpretation for unconventionals
    • Rock physics and geophysics for unconventional resource, multi-component seismic, quantitative interpretation (2IWRP, August 2013) (arXiv) (presentation)
    • Stochastic inversion of seismic PP and PS data for reservoir parameter estimation (SEG, September 2013) (presentation) (Geophysics preprint, December 2013)
    • Noise-thresholding sparse-spike inversion with global convergence: calibration and applications (SEG, September 2013) (presentation)
    • Focal mechanism estimation by classification (arXiv, October 2014)
    • A novel workflow for seismic net pay estimation with uncertainty (arXiv, April 2016)
  • Work at Sandia
    • Regimes of suprathermal electron transport (ICOPS, June 2016)
    • Analysis of laser preconditioning experiments on Z-Beamlet Laser (APS DPP, October 2016)
    • Applying data science to break the degeneracy amongst different hypotheses for interpreting MagLIF experiments (IFSA, September 2017)
    • Multi-objecctive data analysis using Bayesian inference for MagLIF experiments (APS DPP, October 2017)
    • Quantification of MagLIF stagnation morphology using the Mallat Scattering Transformation (APS DPP, October 2017) (video) (YouTube)
    • Decision Science applied to Scientific Endeavors (National Diagnostics Working Group meeting, December 2018)
    • A NIF platform for transport experiments (Workshop on Kinetic Effects in Inertial Confinement Fusion, May 2018)
    • At ignition scale experiments on NIF of next generation MagLIF laser preheat (APS DPP, November 2018)
    • Quantification of MagLIF implosion morphology using the Mallat Scattering Transformation (APS DPP, November 2018)
    • The Mallat Scattering Transform in high energy density plasmas: a new look at nonlinear, multiscale physics in HED (HEDSA @ APS DPP, November 2018) (video) (YouTube)
    • The Mallat Scattering Transform as a representation for MLDL that builds in nonlinear physics (Machine Learning for Computational Fluid and Solid Mechanics -- a LANL Center for Nonlinear Studies conference, February 2019)
    • The Mallat Scattering Transform in high energy density plasmas: a new look at nonlinear, multiscale physics in HED (ICHEDS, April 2019)
    • Quantification of MagLIF Morphology using the Mallat Scattering Transformation (SAND Report, October 2019) (arXiv)
    • Data and Decision Science at Sandia National Labs (National Diagnostics Working Group Bayesian data workshop, November 2019)
    • Helicity in Hamiltonian dynamical systems (SAND Report, December 2019) (arXiv)
    • Relationship of the Mallat Scattering Transformation (a deep convolutional network) to causal physics and complexity (seminars at CMU, Pitt and Sandia, January and February 2020) (video) (YouTube) (abstract)
    • Quantification of MagLIF Morphology using the Mallat Scattering Transformation (published in Physics of Plasmas, November 2020) (arXiv)
    • Predicting time dependent shock propagation using Machine Learning (poster at NSF Workshop on Exuberance of Machine Learning in Transport Phenomena, February 2020)
    • Portfolio de-risking for major- capital scientific investments (presentation at DAAG Conference, online, June 2020) (YouTube)
    • Relationship of the Mallat Scattering Transformation (a deep convolutional network) to causal physics, complexity, and topology (presentation at SIAM Mathematics of Data Science Conference, online, August 2020) (YouTube)
    • The MST for ROMing of PDEs (presentation at April Meeting of APS, online, April 2021) (YouTube)
    • VISAR measurements of MagLIF preheat at NIF (presentation at ICOPS, online, September 2021) (YouTube)
    • VISAR measurements of MagLIF preheat at NIF (presentation at APS DPP, online, November 2021) (YouTube)
    • Advantage of Machine Learning over Maximum Likelihood in Limited-Angle Low-Photon X-Ray Tomography (presented at Machine Learning for Scientific Imaging 2022 Conference, at IS&T Electronic Imaging 2022)
    • Noise-resilient deep tomographic imaging (January 2023) (Optics Express preprint)
    • SetRunner computer infrastructure for HPC ensemble running and analysis (December 2022) (GitHub archive)
  • Work at BNZ Energy Inc.
