Most and least competitive areas for EECS

[doge89]

Lets try to map out which paths in EE and CS are the more and less beaten ones. Anecdotal and concrete evidence (such as enrollment numbers, etc) are all welcome.

From what I've gathered so far, looking at enrollment numbers in my department and from talking to people: taking into account both saturation and competitiveness I'd say it goes somewhat in this order:

1. ML / AI / Theory: Due to all the marketing it gets, buzzwords like data science and CS being popular in general. Attracts high volume of smart people in addition to all the wannabes.

2. Digital Signal Processing / Info Theory / Comms: I've heard its a fairly mature field where all the low hanging fruits are gone. Attracts brilliant math people who typically know what they're doing because its a make it or break it field.

3. Embedded / Networking / Distributed: CLOUD COMPUTING IOT IOT CLOUD THE CLOUD!!... did I mention CLOUD COMPUTING?!?!

4. HCI: Ditto, anecdotally speaking its very popular. People uninterested in theory or math tend to drift here.

5. IC Design / Circuits: Most EEs were introduced to EE through circuits after all. But hardware tends to be less popular.

6. Nanotechnology: Could be very niche, or have huge numbers of interested bioengineering people / demonic premeds?

7. Electromagnetics / Photonics: Most undergrads don't even know what photonics is, highly niche so = relatively low competition?

8. Microelectronics / Devices: In my department at least, solid state devices is easily the most hated class in the curriculum that everyone wants to get over with and forget.

I need more information on these topics however:

High Performance Parallel / Scientific Computing / Computational Science and Engineering

Computer Architecture

Optimization / Controls

Remote Sensing

NEMS / MEMS

Inputs are appreciated! If this thread gets going, I'll have other things to add.

 

[Edotdl]

I would put Comp Arch/Parallel computing near embedded systems, Optimization near DSP/Info theory, remote sensing near networking and circuits, and MEMs near Nanotech. Just my opinion though. 

[compscian]

I'm more familiar with the EE (or EECS if I can say) side of things as opposed to pure CS areas. My reading is pretty similar to yours. In decreasing order of competition.

1. Machine learning and related areas like computer vision, NLP, speech, and general data science are the most competitive. From my experience, these also provide the most lucrative post PhD outcomes -- especially in the industry.
2. The signals & systems side of EE -- optimization, info theory, comms, control, DSP, compressed sensing. This attracts the mathematically minded folks who want to work on theoretical questions and stay in academia. Some of the more practical ones might jump ship to (1) above; and separation within these areas in (2) is wafer thin. Industry lags behind theory by at least a decade or two, and hence jobs meaningful of your research is hard. As you said, it's make it or break it -- professor or bust (or jump ship to data science band wagon).
3. IoT, embedded systems -- possibly the next big thing.
4. Computer Arch, High performance computing, HCI
5. After this, I think (5), (6), (7), (8) in your list is quite accurate.