MICCAI 2023 Daily - Tuesday

31 DAILY MICCAI Tuesday Mirabela Rusu [hesitates for a moment] Hmm, my message to the world would be, first of all, if you're a young trainee, and you're trying to figure out whether science in academia or science in industry is your path, follow your gut. If you feel like that's the path you want to go, go with it. Don't get too distracted by other voices. Mentors are very useful in this. But sometimes I find mentors always providing advice that is useful from their perspective, not yours as a trainee. So, I have gone against the advice of many mentors many times over the career that I have, and I don't regret it one single time. One of them was a postdoc, and I decided to go into industry for three years. I was told, don't go to industry. I said I'm going to industry. Don't go to this company. I decided to go to that company. I got a lot of other ones, such as don't go into medical imaging, and I went into medical imaging. So I advise every trainee to make their decisions based on what they feel they want to do, even if other people are advising them in a different direction. Understand their perspective and understand their positive points, but move on with their own gut and feelings. One of the things that I wanted to do was to go to the industry because I thought I needed to go a little bit on the dark side. I don't think the industry is really the dark side, at least not anymore. But it's an interesting perspective. So I did that, too, and I understood the challenges of both worlds. I still came back as a professor at Stanford. Some people trusted that I could do this job, even though I come from an industry position, I'm feeling okay doing it. I feel like I am accomplishing something. Today, I just gave a keynote for one of the workshops. It's a big step. So follow your gut and go wherever you feel, whether that's industry or academia. Don't close your doors. Try to keep them open as you are doing it, and then let's see how we can do good with this AI approach. Ultimately, that's all that matters. They're very powerful. We have data and skills that are unique and can be used for the better, so why not use them?

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