I think this post is on the money! I’ve proactively created a tag for operations research; feel free to add any information you think would be useful to have on the wiki entry.
I went to Cornell, and (as you state) operations research is one of the majors offered in the engineering school, but I never took any OR classes because I wrongly assumed they would be too dry and difficult. But in retrospect, I think that taking even a whirlwind tour of OR would have been incredibly insightful for me. We have an ML engineer on my team at work who was using mixed-integer programming (or something like that) for model selection.
Thank you for creating the tag! I was also a CS major at Cornell who actually only took the intro OR class (which was great but my impression is that undergrad ORIE at Cornell is not taught efficiently otherwise).
As for your suggestions
Emily Tucker has nice list of broadly useful resources for academic OR but this could probably be improved for an EA audience
This is a great idea!
The open-source solvers are way behind the commercial ones in terms of performance so I am skeptical this has high EV. AFAICT, much of Gurobi’s licensing is customer specific, so I suspect non-profit orgs could get a steep discount if not a free license.
Jumping in on this comment thread: I would LOVE to see a collection of resources for self-teaching, either in the form of a well-organized syllabus if possible, or simply thrown together as a list with a short description of each resource. I’ve always felt bad that so much knowledge appears “locked” behind academia, and I am not able to access that knowledge (unless I have a GRE and a few recommendation letters and a 40,000 USD and two years to commit to the learning).
I think this post is on the money! I’ve proactively created a tag for operations research; feel free to add any information you think would be useful to have on the wiki entry.
I went to Cornell, and (as you state) operations research is one of the majors offered in the engineering school, but I never took any OR classes because I wrongly assumed they would be too dry and difficult. But in retrospect, I think that taking even a whirlwind tour of OR would have been incredibly insightful for me. We have an ML engineer on my team at work who was using mixed-integer programming (or something like that) for model selection.
I have some suggestions for next steps:
Compile a list of open-source OR tools (such as spark-or, which integrates with Spark, and these libraries for Python).
Do a workshop at a future EA Global or EAGx where you walk through an example OR problem related to EA, preferably with live coding.
Volunteer to improve open-source OR libraries (possibly for pay) and fund their development, aiming for parity with the commercial ones.
Thank you for creating the tag! I was also a CS major at Cornell who actually only took the intro OR class (which was great but my impression is that undergrad ORIE at Cornell is not taught efficiently otherwise).
As for your suggestions
Emily Tucker has nice list of broadly useful resources for academic OR but this could probably be improved for an EA audience
This is a great idea!
The open-source solvers are way behind the commercial ones in terms of performance so I am skeptical this has high EV. AFAICT, much of Gurobi’s licensing is customer specific, so I suspect non-profit orgs could get a steep discount if not a free license.
Jumping in on this comment thread: I would LOVE to see a collection of resources for self-teaching, either in the form of a well-organized syllabus if possible, or simply thrown together as a list with a short description of each resource. I’ve always felt bad that so much knowledge appears “locked” behind academia, and I am not able to access that knowledge (unless I have a GRE and a few recommendation letters and a 40,000 USD and two years to commit to the learning).