LabCompass

Indranil Nayak

Physics and Astronomy · The Ohio State University

OpenAlex ORCID
Early career · publishing since 2019Rising activity
Model Reduction and Neural NetworksReal-time simulation and control systemsElectrostatic Discharge in ElectronicsPlasma Diagnostics and ApplicationsLaser-Plasma Interactions and Diagnostics

Publications

40

Citations

86

Est. group size

~3

Recurring co-author estimate

Active years

8

Publishing since 2019

Research summary
AI-generated

Indranil Nayak works on data-driven methods for modeling and predicting the behavior of complex dynamical systems, such as spacecraft trajectories, plasma-wave interactions, and particle accelerators. Much of the work uses techniques like Dynamic Mode Decomposition and Koopman-based machine learning to build simplified, physics-informed models that can forecast how systems evolve over time, with applications in aerospace path planning, orbital mechanics, and sensor-based state estimation.

Data-driven modeling of nonlinear dynamical systemsDynamic Mode Decomposition and Koopman methodsSpacecraft trajectory and orbital mechanics predictionPath planning and autonomous navigationPlasma physics and particle accelerator modeling

Publication output has grown from near zero in 2017-2018 to a steady average of about 6 papers per year over the last five years, with a peak in 2023.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 6.2/year recently
17182019: 2 publications192020: 3 publications202021: 4 publications212022: 3 publications222023: 10 publications10232024: 6 publications242025: 6 publications252026: 6 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×10
  • 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI)×2
  • AIAA SCITECH 2023 Forum×2
  • Scientific Reports×1
  • Journal of Computational Physics×1
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 19, 2026.

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