I found your profile through Reddit comments and came across this article just at the moment when Iâm feeling hesitant about my future career.
I live in Asia, and I first discovered operations research about 3 years ago when I faced a software development problem that actually needed to be solved as a MIP. I spent many days and nights trying to find a way to handle it within feasible time and with feasible computational resources. Eventually, I came up with an idea: solving it as an LP with a custom probability function. That experience was soooooo fascinating that I realized this is something I would love for the rest of my life.
However, it has been difficult to find more opportunities like that with only a bachelorâs degree in physics and work experience in software development. When I try changing jobs and get interviews, people mostly talk about AI. Some say optimization is just a niche field, and many donât even know what it isâthough I feel strongly that AI and optimization are deeply connected and can inspire each other.
Thatâs why Iâve decided to pursue a masterâs, or even a PhD, in this field. But in Asia, the closest programs I can realistically access are Industrial Engineering or Applied Mathematics, which donât carry the same recognition as CS or DS.
On top of that, being in my 30s makes me feel âtoo oldâ in the eyes of Asia culture, and even one of my friend with doctorates tell me that pursuing a PhD can make you sick.
Still, reading your article and especially the comment from your wife gave me courage.
I feel very fortunate to have found it. For me, the worst outcome is simply returning to software engineering if things donât work out. But if I never try, I will only ever remain a software engineer, hoping another chance that an NP problem come to my hand... and that would be the greater regret.
I love how that first MIP/LP experience 'hooked' you!
Maybe it's just a cultural difference, but you're not too old to start whatever path you want. In fact, your software background is a huge asset. Most optimization projects in industry need solid engineering skills as much as algorithms, so you already bring something many PhDs have to learn later.
Industrial Engineering or Applied Math are excellent entry points. The title matters far less than the skills and the problems you work on.
Whatever you choose, you're already doing something rare: listening to what excites you and acting on it. That's the hard part.
Wishing you the best on this path; please keep me posted on where it takes you!
Thank you so much for sharing your story.
I found your profile through Reddit comments and came across this article just at the moment when Iâm feeling hesitant about my future career.
I live in Asia, and I first discovered operations research about 3 years ago when I faced a software development problem that actually needed to be solved as a MIP. I spent many days and nights trying to find a way to handle it within feasible time and with feasible computational resources. Eventually, I came up with an idea: solving it as an LP with a custom probability function. That experience was soooooo fascinating that I realized this is something I would love for the rest of my life.
However, it has been difficult to find more opportunities like that with only a bachelorâs degree in physics and work experience in software development. When I try changing jobs and get interviews, people mostly talk about AI. Some say optimization is just a niche field, and many donât even know what it isâthough I feel strongly that AI and optimization are deeply connected and can inspire each other.
Thatâs why Iâve decided to pursue a masterâs, or even a PhD, in this field. But in Asia, the closest programs I can realistically access are Industrial Engineering or Applied Mathematics, which donât carry the same recognition as CS or DS.
On top of that, being in my 30s makes me feel âtoo oldâ in the eyes of Asia culture, and even one of my friend with doctorates tell me that pursuing a PhD can make you sick.
Still, reading your article and especially the comment from your wife gave me courage.
I feel very fortunate to have found it. For me, the worst outcome is simply returning to software engineering if things donât work out. But if I never try, I will only ever remain a software engineer, hoping another chance that an NP problem come to my hand... and that would be the greater regret.
Wow, thank you for sharing so openly.
I love how that first MIP/LP experience 'hooked' you!
Maybe it's just a cultural difference, but you're not too old to start whatever path you want. In fact, your software background is a huge asset. Most optimization projects in industry need solid engineering skills as much as algorithms, so you already bring something many PhDs have to learn later.
Industrial Engineering or Applied Math are excellent entry points. The title matters far less than the skills and the problems you work on.
Whatever you choose, you're already doing something rare: listening to what excites you and acting on it. That's the hard part.
Wishing you the best on this path; please keep me posted on where it takes you!