    • Mallat Scattering Transformation based surrogate for MagnetoHydroDynamics (slides, March 2024) (arXiv preprint, December 2022) (YouTube video, March 2024)
    • A new economic and financial theory of money (most recent paper, November 2023) (arXiv) (YouTube) (slides) (transcript)
    • A physics-based Reduced Order Model capturing the topology of dynamical manifolds (slides, November 2023) (YouTube video) (LLNL YouTube video)
    • The inherent goodness of well educated intelligence (most recent paper, December 2023) (slides) (YouTube video) (extended slides) (arXiv preprint) (Livestream TED-like general interest talk) (Transcript of Livestream)
    • A transformational approach to collective behavior (most recent paper, October 2024) (slides) (YouTube video) (Transcript of YouTube video) (arXiv preprint)
    • A coordinate-free expression of plasma theory (most recent paper, December 2024) (arXiv preprint)
• other papers
  • M.E. Glinsky, P.G. Hjorth, "Helicity in Hamiltonian dynamical systems," Sandia National Laboratories Technical Report, SAND2019-14731 (December 2019).
  • M.E. Glinsky et al., "Quantification of MagLIF Morphology using the Mallat Scattering Transformation," Sandia National Laboratories Technical Report, SAND2019-11910 (October 2019).
  • Z. Budimlic, V. Cave, J. Shirako, Y. Yan, J. Zhao, V. Sarkar, M.E. Glinsky, J. Gunning, "Parallel Object-Oriented Scientific Computing with Habanero-Java," 9th Workshop on Parallel/High-Performance Object-Oriented Scientific Computing (POOSC'10), co-located with SPLASH 2010, (2010).
  • T.A. Thompson, M.G. Lamont, B.M. Hartley, M.E. Glinsky, "Prestack hyperspace propagation for automated event picking" SEG Technical Program Expanded Abstracts, 2076-2079 (2004).
  • M.E. Glinsky, D. DePledge, J. Straccia, G. Davis, D. Nevelsteen, "The turbojet engine model of R&D Management," Royal Dutch Shell Technical Report (1999).
  • M. Strauss, Y. Kaufman, M.Sapir, P. Amendt, R.A. London, M.E. Glinsky, "Self-consistent evolution of tissue damage under stress wave propagation," SPIE 3601, 178 (1999).
  • M. Strauss, M. Friedman, E. Gurewitz, P. Amendt, R.A. London, M.E. Glinsky, "Two-dimentional extended Rayleigh model of vapor bubble evolution," SPIE 3601, 212 (1999).
  • M.E. Glinsky, P.A. Amendt, D.S. Bailey, R.A. London, A.M. Rubenchik, "Extended Rayleigh model of bubble evolution with material strength compared to detailed dynamic simulations," SPIE 2975, 318 (1997). presentation movie
  • M.E. Glinsky, D.S. Bailey, R.A. London, "LATIS modeling of laser induced midplane and backplane spallation," SPIE 2975, 374 (1997). presentation movie
  • M. Strauss, P. A. Amendt, R.A. London, D.J. Maitland, M.E. Glinsky, C.P. Lin, W.M. Kelley, "Computational modeling of stress transient and bubble evolution in short-pulse laser irradiated melanosome particles," SPIE 2975, 261 (1997).
  • M. Strauss, P. A. Amendt, R.A. London, D.J. Maitland, M.E. Glinsky, P. Celliers, D.S Bailey, D.A. Young, S.L. Jacques, "Computational modeling of laser thrombolysis for stroke treatment," SPIE 2671, 11 (1996).
  • D.J. Maitland, D.C. Eder, R.A. London, M.E. Glinsky, B.A. Soltz, "Dynamic simulations of tissue welding," SPIE 2671, 234 (1996).
  • M.E. Glinsky, R.A. London, G.B. Zimmerman, S.L. Jacques, J.D. Ols, "Computer modeling of endovascular patch welding using temperature feedback," SPIE 2623, 349 (1996).
  • A.A. Oraevsky, L.B. DaSilva, M.D. Feit, M.E. Glinsky, B.M. Mammini, K.L. Paquette, M.E. Perry, A.M. Rubenchik, W. Small IV, B.C. Stuart, "Plasma mediated ablation of biological tissues with ultrashort laser pulses," SPIE 2391, 423 (1995).
  • T. Antoun, M.E. Glinsky, L. Seaman, "Modeling of ablation by photospalation using the computer program PUFF/DFRACT," SPIE 2391, 413 (1995).
