PNNL

Rounak Meyur is a data scientist with the Data Science and Machine Intelligence group at Pacific Northwest National Laboratory (PNNL). His research interests lie at the intersection of optimization, control, and learning applied to complex networked systems. In particular, his expertise lies in the area of mathematical programming, convex optimization, optimal control, heuristics and approximation algorithms. He applies these techniques to solve problems that arise in enhancing cyber-physical security, creating synthetic networked infrastructure, decarbonization of energy infrastructure systems, and improving resiliency of infrastructure systems. He was a research assistant at the Biocomplexity Institute & Initiative of the University of Virginia between 2020 and 2022. He was involved in developing frameworks for the realistic modeling and analysis of power grids. He has previously interned at PNNL and PJM Interconnection. 

• Combinatorial Optimization
• Distributed Energy Resources
• Graph Theory
• Network Science
• Power Systems and Electrical Engineering
• Python

PhD, Electrical Engineering, University of Virginia

MS, Electrical Engineering, Virginia Polytechnic Institute & State University

BS, Electrical & Electronic Engineering, National Institute of Technology, Warangal, India