Sandeep Reddy B

Sandeep Reddy B

Postdoctoral Research Scientist

Max Planck Institute for Dynamics of Complex Technical Systems


I am a postdoctoral research scientist at Max Planck Institute, Germany where i am actively involved in developing innovative methods for discovery of parsimonious nonlinear dynamical models using the concepts from scientific machine learning. I am also part of Max Planck research network on big data-driven material science BiGmax. Prior to MPI, I worked as a research scientist at TCOMS under Prof Chan Eng Soon and developed fast and accurate methods for reconstruction and propagation of multidirectional ocean wave fields. My work at TCOMS broadly touched upon concepts ranging from compressed sensing, sparse representation, model order reduction, proper orthogonal decomposition, physics informed A.I and custom made ML networks such as Fourier neural operators. In my doctoral work under Prof A R Magee and Prof R K Jaiman, I focused on developing data-driven methods for stability analysis and prediction of fluid-structure interaction. As part of my PhD research, I pursued topics ranging from system identification, ERA, Recurrent neural networks, Convolutional neural networks, Proper orthogonal decompisition and data-driven reduced order models.

I am always open for any kind of discussion on anything related to my work or any interesting ideas or topics.

In addition to the above, i try to do… 🏃 🥋 🏎️ 🏏 🎦 in my free time.

  • Machine learning/ Deep learning
  • Physics-informed A.I.
  • Model order reduction
  • Nonlinear dynamics
  • Applied mathematics
  • Computational physics
  • PhD in Data-driven computational fluid mechanics, 2020

    National University of Singapore

  • in Applied mechanics, 2015

    Indian Institute of Technology, Madras

  • in Naval architecture and Ocean engineering, 2014

    Indian Institute of Technology, Madras


Max Planck Institute for Dynamics of Complex Technical Systems
Postdoctoral Research Scientist
Sep 2021 – Present Magdeburg, Germany

Physics Enhanced Machine Learning

  • Developmemt of parsimonious dynamical models using scientific machine learning.
  • Discovery of physically interpretable continuum models of materials science from experimental data
Research Scientist
Mar 2020 – Aug 2021 Singapore

Development of digital twin of ocean wave environment

  • Reconstruction of ocean wave field from instantaneous probe data using the concepts of compressed sensing
  • Reduced order models for fast propagation of multi-directional ocean wave fields
  • Data-driven models for reconstruction and propagation of multi- directional ocean wave fields
National University of Singapore
Research Engineer
Sep 2019 – Mar 2020 Singapore
Model order reduction for nonlinear evolution of ocean waves
National University of Singapore
Doctoral scholar
Aug 2015 – Aug 2019 Singapore

Data-driven computing for stability analysis and prediction of fluid-structure interaction

  • Data-driven computing for stability analysis of passive suppression
  • Hybrid reduced order model for fluid structure interaction
  • Convolutional recurrent autoencoder networks for complete predic- tion of flow field


Deep learning
See certificate
Tensorflow developer
See certificate


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