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base station switching control, user association, and routing, and localization
in the application layer

And trust me; this is just the tip of the iceberg. If you dig in a little further,
you may find that ML has applications in almost every course that you have

studied/ are studying.

So, there’s no need for you to leave your core branch in the race of doing
something in ML, but rather you can come out with project and research

with is an amalgamation of EC and ML. You just need to put on your thinking
hats, use your domain expertise, and of course, a little bit of ML, and who

knows, you may come out with solutions to conventional problems listed
above and many more.

Good luck and happy learning!
Waiting to see your accomplishments.

And I can’t be called an academician or researcher if I leave an article without

listing the references, so here it goes :)

References:
1. Elfadel, I. M., Boning, D. S., & Li, X. (Eds.), Machine Learning in VLSI Comput-

er-Aided Design. Springer, 2019.
2. Beerel, P. A., & Pedram, M., “Opportunities for machine learning in electronic
design automation”, IEEE International Symposium on Circuits and Systems (ISCAS), pp.
1-5, May 2018.

3. Sun, Yaohua, et al. “Application of machine learning in wireless networks: Key
techniques and open issues.” IEEE Communications Surveys & Tutorials, vol. 21, no. 4,
pp. 3072-3108, 2019.
4. Applications of Machine learning in wireless communications, IET Telecommu-

nications series, 2019. [Online]. Available: https://digital-library.theiet.org/content/
books/te/pbte081e
5. EE 5611: Machine Learning Applications for Wireless Communications. Available:
https://www.iith.ac.in/~asaidhiraj/ee5611_spring_2019.html

6. El Misilmani, Hilal & Naous, Tarek, “Machine Learning in Antenna Design: An
Overview on Machine Learning Concept and Algorithms”, 2019.

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