Bio


Karthik Menon is a postdoctoral scholar in the Cardiovascular Biomechanics Computation Laboratory at Stanford University, advised by Alison Marsden. His current research involves the development of computational methods for accurate patient-specific cardio­vascular blood flow simulations and uncertainty quantification. He graduated with a Ph.D. in Mechanical Engineering from Johns Hopkins University in 2021, where his doctoral work focused on the flow physics of fluid-structure interactions. His broad research interests include fluid mechanics, computational modeling and data-driven methods.

Honors & Awards


  • WCCM-PANACM Travel Award, U.S. Association for Computational Mechanics (2024)
  • Future Faculty Symposium Travel Award, Society of Engineering Science Conference (2023)
  • Mark O. Robbins Prize in High-Performance Computing, Johns Hopkins University (2021)
  • Corrsin-Kovasznay Outstanding Paper Award, Center for Environmental and Applied Fluid Mechanics, Johns Hopkins University (2020)
  • Prosperetti Travel Award, Johns Hopkins University (2017)
  • Departmental Fellowship, Mechanical Engineering, Johns Hopkins University (2016)
  • Summer Research Fellowship, Indian Academy of Sciences (2014)

Professional Education


  • Doctor of Philosophy, Johns Hopkins University (2021)
  • Bachelor of Engineering, Birla Institute of Technology and Science (2015)
  • Master of Science, Johns Hopkins University (2019)

Stanford Advisors


All Publications


  • Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees. Npj imaging Menon, K., Khan, M. O., Sexton, Z. A., Richter, J., Nguyen, P. K., Malik, S. B., Boyd, J., Nieman, K., Marsden, A. L. 2024; 2 (1): 9

    Abstract

    Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary anatomies combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. We propose an optimization-based method to personalize multiscale coronary flow simulations by assimilating clinical CT myocardial perfusion imaging and cardiac function measurements to yield patient-specific flow distributions and model parameters. Using this proof-of-concept study on a cohort of six patients, we reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based purely on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

    View details for DOI 10.1038/s44303-024-00014-6

    View details for PubMedID 38706558

    View details for PubMedCentralID PMC11062925

  • A probabilistic neural twin for treatment planning in peripheral pulmonary artery stenosis. International journal for numerical methods in biomedical engineering Lee, J. D., Richter, J., Pfaller, M. R., Szafron, J. M., Menon, K., Zanoni, A., Ma, M. R., Feinstein, J. A., Kreutzer, J., Marsden, A. L., Schiavazzi, D. E. 2024: e3820

    Abstract

    The substantial computational cost of high-fidelity models in numerical hemodynamics has, so far, relegated their use mainly to offline treatment planning. New breakthroughs in data-driven architectures and optimization techniques for fast surrogate modeling provide an exciting opportunity to overcome these limitations, enabling the use of such technology for time-critical decisions. We discuss an application to the repair of multiple stenosis in peripheral pulmonary artery disease through either transcatheter pulmonary artery rehabilitation or surgery, where it is of interest to achieve desired pressures and flows at specific locations in the pulmonary artery tree, while minimizing the risk for the patient. Since different degrees of success can be achieved in practice during treatment, we formulate the problem in probability, and solve it through a sample-based approach. We propose a new offline-online pipeline for probabilistic real-time treatment planning which combines offline assimilation of boundary conditions, model reduction, and training dataset generation with online estimation of marginal probabilities, possibly conditioned on the degree of augmentation observed in already repaired lesions. Moreover, we propose a new approach for the parametrization of arbitrarily shaped vascular repairs through iterative corrections of a zero-dimensional approximant. We demonstrate this pipeline for a diseased model of the pulmonary artery tree available through the Vascular Model Repository.

    View details for DOI 10.1002/cnm.3820

    View details for PubMedID 38544354

  • Force moment partitioning and scaling analysis of vortices shed by a 2D pitching wing in quiescent fluid EXPERIMENTS IN FLUIDS Zhu, Y., Lee, H., Kumar, S., Menon, K., Mittal, R., Breuer, K. 2023; 64 (10)
  • Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees. medRxiv : the preprint server for health sciences Menon, K., Khan, M. O., Sexton, Z. A., Richter, J., Nieman, K., Marsden, A. L. 2023

    Abstract

    Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary models combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. Personalized flow distributions and model parameters are informed by clinical CT myocardial perfusion imaging and cardiac function using surrogate-based optimization. We reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.

    View details for DOI 10.1101/2023.08.17.23294242

    View details for PubMedID 37645850

  • Predictors of Myocardial Ischemia in Patients with Kawasaki Disease: Insights from Patient-Specific Simulations of Coronary Hemodynamics. Journal of cardiovascular translational research Menon, K., Seo, J., Fukazawa, R., Ogawa, S., Kahn, A. M., Burns, J. C., Marsden, A. L. 2023

    Abstract

    Current treatments for patients with coronary aneurysms caused by Kawasaki disease (KD) are based primarily on aneurysm size. This ignores hemodynamic factors influencing myocardial ischemic risk. We performed patient-specific computational hemodynamics simulations for 15 KD patients, with parameters tuned to patients' arterial pressure and cardiac function. Ischemic risk was evaluated in 153 coronary arteries from simulated fractional flow reserve (FFR), wall shear stress, and residence time. FFR correlated weakly with aneurysm [Formula: see text]-scores (correlation coefficient, [Formula: see text]) but correlated better with the ratio of maximum-to-minimum aneurysmal lumen diameter ([Formula: see text]). FFR dropped more rapidly distal to aneurysms, and this correlated more with the lumen diameter ratio ([Formula: see text]) than [Formula: see text]-score ([Formula: see text]). Wall shear stress correlated better with the diameter ratio ([Formula: see text]), while residence time correlated more with [Formula: see text]-score ([Formula: see text]). Overall, the maximum-to-minimum diameter ratio predicted ischemic risk better than [Formula: see text]-score. Although FFR immediately distal to aneurysms was nonsignificant, its rapid rate of decrease suggests elevated risk.

