基本信息
views: 143
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Dr. Jean-Paul Watson is a member of the Analytics Department, and has been a member of this department or a previous version of this department since starting at Sandia in 2003. He has over 15 years of experience applying and analyzing algorithms for solving difficult combinatorial optimization and informatics problems, in fields ranging from logistics and infrastructure security to power systems and computational chemistry. His research currently focuses on methods for approximating the solution of large-scale deterministic and stochastic mixed-integer programs, with applications in the domain of electricity grid operations and planning. He presently leads projects at Sandia for DOE ARPA-e (stochastic unit commitment), DOE OS/ASCR (optimization for the power grid), and LDRD (quantifiable and rigorous power grid operations and planning). Previously, he developed solutions for real-world stochastic optimization problems in logistics (Lockheed Martin and the US Army) and sensor placement (US Environmental Protection Agency). Additionally, he led the development of programs involving the use of semantic graph technologies for performing geospatial imagery analysis. He is a co-developer of Sandia's Coopr (https://software.sandia.gov/trac/coopr) open-source software package for modeling and solving optimization problems, and has published over 25 journal articles in the areas of optimization algorithms and their application. Prior to graduate school, he worked at IBM in Austin, Texas working on VLSI design - specifically for the PowerPC family of chips -- and at Hughes Information Technology Corporation in Aurora, Colorado working on satellite systems. He received his PhD in Computer Science from Colorado State University in 2003.
Research Interests
Papers共 212 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
arxiv(2024)
Cited0Views0Bibtex
0
0
CoRR (2024)
Cited0Views0EIBibtex
0
0
Operations Research (2023)
INFORMS J. Optim.no. 2 (2023): 172-190
OPERATIONS RESEARCH (2023)
Pyomo — Optimization Modeling in Pythonpp.29-45, (2021)
Load More
Author Statistics
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn