World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
47
Citations
10762
World Ranking
1249
National Ranking
557

Engineering and Technology

D-Index
51
Citations
12071
World Ranking
3792
National Ranking
1112

Overview

Jean-Paul Watson is affiliated with Lawrence Livermore National Laboratory in the United States. Their research primarily spans the field of Engineering, with a strong focus on Electrical and Electronic Engineering, Control and Systems Engineering, Safety, Risk, Reliability and Quality, Global and Planetary Change, and Management Science and Operations Research.

The scientist's work concentrates on several key topics, including Electric Power System Optimization, Optimal Power Flow Distribution, Integrated Energy Systems Optimization, Risk and Portfolio Optimization, Power System Reliability and Maintenance, Smart Grid Security and Resilience, and Optimization and Mathematical Programming.

Notable recent publications by Jean-Paul Watson encompass a variety of studies related to optimization and power systems. These include:

  • On Mixed-Integer Programming Formulations for the Unit Commitment Problem, 2020, INFORMS journal on computing
  • A computationally efficient algorithm for computing convex hull prices, 2021, Computers & Industrial Engineering
  • A novel matching formulation for startup costs in unit commitment, 2020, Mathematical Programming Computation
  • Assessment of wind power scenario creation methods for stochastic power systems operations, 2020, Applied Energy
  • Optimization-Driven Scenario Grouping, 2020, INFORMS journal on computing

Jean-Paul Watson collaborates frequently with several researchers, including David L. Woodruff, Carl D. Laird, John D. Siirola, Bethany L. Nicholson, and Michael Bynum. These collaborations reflect a continued focus on optimization and power systems research.

The scientist has contributed to several publication venues repeatedly. The most frequent outlets for their work are arXiv (Cornell University), INFORMS journal on computing, Mathematical Programming Computation, Electric Power Systems Research, and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

In addition to journal articles, Jean-Paul Watson has published books related to optimization modeling in Python. These include:

  • Pyomo - Optimization Modeling in Python, Springer International Publishing, 2021
  • Pyomo - Optimization Modeling in Python 3rd Ed., Office of Scientific and Technical Information, 2022

This profile reflects Jean-Paul Watson's engagement in advanced optimization techniques applied to energy systems and related operational challenges, as well as their active presence in both academic and applied research communities.

Best Publications

  • Pyomo - Optimization Modeling in Python

    William E. Hart;Carl Laird;Jean-Paul Watson;David L. Woodruff

  • Pyomo: modeling and solving mathematical programs in Python

    William E. Hart;Jean-Paul Watson;David L. Woodruff

  • Multi-stage robust unit commitment considering wind and demand response uncertainties

    Chaoyue Zhao;Jianhui Wang;Jean-Paul Watson;Yongpei Guan

  • The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms

    Avi Ostfeld;James G. Uber;Elad Salomons;Jonathan W. Berry

  • Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems

    Jean-Paul Watson;David L. Woodruff

  • Sensor Placement in Municipal Water Networks

    Jonathan W. Berry;Jonathan W. Berry;Lisa Fleischer;Lisa Fleischer;William E. Hart;William E. Hart;Cynthia A. Phillips;Cynthia A. Phillips

  • Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models

    Jonathan Berry;William E. Hart;Cynthia A. Phillips;James G. Uber

  • Scheduling Space–Ground Communications for the Air Force Satellite Control Network

    Laura Barbulescu;Jean-Paul Watson;L. Darrell Whitley;Adele E. Howe

  • Two-stage robust optimization for N-k contingency-constrained unit commitment

    Qianfan Wang;Jean-Paul Watson;Yongpei Guan

  • Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs

    Dinakar Gade;Gabriel Hackebeil;Sarah M. Ryan;Jean-Paul Watson

  • The IEEE Reliability Test System: A Proposed 2019 Update

    Clayton Barrows;Eugene Preston;Andrea Staid;Gord Stephen

  • Ensuring Profitability of Energy Storage

    Yury Dvorkin;Ricardo Fernandez-Blanco;Daniel S. Kirschen;Hrvoje Pandzic

  • Conceptual Framework for Developing Resilience Metrics for the Electricity, Oil, and Gas Sectors in the United States

    Jean-Paul Watson;Ross Guttromson;Cesar Silva-Monroy;Robert Jeffers

  • PySP: modeling and solving stochastic programs in Python

    Jean-Paul Watson;David L. Woodruff;William E. Hart

  • A Multiple-Objective Analysis of Sensor Placement Optimization in Water Networks

    Jean-Paul Watson;Harvey J. Greenberg;William E. Hart

  • pyomo.dae : a modeling and automatic discretization framework for optimization with differential and algebraic equations

    Bethany Nicholson;John D. Siirola;Jean-Paul Watson;Victor M. Zavala

  • Problem difficulty for tabu search in job-shop scheduling

    Jean-Paul Watson;J. Christopher Beck;Adele E. Howe;L. Darrell Whitley

  • Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance

    Jean-Paul Watson;Laura Barbulescu;L. Darrell Whitley;Adele E. Howe

  • Scalable Planning for Energy Storage in Energy and Reserve Markets

    Bolun Xu;Yishen Wang;Yury Dvorkin;Ricardo Fernandez-Blanco

  • Modeling and solving a large-scale generation expansion planning problem under uncertainty

    Shan Jin;Sarah M. Ryan;Jean-Paul Watson;David L. Woodruff

  • Multi-Stage Robust Unit Commitment Considering Wind and Demand Response Uncertainties.

    Jean-Paul Watson;Chaoyue Zhao;Yongpei Guan;Jianhui Wang

  • Two-Stage Robust Optimization for N-K Contingency-Constrained Unit Commitment.

    Jean-Paul Watson;QIanfan Wang;Yongpei Guan

  • Mathematical Programs with Equilibrium Constraints

    William E. Hart;Carl D. Laird;Jean-Paul Watson;David L. Woodruff

Frequent Co-Authors

David L. Woodruff
David L. Woodruff University of California, Davis
William E. Hart
William E. Hart Sandia National Laboratories
Adele E. Howe
Adele E. Howe Colorado State University
L. Darrell Whitley
L. Darrell Whitley Colorado State University
Cynthia A. Phillips
Cynthia A. Phillips Sandia National Laboratories
Yongpei Guan
Yongpei Guan University of Florida
Ali Pinar
Ali Pinar Sandia National Laboratories
Roger J.-B. Wets
Roger J.-B. Wets University of California, Davis
Yury Dvorkin
Yury Dvorkin New York University
Daniel S. Kirschen
Daniel S. Kirschen University of Washington

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