    View details for DOI 10.1007/s12265-023-10374-w

    View details for PubMedID 36939959

  • Contribution of spanwise and cross-span vortices to the lift generation of low-aspect-ratio wings: Insights from force partitioning PHYSICAL REVIEW FLUIDS Menon, K., Kumar, S., Mittal, R. 2022; 7 (11)
  • A method for partitioning the sources of aerodynamic loading noise in vortex dominated flows PHYSICS OF FLUIDS Seo, J., Menon, K., Mittal, R. 2022; 34 (5)

    View details for DOI 10.1063/5.0094697

    View details for Web of Science ID 000797244200009

  • Investigation of aerodynamic instability vibration of rectangular cylinder based on energy transfer JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS Noda, H., Mittal, R., Seo, J., Menon, K. 2022; 220
  • Significance of the strain-dominated region around a vortex on induced aerodynamic loads JOURNAL OF FLUID MECHANICS Menon, K., Mittal, R. 2021; 918
  • On the initiation and sustenance of flow-induced vibration of cylinders: insights from force partitioning JOURNAL OF FLUID MECHANICS Menon, K., Mittal, R. 2021; 907
  • Quantitative analysis of the kinematics and induced aerodynamic loading of individual vortices in vortex-dominated flows: a computation and data-driven approach JOURNAL OF COMPUTATIONAL PHYSICS Menon, K., Mittal, R. 2021; 443
  • Aeroelastic response of an airfoil to gusts: Prediction and control strategies from computed energy maps JOURNAL OF FLUIDS AND STRUCTURES Menon, K., Mittal, R. 2020; 97
  • Dynamic mode decomposition based analysis of flow over a sinusoidally pitching airfoil JOURNAL OF FLUIDS AND STRUCTURES Menon, K., Mittal, R. 2020; 94
  • Aerodynamic Characteristics of Canonical Airfoils at Low Reynolds Numbers AIAA JOURNAL Menon, K., Mittal, R. 2020; 58 (2): 977-980

    View details for DOI 10.2514/1.J058969

    View details for Web of Science ID 000513533200039

  • Flow physics and dynamics of flow-induced pitch oscillations of an airfoil JOURNAL OF FLUID MECHANICS Menon, K., Mittal, R. 2019; 877: 582-613
  • Phase separation and coexistence of hydrodynamically interacting microswimmers SOFT MATTER Blaschke, J., Maurer, M., Menon, K., Zoettl, A., Stark, H. 2016; 12 (48): 9821-9831

    Abstract

    A striking feature of the collective behavior of spherical microswimmers is that for sufficiently strong self-propulsion they phase-separate into a dense cluster coexisting with a low-density disordered surrounding. Extending our previous work, we use the squirmer as a model swimmer and the particle-based simulation method of multi-particle collision dynamics to explore the influence of hydrodynamics on their phase behavior in a quasi-two-dimensional geometry. The coarsening dynamics towards the phase-separated state is diffusive in an intermediate time regime followed by a final ballistic compactification of the dense cluster. We determine the binodal lines in a phase diagram of Péclet number versus density. Interestingly, the gas binodals are shifted to smaller densities for increasing mean density or dense-cluster size, which we explain using a recently introduced pressure balance [S. C. Takatori, et al., Phys. Rev. Lett. 2014, 113, 028103] extended by a hydrodynamic contribution. Furthermore, we find that for pushers and pullers the binodal line is shifted to larger Péclet numbers compared to neutral squirmers. Finally, when lowering the Péclet number, the dense phase transforms from a hexagonal "solid" to a disordered "fluid" state.

    View details for DOI 10.1039/c6sm02042a

    View details for Web of Science ID 000394087100021

    View details for PubMedID 27869284

  • Attraction-induced jamming in the flow of foam through a channel SOFT MATTER Menon, K., Govindarajan, R., Tewari, S. 2016; 12 (37): 7772-7781

    Abstract

    We study the flow of a pressure-driven foam through a straight channel using numerical simulations, and examine the effects of a tuneable attractive potential between bubbles. We show that the effect of an attractive potential is to introduce a regime of jamming and stick-slip flow in a channel, and report on the behaviour resulting from varying the strength of the attraction. We find that there is a force threshold below which the flow jams, and upon further increasing the driving force, a crossover from intermittent (stick-slip) to smooth flow is observed. This threshold force below which the foam jams increases linearly with the strength of the attractive potential. By examining the spectra of energy fluctuations, we show that stick-slip flow is characterized by low frequency rearrangements and strongly local behaviour, whereas steady flow shows a broad spectrum of energy drop events and collective behaviour. Our work suggests that the stick-slip and the jamming regimes occur due to the increased stabilization of contact networks by the attractive potential - as the strength of attraction is increased, bubbles are increasingly trapped within networks, and there is a decrease in the number of contact changes.

    View details for DOI 10.1039/c6sm01719c

    View details for Web of Science ID 000384442500008

    View details for PubMedID 27526347