Courtesy : imperial.ac.uk
Innovation is strongly entwined with mathematics. From ideas to proof of concept, implementation and real-world use, mathematics plays a role in every innovation journey.
Even the process of innovation itself, although a bit of mystery how it happens, follows a set of patterns which have been mathematically modelled to study the interplay between the actual and the possible. Scientists at Iprova, have already used machine learning and NLP to create tools that speed up the process of innovation.
In medicine, energy, quantum, AI, transport and agritech to name just a few fields, mathematics is key to creating new technologies, products or services. Even Quantum 2.0 presents many mathematical challenges relating to optimisation, device miniaturisation, stabilisation, efficiency, error correction and so on.
An innovation cycle, in its simplest form, starts with “identifying a need” and aims to “develop, implement or roll out a new service or a new product”. As mathematicians, we start by “defining a problem” and work to “derive a solution”. In some innovation projects these two cycles overlap. A first step is to translate the “innovation question” into a mathematical problem. A later step is turning a mathematical solution into an actual innovation.
As a mathematician you may be curious about:
- Further applications of your research or
- Translating your insights into a product or a service or
- Developing a solution to one of the many problems that need solving in the world today, e.g. Problems and more problems
- Innovation or entrepreneurship but are not clear how to apply your research or insights to these problems.
- You may already have a brilliant idea but not sure how to proceed.
But this is just the begining, because there is no “solve for x” in the real world.
If you are interested in learning more please get in touch or sign up for the Mathematics for Innovation Workshop series where we will explore topics such as:
- Entrepreneurship for mathematicians
- The role of mathematicians in innovation
- Solving real world problems
- Working as a mathematician in industry
- Skills and opportunities
- Applications of your research
- How to translate your research into an innovative solution.