Robert Mieth

Robert Mieth

Assistant Professor

Rutgers University


Update: Please see my lab website for most recent updates.

I am currently an Assistant Professor at the Department of Industrial and Systems Engineering at Rutgers University. Prior to joining Rutgers I was a Postdoctoral Fellow at the Department of Electrical and Computer Engineering at Princeton University. I received the Doctorate in engineering (Dr.-Ing.) degree from the Technical University of Berlin, Germany, in 2021. From 2018 to 2020, I was a Visiting Scholar and, from 2021 to 2022, a Postdoctoral Researcher at the Department of Electrical and Computer Engineering of New York University’s Tandon School of Engineering. My research interests include risk analysis, stochastic optimization, and data methods for modern power system operations and electricity markets.

Research topics include:

  • Power System Operation and Planning
  • Stochastic Optimization and Data Methods for Power Systems
  • Electricity Markets and Energy Economics
  • Decarbonization and Renewable Energy Integration
  • Power System Resiliencey and Cybersecurity
  • Distributed and Demand-Side Resources

Download my CV .

  • PhD in Electrical Engineering, 2021

    Technical University Berlin

  • MSc Electrical Enegineering, 2017

    Technical University of Berlin

  • MSc Industrial Engineering, 2017

    Technical University of Berlin

Recent News

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[Sept. ‘23] I started a new position as Assistant Professor at Rutgers University.

[July ‘23] Jingrong Zhang and I presented our work on 100% electrified transportation in NYC at the 2023 IEEE PES General Meeting.

[May ‘23] New preprint: Data Valuation from Data-Driven Optmization.

[Apr. ‘23] Our paper Uncertainty-Aware Capacity Allocation in Flow-Based Market Coupling was accepted for publication in IEEE Transactions on Power Systems.

[Mar. ‘23] I gave a talk for the Princeton Optimization Seminar titled “Enabling Data Valuation via multi-source data-driven distributionally robust optimization”.

Selected Publications

All publications» and Google Scholar .

(2023). Data Valuation from Data-Driven Optimization.

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(2022). Risk-Aware Dimensioning and Procurement of Contingency Reserve. IEEE Transactions on Power System.


(2020). Risk-and variance-aware electricity pricing. 2020 Power Systems Computation Conference.

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(2020). Risk Trading in a Chance-Constrained Stochastic Electricity Market. IEEE Control Systems Letters.

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(2020). Fast Security-Constrained Optimal Power Flow Through Low-Impact and Redundancy Screening. IEEE Transactions on Power Systems.

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(2019). Online learning for network constrained demand response pricing in distribution systems. IEEE Transactions on Smart Grid.

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(2019). Distribution electricity pricing under uncertainty. IEEE Transactions on Power Systems.

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(2018). Data-Driven Distributionally Robust Optimal Power Flow for Distribution Systems. IEEE Control System Letters.

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