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Tough choice: PhD in Operations Research: Northwestern vs Georgia Tech


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Hi, I am an international student who received PhD offers from Northwestern IEMS and Georgia Tech ISyE (Operations Research) and I wish to know your thoughts about these 2 p rograms.

I think these are the only choices I am considering right now.

My research interests would include optimizaiton, especially distributed optimization with applications in machine learning, high-dimensional probability and applied praobability stuff including reinforcement learning and online optimization. I come from a math and statistics backgrond, so I would prefer projects related to data, unceratainty, or probability.

For industrial jobs, I assume both can give me a good shot for opporutnies in sillicon valley or commercial banks as either a software engineer, data scientist or research scientist. I think Northwestern could better help me land a quantitative researcher job in a hedge fund in Chicago or NYC as well, as compared to Georgia Tech, mainly due to the reputation of Kellogg.

As for placemment in academia, I have heard rumors that in general, the variance of placement of Georgia Tech ISyE is very large due to large cohort size. I was told that IEMS students can easily find advisors from Kellogg, which should be great.

I prefer to go to academia, but if it does not work, I will probably find a job in industry in the US.

The main pro for Georgia Tech is its reputation in engineering and computer science, but I do not know how important it is.

I would love to hear more advice from your side. Many thanks!


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Hi, I got into both programs as well (ML program in the IsYE department). For Georgia Tech's academic placements, the variance largely dissapears once you control for advisors. I'm would check the placement of the alumni who graduted under the advisors you'd be interested in working with as well as how many students those professors are taking.

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