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I’m a physics major (for now) by Masha G. '24

feeling scholarly, part 2/2

Last week, I wrote all about the classes I took this past year. It was originally meant to be a one-off post, but in writing it, I found myself having a lot to say about the impact those classes have had on how I think about myself academically: what major I declared, what research I’m doing, what I think I might want to do with my life.

Back in September, in my very first blog post, I came up with an assortment of general topic areas I’m interested in exploring at MIT. From that ridiculous list, I feel like I’ve definitely refined some core themes. It’s largely as I expected: I’m still focusing on physics, CS, and earth science; though the earth science comes in through my research, and not through classes. This was very much supported by the physics and CS classes I took last year and how I felt about them. What was less expected, though, was how much I enjoyed my math classes. I was always planning on taking the classes that I took – those weren’t spur of the moment decisions – but I hadn’t really considered math as a subject in its own right, outside of its utility for physics and CS. I suppose I still don’t, since I’m not particularly interested in pure, abstract math. But I’ve started considering applied math in its own right, as a field I might be interested in.

 

Let’s talk about things in order, though.

Start with physics. I’ll spoil the punchline for you: I’m officially a course 8 major now. And yet, whenever I tell someone that I’m a physics major, I feel the need to somehow qualify the statement. Usually I’ll say, “oh but I’m a course 1201 Earth, Atmospheric, and Planetary Science at heart” in a mildly pleading tone. It’s not that I have anything against physics majors, it’s just that whenever I identify myself as one I feel like a) I’m giving myself too much credit and b) I’m misrepresenting my academic interests or associating myself with something I don’t feel that connected to. I know both of these are objectively invalid concerns, because, well, I am a physics major, but I really can’t help myself.

The thing is, I’m not actually interested in pursuing physics beyond my undergraduate degree. There’s a good chance that I’ll go to grad school, but it certainly won’t be for physics. I’m not interested in particle physics, cosmology, high-energy lasers, or any of the problems of contemporary physics.02 the possible exception being fluid dynamics, but even that is interdisciplinary enough that it's not exactly a field of physics in the traditional sense I love taking physics classes, sure. I love seeing the way the laws of the universe flow out of math equations, I love solving physics problems, I love the feeling of achievement when I develop an intuition for a new topic. I love taking physics classes enough that I can see myself taking a major’s worth of them. But ultimately, these classes probably won’t directly inform anything that I want to do in the future.

Now, let’s talk about CS.  I really enjoyed all the course 6 classes I took this year. This came as somewhat of a surprise, though at the same time it wasn’t a surprise at all. Although I came into MIT knowing how to code, I had never taken a formal class in anything related to CS, so I didn’t really know how I would feel about it. Turns out, I found my course 6 classes to be fun and engaging, even when they were hard. I find myself excited to take 6.00603 Intro to Algorithms in the fall, and 6.03604 Intro to Machine Learning next spring. Coming into MIT, I thought I might double major in 6-3, but I’ve more or less dropped the idea, since I’m not as excited about hardware and computer architecture as I am about programming and algorithms.

Finally, course 12. Since February, I’ve been working on a UROP05 research project about machine learning for weather prediction. Although so far I have mostly just been making graphs for the purpose of assessing forecast quality, working on this research has really helped me think about my interests and possible career/research paths in a new way. This project is exactly the kind of work I can see myself pursuing long-term: it lies perfectly at the intersection of weather/climate and computer science. Interestingly enough, although the topic (weather forecasting) is very much within the purview of course 12, the project itself has nothing to do with that department, but is instead housed through the MIT Quest for Intelligence, which focuses on applying machine learning to various problems across all disciplines. Most of the team members, including my UROP mentor, have backgrounds in computer science, not meteorology. And yet, the project has impacts directly in weather and climate prediction. Seeing this first-hand has reaffirmed my original plan of not specializing too early: I’d rather learn about tools (so, CS) than dive right into their applications. Since I’m certain that whatever path I ultimately choose will be computational in some way, I might as well take course 6 or even course 1806 Math classes for now, and then narrow my focus to their applications in climate science later on (in grad school, or in my choice of job). This would give me a deeper understanding of the techniques I use, in addition to more flexibility in terms of subject areas I can pursue later on. My mentor phrased this in a really nice way, I think: she said one fo the best pieces of advice someone had given her was to take classes in fields as high up the hierarchy of generality/applicability as you are comfortable with. I like that way of thinking about it.

two differently colored maps of the western US side by side

here’s a pretty graph from my UROP, with no context, just so you don’t have to stare at a full page of text. trust me, though, that it has things to do with weather forecasting

Which brings me back to math, kind of. Let’s just say I’m interested in pursuing weather forecasting or climate modeling long-term. This might change, this might not, but either way I’m going to stick to higher levels of generality for now. I enjoy taking CS classes, which are clearly helpful for those fields. I enjoy taking math classes, which form the basis for machine learning and statistics, which are tools I will inevitably be using. Plus, there’s just so much math that I want to know, apparently; I didn’t even think much of it before, but there’s a good number of classes that I just want to take for my own curiosity. It was this logic that suddenly made me consider declaring course 18C back in April, as I was staring at the major declaration form. 18C stands for “Math and Computer Science,” and it’s really flexible. In 18C, I would take a variety of course 18 and course 6 classes, and I could essentially choose what subfields I focus on.

Overall, some of the best advice I’ve gotten about choosing a major is to just take whatever classes I’m interested in, and see what that comes out to. Though 18C sounds great, I don’t think I’m ready to let go of physics just yet, despite it being less relevant to the career paths I see for myself. Course 8 also offers a flexible major, called 8-Flex, where I take fewer strict physics requirements and am instead able to count courses from other departments towards my major. I’m pretty sure I could only take one course 8 class per semester for the rest of my time at MIT and still fulfill all the requirements. As long as I stay interested in my physics classes, this can be enough. I’ll then be free to take other classes I’m interested in without the strict confines of major requirements.

This is exactly what the plan looks like right now. I’ll major in 8-Flex, with a minor in 6 and a minor in 18 or in data and statistics.07 an interdisciplinary minor that encompasses a lot of the math classes I'm curious about But there’s also a non-negligible chance that somewhere down the line, I’ll lose interest in higher-level physics, or I’ll find the classes too hard or not engaging enough, at which point I will easily switch to 18C because I’ll be taking so many of those classes anyway. All the while, I’ll keep doing research in course 12-adjacent fields, like climate, atmospheric physics, fluids, or weather prediction. I might also decide that I want to go more theoretical with my interests in forecasting or machine learning or fluid dynamics; then I’ll take more higher-level math and CS classes. I could double major, of course, with either course 6 or 18C, but why? If it comes to a difference of a couple of classes, maybe I’ll do it. But I’m not going to use the goal of getting a second major as a factor in making decisions.

  1. Earth, Atmospheric, and Planetary Science back to text
  2. the possible exception being fluid dynamics, but even that is interdisciplinary enough that it's not exactly a field of physics in the traditional sense back to text
  3. Intro to Algorithms back to text
  4. Intro to Machine Learning back to text
  5. research project back to text
  6. Math back to text
  7. an interdisciplinary minor that encompasses a lot of the math classes I'm curious about back to text