  • M.E. Glinsky, R.A. London, G.B. Zimmerman, S.L. Jacques, "Modeling of endovascular patch welding using the computer program LATIS," SPIE 2391, 262 (1995).
  • R.A. London, M.E. Glinsky, G.B. Zimmerman, D.C. Eder, S.L. Jacques, "Coupled light transport-heat diffusion model for laser dosimetry with dynamic optical properties," SPIE 2391, 434 (1995).
  • T. Antoun, L. Seaman, D. Curran, M.E. Glinsky, "Damage and failure mechanisms associated with photo ablation of biological tissues," AIP Conference Proceedings 370, 1277 (1995).
  • M.E. Glinsky, "Diversification and strategic management of LLNL's R&D portfolio," LLNL Internal Report UCRL-ID-119576, (1994).
  • M.E. Glinsky, "Differential forms applied to plasma physics," DTU seminar, Dept. of Mathematics, (1993).
  • M.E. Glinsky, "Temperature equilibration and three-body recombination in strongly magnetized pure electron plasmas," PhD Dissertation, UCSD, (1991).
  • M.E. Glinsky, P.G. Hjorth "Helicity in hamiltonian dynamical systems," manuscript, (1990).
  • M.E. Glinsky, T.M. O'Neil, M.N. Rosenbluth, K. Tsuruta, S. Ichimaru, "Collisional equipartition rate for a magnetized pure electron plasma," Bul. Am. Phys. Soc. 36, 2330 (1991).
  • M.E. Glinsky, T.M. O'Neil, M.N. Rosenbluth, K. Tsuruta, S. Ichimaru, "Collisional equipartition rate for a magnetized pure electron plasma," Bul. Am. Phys. Soc. 35, 2134 (1990).
  • M.E. Glinsky, T.M. O'Neil, "Three-body recombination in a strong magnetic field," Bul. Am. Phys. Soc. 34, 1934 (1989).
  • M.E. Glinsky, T.M. O'Neil, "Guiding center atoms," Bul. Am. Phys. Soc. 33, 1899 (1988).
  • M.E. Glinsky, "Helicity conservation and Reversed Field Pinches," UCSD Oral PhD Qualifying Exam, (September 1987).
  • M.E. Glinsky, "Motion of electron in radial E-field skew to constant B-field," manuscript, (1987).
  • M.E. Glinsky, "Exterior calculus encapsulates multiple variate calculus," UCSD short course, (1987).
  • M.E. Glinsky, "Neon K-edge as a tool to measure crystal resolving power at 870 eV," LLNL Technical Report, RP-85-106, (1985).
  • M.E. Glinsky, "ROCKIT: a program to calculate spectrometer rocking curves," LLNL Technical Report, RP-85-105, (1985).
  • M.E. Glinsky, "Optical resolving power of a curved mica crystal," LLNL Technical Report, RP-85-104, (1985).
  • M.E. Glinsky, P.A. Waide, "resolving power of muscovite mica (002)," LLNL Technical Report, RP-85-91, (1985).
• Patents
  • M. Glinsky, "Model predicting fracturing of shale", U.S. Patent 9152745
  • M.E. Glinsky, J. Kalifa, S. Mallat, "Method for determining impedance coefficients of a seismic trace", U.S. Patent 7519477
  • D.C. DeMartini, M.E. Glinsky, "Method for improving prediction of the viability of potential petroleum reservoirs", U.S. Patent 7516016
  • J.S. Gunning, M.E. Glinsky, C.D. White, "Method for estimating and/or reducing uncertainty in reservoir models of potential petroleum reservoirs", U.S. Patent 7254091
  • W. Bennet et al., "Opto-acoustic transducer for medical applications", U.S. Patent 6379325 and 5944687
  • P. Celliers et al., "Opto-acoustic thrombolysis", U.S. Patent 6022309
  • M. Glinsky, R. London, G. Zimmerman, S. Jacques, "Intraluminal tissue welding for anastomosis", U.S. Patent 5827265
  • Neev et al., "Ultrashort pulse high repetition rate laser system for biolobical tissue processing", U.S. Patent 5720894
  • M. Glinsky, G. Hansen, "Method and system for providing a graphical workbench environment with intelligent plug-ins", U.S. Patent Application 11/439082
  • M. Glinsky, "Systems and Methods for Controlling Complex Systems", U.S. Patent Application 18/906844