Services

“We read the papers, so you don’t have to” - Dr Craig Brown"

Consulting

Dr. Craig Brown EngD MEng MIET AMIChemE is a simulation and algorithms veteran with over 13 years of experience.

Recently, he was responsible for motion and cueing development for the McLaren-MTS Vehicle Dynamics Simulator. Subsequently, as a principal engineer at Toyota and founding member of Toyota Gazoo Racing Simulation UK, he was responsible for the development of an international portfolio of state-of-the-art motion simulators. He helped found the influential modeling and simulation department at Worcester Bosch Thermotechnology whilst completing his thesis on the application of machine learning (recurrent neural nets) to engineering control problems (renewables). He was support lead at dSPACE UK, helping many well-known OEM’s and Tier 1’s achieve their objectives in the domain of real-time simulation. He is a published author with over 50 citations.

Now, he is director of BrownSim, an engineering services provider whose mission is to help companies to maximise returns from their simulation & digital twin activities.

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Outsourcing

With our partners in Vietnam, we can build a hardened scientific software, data and simulation team at a competitive cost. All activities are overseen by Dr Brown. We offer outsourcing on an augmentation or project basis.

High quality source code for solving engineering challenges.
Capabilities
Scientific simulation

Traditional scientific simulation emphasising the application of traditional laws and well understood empirical relationships. Anticipate design challenges earlier in your development cycle saving costs and time.

Automation in an advanced scientific facility.
Digital twins

A less traditional simulation approach which may also be applied to non-scientific applications with an emphasis on real-time interactivity and synchronicity with a company’s data streams. A highly valuable decision-making aid.

Engineer reviews the output of some scientific simulations.

Data Science & Machine Learning

Whereas the scientific method seeks universal generalisation, machine learning seeks only generalisation that is “sufficient” for a given domain. This lends its application to “non-traditional” modelling problems such as recommender systems, chat bots, etc…

Artificial intelligence, machine learning and data science in a human form.
Software Development

Advanced technical capability is rendered useless without an intuitive user experience. We view the above topics as specialisations within the software field, rather than a separate discipline. Thus, our integrated approach can take experimental software through to client facing production code.

Typing up some code.
Our principles
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Innovate When Necessary

We avoid reinventing the wheel and ensure the prior art is exhausted. The most exciting innovations are built on a solid foundation.

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Comprehensibility First

We prioritise certainty. Statistical approaches are helpful in situations with hidden variables and genuine uncertainty.

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Quality

“Proof of concept” does not have to mean low quality. We work assuming commercialisation is just over the horizon.

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Contrarian

We are not afraid to challenge the dogma of the day, if it produces an advantage.

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Empirical

We focus on what’s true in practice rather than esoteric theory.

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Responsive

We are active listeners and believe the “qualitative” is as valuable as the “quantitative”.