Scholar
Sayak Mukherjee
Google Scholar ID: x2aB63gAAAAJ
Senior Research Scientist, Pacific Northwest National Laboratory - PNNL
Citations & Impact
Citations
464
H-index
12
i10-index
17
Publications
20
Co-authors
15
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers on power system control, reinforcement learning, data-driven control, etc., in journals such as IEEE Transactions on Smart Grid, Automatica; Participated in and organized sessions at international conferences like INFORMS 2024, IECON 2024; Authored book chapters.
Research Experience
- Worked as an R&D intern at New York Power Authority during Ph.D.; Post-Doctorate Research Associate at PNNL after graduation.
Education
- Ph.D. in Electrical Engineering from North Carolina State University, Raleigh, NC, USA (Aug. 2015 - May 2020), dissertation: 'Data-Driven Reinforcement Learning Control using Model Reduction Techniques: Theory and Applications to Power Systems', Advisor: Dr. Aranya Chakrabortty; B.E., Electrical Engineering, Jadavpur University, Kolkata, India (2011-2015), First Class Honours, CGPA: 9.38/10, Percentage: 87.31.
Background
- Currently a staff scientist in the Optimization and Control Group at Pacific Northwest National Laboratory (PNNL). Research interests include Optimal and Robust Control, Data-driven Optimal Control using Reinforcement Learning, AI/ML, Secure Controls, Distributed Control, Machine Learning with Graph Neural Nets. Applications span across Energy Systems, Large-scale Power grid Dynamics and Control, Grid resiliency, Grid reliability, Analysis and Control of Wind-integrated Power Systems, Distributed Energy Resources, Grid-forming Inverters and Power Electronics-dominated Grids.
