My main motivation to start a Ph.D. was the thirst for knowledge, I wanted to learn more about science and technology. Surprisingly, the most important lessons are the ones that taught me something about myself. Below are some comments on the unexpected lessons or challenges that I faced during my Ph.D.
Risk Management
The Ph.D. was the first time I needed to take choices based on intuitions and that would have an important impact on my work. Should we explore question A or question B? Can we solve problem X using this approach/tool?
Choosing a research problem has some similarities with investment: the greater the risk, the greater the potential reward. For research, the risk is not finding a solution in a reasonable amount of time. The reward is the impact that your research has.
All in all, when making decisions I needed to take into account the limited time, resources and information I had. The experience and feedback of my advisors were crucial in those situations.
Humility
Like a lot of people who end up doing a Ph.D., I was “a good student”. However, as Paul Graham explains in his essay, the school system “gives you a misleading impression of what work is like”. Once you master the algorithm to have good grades (study the lessons, do a bunch of exercises, and pass the exam), you get a false sense of control. Sadly, there is not a magical algorithm for good work, especially in research. The solution to a research problem can not be found in a textbook; otherwise it would not be a research problem in the first place. It was the first time I could not brute force my way to solve the question at hand only with hard work. I needed a good idea…
This is when humility comes. Once you realize how hard and how difficult it is to have a new and good idea, you start listening more closely and easily accept the feedback from your advisors and colleagues. You also start to realize that it is normal not to get the right answer instantly, which brings me to iteration.
Embracing Iteration
By reading a lot of papers and seeing the evolution of research projects, I realized that every great result started small. This realization was very comforting because it is very different from how the school system works. In school, the student is expected to know the answer to the problems he is given right away. If he does not know the answer, it is his fault. Research works very differently. In research, you do not know if the problem you are working on has a solution, nor if it is the right problem to work on. So you try something and see what happens. If it does not work, you either change your approach, tools, or even the question you are working on1. It is by nature an iterative process, failure is just a step to success. Strangely enough, failure can be a good sign. It means that the problem is harder than you thought, which makes it an even more interesting research problem and a new opportunity.
The Devil Is in the Details and Feedback Loops
“The first principle is that you must not fool yourself and you are the easiest person to fool.” – Richard P. Feynman
It is extremely important to be methodical and pay attention to all the details, especially if something bothers you. It is better to convince yourself that what you are doing now is correct than to redo all your work three or six months later because you discovered some mistake.
Feedback loops are a good way to avoid these situations. Common feedback loops are your advisors and colleagues which you should not hesitate to talk to. Besides, what worked for me as a “personal feedback loop” was to write things down. Some people prefer to talk, like developers who sometimes talk to rubber ducks to debug their code.
Research, Art, and Innovation
Research in engineering is very different from other scientific fields. In engineering creativity plays an important role:
“Scientists discover the world that exists; engineers create the world that never was.”
– Theodore Von Karman
By being confronted to create something new, I better understand the difficulty and courage needed by artists and innovators to create.
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Changing/refining the question might feel like “cheating”, but it actually means that you are understanding better the scope and limits of your work. ↩︎