Kinshuk Panda


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Kinshuk Panda is a postdoctoral researcher in the Complex Systems Simulation and Optimization Group. In his role, he is investigating the application of multi-fidelity methods for modeling optimal grid operations and wind farm design under uncertainty. Furthermore, he enabled the development and deployment of scalable software on the U.S. Department of Energy’s leadership-class supercomputers for modeling grid operations under extreme weather events as part of the Exascale Computing Project. Panda is passionate about using advanced computing systems to develop solutions for various water and clean energy technologies. He is currently developing analysis tools for evaluating the performance of water treatment models using high-performance computing (HPC) systems. Furthermore, he is facilitating the use of HPC in other projects by maintaining documentation and how-to guides on running applications on NREL’s HPC Eagle system.

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

Research Interests

Clean energy systems modeling at scale

Uncertainty quantification

Multidisciplinary design analysis and optimization

Professional Experience

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

Research Assistant, Rensselaer Polytechinc Institute (2014–2019)

Teaching Assistant, Rensselaer Polytechinc Institute (2013–2015, Fall 2019)

Education/Academic Qualification

Bachelor, Mechanical Engineering, Manipal Institute of Technology

PhD, Mechanical Engineering, Rensselaer Polytechnic Institute


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