The day to day is basically like many of you have. I either code right away or sit down and scribble ideas in a paper. It usually ends coding those ideas and testing them in a "statistically sound way". We have different datasets against which we test the performance of the feature detection in many ways. We have to think of different dimensions. One is the accuracy, of course, so we need to have data that is annotated by humans and tell "how the algorithm does", but we consider other things, like time-performance or memory-performance. The idea is to bring these ideas to the point where they can be used by consumers. The industry requirements are very high, and also dependant on the requirements of the different projects. As you can imagine, there are design compromises. In some devices memory is very expensive, so you need to optimize for memory usage, in others accuracy is more important, in some others, time is the most important dimension...
When I sit on the electronics bench, I usually work with light sensors (a.k.a. cameras), illumination (visible and infrared) and as well sometimes modelling and 3D printing, as we move towards the prototyping.
Research is a highly creative work, and in my opinion, most of the times based on remixing ideas, though sometimes you need to come up with your own original approaches. Nonetheless, because my work is essentially related to software and hardware, my day to day is closer to office work than to what people could usually expect.
I ended up as a researcher because, after finishing my Master's degree, I was hired by the University as a research assistant. Now I have moved towards junior researcher while pursuing a PhD. To be honest, I did not deliberately choose this path, it was more of my final destination. :D
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What’s day-to-day like for a researcher?
What got you involved in this as opposed to applied computer science like many of us?
The day to day is basically like many of you have. I either code right away or sit down and scribble ideas in a paper. It usually ends coding those ideas and testing them in a "statistically sound way". We have different datasets against which we test the performance of the feature detection in many ways. We have to think of different dimensions. One is the accuracy, of course, so we need to have data that is annotated by humans and tell "how the algorithm does", but we consider other things, like time-performance or memory-performance. The idea is to bring these ideas to the point where they can be used by consumers. The industry requirements are very high, and also dependant on the requirements of the different projects. As you can imagine, there are design compromises. In some devices memory is very expensive, so you need to optimize for memory usage, in others accuracy is more important, in some others, time is the most important dimension...
When I sit on the electronics bench, I usually work with light sensors (a.k.a. cameras), illumination (visible and infrared) and as well sometimes modelling and 3D printing, as we move towards the prototyping.
Research is a highly creative work, and in my opinion, most of the times based on remixing ideas, though sometimes you need to come up with your own original approaches. Nonetheless, because my work is essentially related to software and hardware, my day to day is closer to office work than to what people could usually expect.
I ended up as a researcher because, after finishing my Master's degree, I was hired by the University as a research assistant. Now I have moved towards junior researcher while pursuing a PhD. To be honest, I did not deliberately choose this path, it was more of my final destination. :D