Photo of Samuel Grauer

232 Research East Building
Penn State
814-863-6289
sgrauer@psu.edu

Samuel Grauer’s Home Page

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Biography

I am an Assistant Professor in the Department of Mechanical Engineering at Penn State. My research group studies inverse problems in optical diagnostics, with a focus on flow reconstruction, non-destructive testing and evaluation, and large-scale uncertainty quantification for nonlinear and chaotic systems.

Our work centers on interpreting measurements from advanced optical diagnostics, including:

We integrate sensor data with physical models, such as governing equations, reduced-order descriptions, and generic priors like smoothness constraints, and we leverage scientific machine learning, differentiable programming, and Bayesian inference to investigate: A central theme of our work is developing high-fidelity, differentiable observation operators, realistic noise models, and theoretical tools for characterizing the observability of fluid systems. These elements are essential for accurate flow reconstructions and rigorous uncertainty quantification.

I earned a PhD from the University of Waterloo in 2018 and a BSc from the University of Manitoba in 2014. From 2018 to 2020, I was a postdoctoral fellow in the Ben T. Zinn Combustion Laboratory at Georgia Tech.

Curriculum Vitae – You can find a copy of my CV here.

Students

Underlined degrees were earned in my group.

Current PhD Students

*Co-supervised with Prof Yuan Xuan

Current MS Students

Current BS Students

Alumni

Prospective Students

If you are an aspiring graduate student with exceptional skills in programming, applied physics, or statistics, a passion for experimenting with laser beams and high-speed cameras, and an insatiable curiosity for tackling challenges at the intersection of physics, measurement, and uncertainty... I'd love to hear from you! Please send me an email to discuss opportunities in my research group.

Publications

Underlined authors were supervised by me and † indicates that authors made an equal contribution.

Book Chapters

  1. SJ Grauer, TA Sipkens, PJ Hadwin, and KJ Daun, “Statistical inversion, uncertainty quantification, and the optimal design of optical experiments,” in Optical Diagnostics for Reacting and Non-Reacting Flows: Theory and Practice, A Steinberg and S Roy, eds, 1st ed (AIAA, 2023), 1137–1202. doi:10.2514/5.9781624106330.1137.1202
  2. BR Halls, TR Meyer, SJ Grauer, and L Ma, “Tutorial: Tomographic imaging in combustion-related flows,” in Optical Diagnostics for Reacting and Non-Reacting Flows: Theory and Practice, A Steinberg and S Roy, eds, 1st ed (AIAA, 2023), 1089–1136. doi:10.2514/5.9781624106330.1089.1136
  3. H McCann, P Wright, K Daun, SJ Grauer, C Liu, and S Wagner, “Chemical species tomography,” in Industrial Tomography: Systems and Applications, M Wang, ed, 2nd ed (Woodhead Publishing, 2022), 155–206. doi:10.1016/B978-0-12-823015-2.00004-2

