I should have loved electrical engineering

EE encompasses a lot of "engineering that takes hard math" at a professional and research level (similar to "hard CS," just different fields of math), so it is very hard to do as an undergrad, when your background in complex analysis and E&M is weak.

Early classes on circuits in EE will usually take shortcuts using known circuit structures and simplified models. The abstraction underneath the field of analog circuits is extremely leaky, so you often learn to ignore it unless you absolutely need to pay attention.

Hobbyist and undergrad projects thus usually consist of cargo culting combinations of simple circuit building blocks connected to a microcontroller of some kind. A lot of research (not in EE) needs this kind of work, but it's not necessarily glamorous. This is the same as pulling software libraries off the shelf to do software work ("showing my advisor docker"), but the software work gets more credit in modern academia because the skills are rarer and the building blocks are newer.

Plenty of cutting-edge science needs hobbyist-level EE, it's just not work in EE. Actual CS research is largely the same as EE research: very, very heavy on math and very difficult to do without studying a lot. If you compare hard EE research to basic software engineering, it makes sense that you think there's a "wall," but you're ignoring the easy EE and the hard CS.

> Actual CS research is largely the same as EE research: very, very heavy on math and very difficult to do without studying a lot.

That is largely true of academic research. A critical difference though is that you don't need big expensive hardware, or the like to follow along with large portions of the cutting edge CS research. There are some exceptions like cutting edge AI training work super expensive equipment or large cloud expenditures, but tons of other cutting edge CS research can run even on a fairly low-end laptop just fine.

It is also true that plenty of software innovation is not even tied to CS style academic research. Experimenting with what sort of perf becomes possible via implementing a new kernel feature, can be very important research but isn't always super closely tied to academic CS research.

Even the more hobbyist level cutting edge research for EE will have more costs, simply because components and PCBs are not exactly free, and you cannot just keep using the same boards for every project for several years like you can with a PC.