MATLAB

MATLAB, short for “matrix laboratory,” is a numerical computing programming language and environment widely used in engineering, science and finance for working with matrices, analyzing data and developing algorithms. Created by mathematician and computer scientist Cleve Moler in the late 1970s while he was a professor at the University of New Mexico, MATLAB began as a simple way to give students easier access to Fortran numerical libraries without having to write Fortran code directly.

From academic tool to commercial product

Moler’s original MATLAB was written in Fortran and ran on minicomputers available to university researchers. In 1984, Moler co-founded MathWorks, the company that has developed and sold MATLAB commercially ever since, turning what began as a teaching aid into one of the most widely licensed engineering software products in the world. MathWorks has continued to expand MATLAB’s capabilities over the following decades, adding toolboxes for specific fields such as signal processing, control systems, image processing and machine learning.

What MATLAB is used for

MATLAB’s core strength is performing matrix and vector operations without requiring a programmer to write explicit loops, which makes it well suited to tasks like linear algebra, statistical analysis, signal processing and numerical simulation. Engineers, scientists and quantitative analysts use MATLAB to prototype algorithms quickly, visualize data through built-in plotting tools, and build and test mathematical models before deploying a finished system in a different programming language if needed.

MATLAB and Simulink

Simulink is a companion product built on top of MATLAB that provides a graphical, block-diagram environment for modeling, simulating and analyzing dynamic systems, such as the behavior of a vehicle’s control system or an electrical circuit over time. Rather than writing MATLAB code directly, a Simulink user builds a model by connecting visual blocks that represent different system components, and Simulink uses MATLAB’s underlying numerical engine to run the simulation.

Who uses MATLAB today

MATLAB remains especially popular in academic engineering departments, where it is often taught as a standard tool for coursework in subjects like control systems, signal processing and numerical methods, as well as in industries such as aerospace, automotive and semiconductor design, where companies use it for algorithm development and testing before implementing finalized systems in production code.

MATLAB in education and industry today

Decades after its creation, MATLAB remains deeply embedded in university engineering curricula, where it is frequently taught alongside foundational courses in subjects like signal processing, control theory and numerical methods, giving generations of engineering graduates early familiarity with the language. In industry, companies in aerospace, automotive, semiconductor and finance continue to rely on MATLAB for algorithm prototyping and testing, often alongside newer open-source alternatives like Python, which has grown as a competing option for some of the same numerical-computing tasks.

FAQs

Who created MATLAB? MATLAB was created by mathematician and computer scientist Cleve Moler in the late 1970s, originally to give university students easier access to Fortran numerical libraries.

Who makes MATLAB today? MathWorks, the company Cleve Moler co-founded in 1984, develops and sells MATLAB commercially.

What does “MATLAB” stand for? MATLAB stands for “matrix laboratory,” reflecting its original design around matrix and vector mathematical operations.

What is the difference between MATLAB and Simulink? MATLAB is a text-based programming language and environment, while Simulink is a graphical, block-diagram tool built on top of MATLAB for modeling and simulating dynamic systems.

Is MATLAB free to use? No; MATLAB is commercial software sold by MathWorks under paid licenses, though many universities provide student licenses, and a free alternative called GNU Octave offers similar syntax for some of the same matrix-based computing tasks.

Editorially reviewed by Specialty Digest Editorial TeamLast reviewed November 9, 2026Researched and drafted with AI assistanceReport an issue