Update README.md and doc with development lead from Binghamton Univ (#…

…779)
GenXProject · Dec 4, 2024 · faaf58a · faaf58a
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diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "GenX"
 uuid = "5d317b1e-30ec-4ed6-a8ce-8d2d88d7cfac"
 authors = ["Bonaldo, Luca", "Chakrabarti, Sambuddha", "Cheng, Fangwei", "Ding, Yifu", "Jenkins, Jesse D.", "Luo, Qian", "Macdonald, Ruaridh", "Mallapragada, Dharik", "Manocha, Aneesha", "Mantegna, Gabe ", "Morris, Jack", "Patankar, Neha", "Pecci, Filippo", "Schwartz, Aaron", "Schwartz, Jacob", "Schivley, Greg", "Sepulveda, Nestor", "Xu, Qingyu", "Zhou, Justin"]
-version = "0.4.1-dev.17"
+version = "0.4.1-dev.18"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"

diff --git a/README.md b/README.md
@@ -13,7 +13,7 @@ that incorporates several state-of-the-art practices in electricity system plann
 The model was [originally developed](https://energy.mit.edu/publication/enhanced-decision-support-changing-electricity-landscape/) by 
 [Jesse D. Jenkins](https://mae.princeton.edu/people/faculty/jenkins) and 
 [Nestor A. Sepulveda](https://energy.mit.edu/profile/nestor-sepulveda/) at the Massachusetts Institute of Technology and is now jointly maintained by 
-[a team of contributors](https://github.com/GenXProject/GenX#genx-team) at the Princeton University ZERO Lab (led by Jenkins), MIT (led by [Ruaridh MacDonald](https://energy.mit.edu/profile/ruaridh-macdonald/)), and NYU (led by [Dharik Mallapragada](https://engineering.nyu.edu/faculty/dharik-mallapragada)). 
+[a team of contributors](https://github.com/GenXProject/GenX#genx-team) at the Princeton University ZERO Lab (led by Jenkins), MIT (led by [Ruaridh MacDonald](https://energy.mit.edu/profile/ruaridh-macdonald/)), NYU (led by [Dharik Mallapragada](https://engineering.nyu.edu/faculty/dharik-mallapragada)), and Binghamton University (led by [Neha Patankar](https://www.binghamton.edu/ssie/people/profile.html?id=npatankar)).
 
 GenX is a constrained linear or mixed integer linear optimization model that determines the portfolio of electricity generation, 
 storage, transmission, and demand-side resource investments and operational decisions to meet electricity demand in one or more future planning years at lowest cost,

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -9,7 +9,7 @@
 
 GenX is a highly-configurable, [open source](https://github.com/GenXProject/GenX/blob/main/LICENSE) electricity resource capacity expansion model that incorporates several state-of-the-art practices in electricity system planning to offer improved decision support for a changing electricity landscape.
 
-The model was [originally developed](https://energy.mit.edu/publication/enhanced-decision-support-changing-electricity-landscape/) by [Jesse D. Jenkins](https://mae.princeton.edu/people/faculty/jenkins) and [Nestor A. Sepulveda](https://energy.mit.edu/profile/nestor-sepulveda/) at the Massachusetts Institute of Technology and is now jointly maintained by [a team of contributors](https://energy.mit.edu/genx/#team) at the Princeton University ZERO Lab (led by Jenkins), MIT (led by [Ruaridh MacDonald](https://energy.mit.edu/profile/ruaridh-macdonald/)), and NYU (led by [Dharik Mallapragada](https://engineering.nyu.edu/faculty/dharik-mallapragada)). 
+The model was [originally developed](https://energy.mit.edu/publication/enhanced-decision-support-changing-electricity-landscape/) by [Jesse D. Jenkins](https://mae.princeton.edu/people/faculty/jenkins) and [Nestor A. Sepulveda](https://energy.mit.edu/profile/nestor-sepulveda/) at the Massachusetts Institute of Technology and is now jointly maintained by [a team of contributors](https://energy.mit.edu/genx/#team) at the Princeton University ZERO Lab (led by Jenkins), MIT (led by [Ruaridh MacDonald](https://energy.mit.edu/profile/ruaridh-macdonald/)), NYU (led by [Dharik Mallapragada](https://engineering.nyu.edu/faculty/dharik-mallapragada)), and Binghamton University (led by [Neha Patankar](https://www.binghamton.edu/ssie/people/profile.html?id=npatankar)). 
 
 GenX is a constrained linear or mixed integer linear optimization model that determines the portfolio of electricity generation, storage, transmission, and demand-side resource investments and operational decisions to meet electricity demand in one or more future planning years at lowest cost, while subject to a variety of power system operational constraints, resource availability limits, and other imposed environmental, market design, and policy constraints.