Kislaya Ravi, M.Sc.

Technische Universität München

Institut für Informatik
Boltzmannstrasse 3
85748 Garching
Germany

Office: MI 02.05.057
Mail: kislaya@in.tum.de 

Tel: +49-89-289-18630
Fax: +49-89-289-18607
Office Hours: by arrangement

 

Background

  • Doctoral Candidate, Chair of Scientific Computing, Technical University Munich, Munich, Germany
  • Master in Science (MSc), Computational Science and Engineering, Technical University Munich, Munich, Germany
  • Master in Technology (MTech.), Machine Design, Indian Institute of Technology (BHU), Varanasi, India
  • Bachelor in Technology (BTech.), Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, India

Research interests

  • Multifidelity
  • Uncertainity Quantification
  • Gaussian Process
  • Sparse Grids Methods
  • Machine Learning
  • Stochastic Optimization

Projects

Teaching

  • Scientific Computing II (IN2141)SS20
  • Algorithm of Uncertainity Quantifications (IN2345) SS20, SS21
  • Scientific Computing I (IN2005) WS20, WS21
  • Master-Praktikum - Machine Learning in Crowd Modeling & Simulation (IN2106, IN4267) WS20, SS21, WS21
  • Seminar High Dimensional Methods in Scientific Computing (IN2107,IN0014,IN2183) SS20

Open and Running Student Projects

Open Student Projects

  • Multi-fidelity bayesian inverse using hamilton markov chain monte carlo
  • Multi-fidelity dyanamic systems

Running Student Projects

  • Adaptive multi-fidelity gaussian process

Finished Student Projects

2021

  • Aurangzeb Ali Rathore: Adaptive Multifidelity Deep Gaussian Process for Uncertainty Quantification. Master thesis, 2021 more…
  • Martin Klapacz: Multifidelity Gaussian Processes for Uncertainty Quantification. Bachelor thesis, 2021 more…

Publications

2019

  • Kislaya Ravi: Neural Network Hyperparameter Optimization using SNOWPAC. Master thesis, 2019 more…

Talks

Posters

2022

  • Ivana Jovanovic Buha; Michael Obersteiner; Tobias Neckel; Hans-Joachim Bungartz: Efficient Uncertainty Quantification and Global Time-Varying Sensitivity Analysis Using the Spatially Adaptive Combination Technique. SIAM Conference on Uncertainty Quantification (UQ22), SIAM, 2022Atlanta, Georgia more…