Journal Papers

  1. Y Bin, XIA Yang, SJ Grauer, and RF Kunz, “Data-enabled reduction of the time complexity of iterative solvers,” J Comput Phys 529, 113859, 2025. doi:10.1016/j.jcp.2025.113859
  2. JP Molnar, EJ LaLonde, CS Combs, O Léon, D Donjat, and SJ Grauer, “Forward and inverse modeling of depth-of-field effects in background-oriented schlieren,” AIAA J 62(11), 4316–4329, 2024. doi:10.2514/1.J064095
  3. JL Suazo Betancourt, SJ Grauer, J Bak, AM Steinberg, and MLR Walker, “Bayesian plasma model selection for Thomson scattering,” Rev Sci Instrum 95, 043004, 2024. doi:10.1063/5.0158749
  4. Y Bin, X Hu, J Li, SJ Grauer, and XIA Yang, “Constrained re-calibration of two-equation Reynolds-averaged Navier–Stokes models,” Theor Appl Mech Lett 14(2), 100503, 2024. doi:10.1016/j.taml.2024.100503
  5. FJ Bauer†, PAB Braeuer†, MWR Wilke, S Will, and SJ Grauer, “2D in situ determination of soot optical band gaps in flames using hyperspectral absorption tomography,” Combust Flame 258, 112730, 2023. doi:10.1016/j.combustflame.2023.112730
  6. K Zhou, J Li, J Hong, and SJ Grauer, “Stochastic particle advection velocimetry (SPAV): theory, simulations, and proof-of-concept experiments,” Meas Sci Technol 34(6), 065302, 2023. doi:10.1088/1361-6501/acc049
  7. JP Molnar, L Venkatakrishnan, BE Schmidt, TA Sipkens, and SJ Grauer, “Estimating density, velocity, and pressure fields in supersonic flows using physics-informed BOS,” Exp Fluids 64, 14, 2023. doi:10.1007/s00348-022-03554-y
  8. TA Sipkens, JC Corbin, SJ Grauer, and GJ Smallwood, “Tutorial: Guide to error propagation for particle counting measurements,” J Aerosol Sci 167, 106091, 2023. doi:10.1016/j.jaerosci.2022.106091
  9. SJ Grauer†, K Mohri†, T Yu, H Liu, and W Cai, “Volumetric emission tomography for combustion processes,” Prog Energy Combust Sci 94, 101024, 2023. doi:10.1016/j.pecs.2022.101024
  10. SJ Grauer, KM Rice, JM Donbar, NJ Bisek, JJ France, BA Ochs, and AM Steinberg, “Optimization of tunable diode laser arrays for inlet mass capture measurement,” AIAA J 60(10), 5854–5867, 2022. doi:10.2514/1.J061774
  11. JP Molnar and SJ Grauer, “Flow field tomography with uncertainty quantification using a Bayesian physics-informed neural network,” Meas Sci Technol 33(6), 065305, 2022. doi:10.1088/1361-6501/ac5437
  12. M Gomez, SJ Grauer, J Ludwigsen, AM Steinberg, SF Son, S Roy, and TR Meyer, “Megahertz-rate background-oriented schlieren tomography in post-detonation blasts,” Appl Opt 61(10), 2444–2458, 2022. doi:10.1364/AO.449654
  13. TA Sipkens, SJ Grauer, AM Steinberg, SN Rogak, and P Kirchen, “New transform to project axisymmetric deflection fields along arbitrary rays,” Meas Sci Technol 33(3), 035201, 2021. doi:10.1088/1361-6501/ac3f83
  14. NP Brown, SJ Grauer, JA Deibel, MLR Walker, and AM Steinberg, “Bayesian framework for THz-TDS plasma diagnostics,” Opt Express 29(4), 4887–4901, 2021. doi:10.1364/OE.417396
  15. SJ Grauer and AM Steinberg, “Linear absorption tomography with velocimetry (LATV) for multiparameter measurements in high-speed flows,” Opt Express 28(22), 32676–32692, 2020. doi:10.1364/OE.408588
  16. RB Miguel, J Emmert, SJ Grauer, J Thornock, and KJ Daun, “Optimal filter selection for quantitative gas mixture imaging,” J Quant Spectrosc Radiat Transfer 254, 107208, 2020. doi:10.1016/j.jqsrt.2020.107208
  17. SJ Grauer and AM Steinberg, “Fast and robust volumetric refractive index measurement by unified background-oriented schlieren tomography,” Exp Fluids 61(3), 80, 2020. doi:10.1007/s00348-020-2912-1
