Mohini S. Bariya

I am a power sector specialist with technical roots in statistical signal processing, machine learning, graph theory, and optimization. I have extensive experience working at the intersection of energy and computation across startups, academia, and international organizations. I hold a bachelor’s degree in Computer Science and a Ph.D. in Electrical Engineering and Computer Sciences, both from the University of California, Berkeley.

My research has focused on developing algorithms and measurement methods for enhanced grid visibility to bolster renewable integration, system resilience, and operational efficiency. Designing algorithmic tools that succeed within real-world constraints—such as measurement noise, system uncertainties, sensor coverage and resolution limitations, and human user needs—has been a consistent theme in my work. I have also worked on a diversity of energy system modeling projects, from network simulation to capacity expansion planning.

Outside the energy sector, my love of signal processing has, in the past, led me to work in domains such as agricultural automation and medical imaging.

selected publications

Topology Estimation

Unsupervised impedance and topology estimation of distribution networks—Limitations and tools

Keith Moffat, Mohini Bariya, and Alexandra Von Meier

IEEE Transactions on Smart Grid, 2019

Bib

@article{moffat2019unsupervised,
  title = {Unsupervised impedance and topology estimation of distribution networks—Limitations and tools},
  author = {Moffat, Keith and Bariya, Mohini and Von Meier, Alexandra},
  journal = {IEEE Transactions on Smart Grid},
  volume = {11},
  number = {1},
  pages = {846--856},
  year = {2019},
  publisher = {IEEE},
}

Topology Estimation

Guaranteed phase & topology identification in three phase distribution grids

Mohini Bariya, Deepjyoti Deka, and Alexandra Von Meier

IEEE Transactions on Smart Grid, 2021

Bib

@article{bariya2021guaranteed,
  title = {Guaranteed phase \& topology identification in three phase distribution grids},
  author = {Bariya, Mohini and Deka, Deepjyoti and Von Meier, Alexandra},
  journal = {IEEE Transactions on Smart Grid},
  volume = {12},
  number = {4},
  pages = {3605--3612},
  year = {2021},
  publisher = {IEEE},
}

Machine Learning

k-shapestream: Probabilistic streaming clustering for electric grid events

Mohini Bariya, Alexandra Von Meier, John Paparrizos, and 1 more author

In 2021 IEEE Madrid PowerTech, 2021

Bib

@inproceedings{bariya2021k,
  title = {k-shapestream: Probabilistic streaming clustering for electric grid events},
  author = {Bariya, Mohini and Von Meier, Alexandra and Paparrizos, John and Franklin, Michael J},
  booktitle = {2021 IEEE Madrid PowerTech},
  pages = {1--6},
  year = {2021},
  organization = {IEEE},
}