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Parikshit Dutta
Postdoctoral Fellow
INRIA Rhône Alpes & Laboratoire Jean Kuntzmann

655 avenue de l'Europe
38330 Montbonnot, France
Phone:   +33 476 61 54 14 (Office)
Email: firstname dot lastname at inria dot fr

Welcome to my home page! I am a postdoctoral fellow at STEEP Team, which is a part of INRIA Rhône Alpes and Laboratoire Jean Kuntzmann (LJK). Prior to joining INRIA, I did my Ph.D. from Texas A&M University. My advisor was Dr. Raktim Bhattacharya.

I am interested in uncertainty quantification and stochastic optimization, and their application to dynamical systems. Please visit the research tab to know more about my current research. Also visit the links tab for software specific information.

Research interests

  • Uncertainty quantification and solution of inverse problems.
  • Sensitivity analysis, model calibration and validation under uncertainty.
  • Filtering and state estimation of stochastic dynamical systems.
  • Stochastic optimization and parameter estimation using Gaussian processes.
  • Stochastic receding horizon control of discrete dynamical systems.
  • Sum of square programming for stability analysis.

Other interests and attractions

  • Stochastic optimal control.
  • Worked on LQG and stochastic HJB.
  • Randomized algorithms and MCMC.
  • With focus on scalability of algorithms used.
  • Fokker Planck and Perron Frobenius operator and their applications.
  • How to approximate the evolving densities in a SDE.
  • Polynomial chaos and Karhunen Loève expansion
  • Use of stochastic FEM methods to approximate the noise as well as the states in a SDE.
  • Planetary entry descent landing (EDL).
  • EDL of a hypersonic vehicle into a planet's atmosphere. Estimating states and parameters of the vehicle in presence of uncertainties.
  • Computational sustainability.
  • This relates to use of computer science and applied mathematics for sustainable development. Find out more here.

Some programming stuff

  • Compiler based languages known- FORTRAN 90, C++ (good knowledge), C (advanced level knowledge). MPI using FORTRAN 90 and C++ (good knowledge).
  • Scripting based languages- Python (advanced level knowledge), Perl, Ruby. HPC using Python (advanced level knowledge)
  • Other software known- MATLAB (advanced level knowledge), MAPLE etc. Worked with several MATLAB toolboxes for optimization and control systems.
  • High performance computing- Using FORTRAN 90 (advanced level knowledge) and C++ (good knowledge).
  • I work on several areas related to symmetric multiprocessing, MPI, OAR, ssh, grid computing etc. Check out our own grid, grid 5000


  • INRIA's ranking amongst research institutes in the world. See this link.
  • CiTiES Project accepted!!!!!! Check updates at our website.