One lesser known feature of Julia is multiple dispatch, which allows you to define functions with the same name but different argument types. This enables highly expressive and flexible code, as you can write generic functions that can handle different data types.

Another lesser known feature is Julia's ability to directly call C and Fortran code without any boilerplate or wrapping. This makes it easy to use existing libraries and leverage their performance within your Julia codebase.

Additionally, Julia has built-in support for parallel computing, making it easy to write code that takes advantage of multiple processors or even distributed clusters. This can significantly speed up computation times when working with large datasets or computationally intensive tasks.

Julia also has powerful metaprogramming capabilities, allowing you to generate code dynamically based on program structure or data. This can be particularly useful for automating repetitive tasks or optimizing code based on specific problem instances.

Lastly, Julia has a rich ecosystem of packages available through its package manager. These packages cover a wide range of domains and provide ready-to-use solutions for various problems. Exploring and utilizing these packages can greatly enhance productivity and save development time.