3 years into Ph.D.

I started my Ph.D. in Fall 2020. With the beginning of the Fall trimester in 2023, I have finished 3 years at Polytechnique Montreal. There were many things in my mind related to research and publications when I started my Ph.D. in 2020. Some of them went as planned. I also learned a few things that I didn’t plan. In this post, I discuss how things turned out and compare it to my expectations at the beginning of my Ph.D. I also discuss what I plan to do in my next year of Ph.D.

Academics

One of the main reasons to start my Ph.D. was to strengthen my theoretical knowledge in operations research. In the first year of Ph.D., I had to take five courses. Unfortunately, at Polytechnique, most of the courses are in French. That limited my choices. Two of the five courses I took were utterly useless. I already knew most of the topics taught in those courses. Unfortunately, I realized that after taking the classes.

Out of five courses, two of them were not operations research related. I must admit that I learned more in those courses than in the operations research courses. I took one course on Machine Learning at Poly and One course on Advanced Theory of Computation (because of curiosity) at McGill. Later in my second year, I audited a course on Reinforcement Learning, which was also helpful in part of my research work.

There were also some mini-courses called CAP workshops. Four CAP workshops are mandatory for all Ph.D. students. Three of them do not serve any purpose. Other optional CAP workshops are somewhat more helpful. One example is the workshop on teaching engineering.

Overall, taking courses at university to improve my theoretical knowledge in operations research was not so beneficial. I learned most of what is needed for my research from other sources. Continuing that approach, I am now learning new things by reading papers or taking free online courses on topics I am curious about. I also realized that I don’t need to understand most concepts in operations research to conduct effective research. Mastery of a selected few topics is sufficient.

Research topic

I looked back at the statement of purpose (SOP) I wrote while applying for Ph.D. programs. In that document, I proposed some potential areas of research. My research topic is not related to any of them. I lightly touched one of those topics through a MIP competition, and it will make it into my thesis.

My research topic is on a completely different branch of operations research called column generation. I did not know much about it at the beginning of my Ph.D. But, after working on it for a while, it seems like a fascinating area for research. It is not so different from the work I planned to do.

Skills

One primary reason to start a Ph.D. was to learn how to publish my work. I have published one paper and submitted two more recently. The publication process is usually long. I improved at formal writing and organizing my research because of the publication part. So clearly, this part is going just as I expected.

I also wanted to learn more about the jobs in academia. I have a better idea about different kinds of jobs and related expectations. I also learned some politics going around in academia. Most of that is driven by issues related to money. I may write about it in other posts.

Finances

When I started my Ph.D., I knew that I was taking a significant pay cut. I thought I was prepared for it. But then inflation hit hard in 2022-23. Everything became more expensive. But my stipend did not increase at all. This year, I learned that Ph.D. students in Canada (particularly Quebec) are paid a stipend lower than minimum wage. On Labor Day, there was a student body protest march about this in Montreal. This payment in pennies is one of the key drivers for me to finish my Ph.D. as early as possible.

One good thing about low payments is that it drove me to study personal finances and investments. I took a few online courses and read many books related to finance and investment. I invested some of my cash savings from my previous job to make it produce better returns.

What next?

I have nearly enough content per the Polytechnique guidelines for the Ph.D. thesis. I am working on a few experiments for my last project. I am about to start writing my thesis and will target to defend it in the Winter or Summer trimester of 2024.

Regarding the jobs, I will be applying for jobs in both industry and academia. For the industry jobs, I will primarily prioritize working on optimization solvers. Other operations research and software engineering jobs will be next on the priority list. Thanks to the recent conferences, I now have some visibility in the community, which will make the application process easier. I will start applying early next year.

For jobs in academia, I will prioritize business schools. The balance between research and teaching is more suitable for me in business schools than in engineering schools. I will also have better opportunities to learn about finance and business management there. From what I understand, the applications at these schools have deadlines in September. I will only start applying to these positions a little later next year. If by then I already have a job, I prefer to stay in that for a year or two before applying to academic job positions.

The lowest priority will be postdoc positions. Some people don’t even call them jobs. In my opinion, these are more like extensions of low-paying Ph.D. positions. Postdocs typically work for some supervisor just like they do in their Ph.D. There is no degree to get at the end of it. And the payment is far below what any other jobs offer.

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