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Kinshuk Panda

Postdoctoral Researcher-Computational Sciences


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Kinshuk Panda is a postdoctoral researcher in the Complex Systems Simulation and Optimization Group. He is currently investigating dimension reduction and multi-fidelity methods for nonintrusive uncertainty quantification for wind farm design and stochastic optimal power flow. Additionally, as part of the Exascale Computing Project, he is working on developing high-fidelity models for wind scenario generation for solving security-constrained optimal power flow problems on the next generation of U.S. Department of Energy leadership-class supercomputers.

Panda has a background in PDE-constrained optimization and investigated the use of Krylov methods for dimension reduction for uncertainty propagation in his doctoral dissertation.

For additional information, see Kinshuk Panda's LinkedIn profile

Disclaimer: Any opinions expressed on LinkedIn are the author’s own, made in the author's individual capacity, and do not necessarily reflect the views of NREL.

Research Interests

Uncertainty quantification

Optimal power flow

Multidisciplinary design analysis and optimization

Education

Ph.D., Mechanical Engineering, Rensselaer Polytechnic Institute

B.E., Mechanical Engineering, Manipal Institute of Technology

Professional Experience

Postdoctoral Researcher, Computational Sciences, NREL (2020–present)

Research Assistant, Rensselaer Polytechnic Institute (2014–2019)

Teaching Assistant, Rensselaer Polytechnic Institute (2013–2014, 2015, 2019)

Associations and Memberships

Member, Society for Industrial and Applied Mathematics

Member, American Institute of Aeronautics and Astronautics

Featured Work

Multi-fidelity Active Subspaces for Wind Farm Uncertainty Quantification, AIAA Scitech (2021)

Hessian-based Dimension Reduction for Optimization Under Uncertainty, AIAA Aviation Multidisciplinary Analysis and Optimization Conference (2018)

Investigation of Stabilization Methods for Multidimensional Summation-by-Parts Discretizations of the Euler Equations, AIAA SciTech (2016)