  18. J Emmert, SJ Grauer, S Wagner, and KJ Daun, “Efficient Bayesian inference of absorbance spectra from transmitted intensity spectra,” Opt Express 27(19), 26893–26909, 2019. doi:10.1364/OE.27.026893
  19. SJ Grauer†, J Emmert†, ST Sanders, S Wagner, and KJ Daun, “Multiparameter gas sensing with linear hyperspectral absorption tomography,” Meas Sci Technol 30(10), 105401, 2019. doi:10.1088/1361-6501/ab274b
  20. SJ Grauer, A Unterberger, A Rittler, KJ Daun, AM Kempf, and K Mohri, “Instantaneous 3D flame imaging by background-oriented schlieren tomography,” Combust Flame 196, 284–299, 2018. doi:10.1016/j.combustflame.2018.06.022
  21. TA Sipkens, PJ Hadwin, SJ Grauer, and KJ Daun, “Predicting the heat of vaporization of iron at high temperatures using time-resolved laser-induced incandescence and Bayesian model selection,” J Appl Phys 123(9), 095103, 2018. doi:10.1063/1.5016341
  22. SJ Grauer, BC Conrad, RB Miguel, and KJ Daun, “Gaussian model for emission rate measurement of a heated plume using hyperspectral data,” J Quant Spectrosc Radiat Transfer 206, 125–134, 2018. doi:10.1016/j.jqsrt.2017.11.005
  23. TA Sipkens, PJ Hadwin, SJ Grauer, and KJ Daun, “General error model for analysis of laser-induced incandescence signals,” Appl Opt 56(30), 8436–8445, 2017. doi:10.1364/AO.56.008436
  24. SJ Grauer, PJ Hadwin, TA Sipkens, KJ Daun, “Measurement-based meshing, basis selection, and prior assignment in chemical species tomography,” Opt Express 25(21), 25135–2514, 2017. doi:10.1364/OE.25.025135
  25. SJ Grauer, RW Tsang, and KJ Daun, “Broadband chemical species tomography: Measurement theory and a proof-of-concept emission detection experiment,” J Quant Spectrosc Radiat Transfer 198, 145–154, 2017. doi:10.1016/j.jqsrt.2017.04.030
  26. SJ Grauer, PJ Hadwin, and KJ Daun, “Improving chemical species tomography of turbulent flows using covariance estimation,” Appl Opt 56(13), 3900–3912, 2017. doi:10.1364/AO.56.003900
  27. SJ Grauer, PJ Hadwin, and KJ Daun, “Bayesian approach to the design of chemical species tomography experiments,” Appl Opt 55(21), 5772–5782, 2016. doi:10.1364/AO.55.005772
  28. KJ Daun, SJ Grauer, and PJ Hadwin, “Chemical species tomography of turbulent flows: Discrete ill-posed and rank deficient problems and the use of prior information,” J Quant Spectrosc Radiat Transfer 172, 58–74, 2016. doi:10.1016/j.jqsrt.2015.09.011
  29. SJ Grauer, EJFR Caron, NL Chester, MA Wells, and KJ Daun, “Investigation of melting in the Al–Si coating of a boron steel sheet by differential scanning calorimetry,” J Mater Process Technol 216, 89–94, 2015. doi:10.1016/j.jmatprotec.2014.09.001

Preprints

  1. JP Molnar, J Xia, R Zhang, SJ Grauer, and C Liu, “Unsupervised neural-implicit laser absorption tomography for quantitative imaging of unsteady flames,” arXiv preprint, 2501.08337, 2024. doi:10.48550/arXiv.2501.08337
  2. AI Masker, K Zhou, JP Molnar, and SJ Grauer, “Neural optical flow for planar and stereo PIV,” arXiv preprint, 2411.02373, 2024. doi:10.48550/arXiv.2411.02373
  3. K Zhou and SJ Grauer, “Flow reconstruction and particle characterization from inertial Lagrangian tracks,” arXiv preprint, 2311.09076, 2023. doi:10.48550/arXiv.2311.09076

Gallery

Boal City Brewing, Summer 2024

Photo of Grauer Lab

Bowling, Spring 2024

Photo of Grauer Lab

Links

Personal research profiles

Affiliated research links

Miscellaneous