What can data-driven mathematical modelling do for you?
Data-driven mathematical modelling, provide efficient and elegant solutions to a vast space of problems ranging from understanding the evolution and composition of the universe to that of the mechanisms responsible for the emergence of life. Among the many aspects of the scientific and industrial problems, mathematical modelling combined with data-science can particularly:
improve experimental accuracy of a process
discover the physical laws, and predict the dynamical behaviour of an evolving phenomenon
acquire visual and imaginative magnification for understanding the underlying processes of a data-driven system
achieve quantitative authority for modular control of a process both on micro and macro scale
increase your chance to secure projects of any magnitude by modelling and data-driven quantitative arguments within your proposal
can provide solution irrespective of the modeller's previous experience to be substantial in the topic
This is the simulation of a Mathematical Model for DNA packaging and chromosome formation. DNA molecules are negatively charged and therefore the strand wraps around the positively charged molecules of proteins called histone. The work and energy required for the action of packaging and twisting is the electrostatic force between the proteins molecules and DNA.
The simulation of a mathematical model to explore the geometric influence of domain on the evolution of pattern on a flat ring
Pattern formation on a sphere achieved by the interference of travelling waves from a single line of source with bilinear longitudinal and latitudinal directionality
INNOVATIVE MATHEMATICAL MODELS MAKE
ACHIEVING GROWTH EASIER
both in science and industry
You are a suitable candidate for our services, if you have data at hand and are willing to accommodate novel data-driven mathematical and computational approaches as a part of your strategy to either achieve growth or gain deeper scientific insight on the underlying mechanism of the phenomenon you are dealing with.
Here you will find a small number of example projects to give you a taste of the type of problems our expertise have dealt with in the past. You are encouraged to get in touch with us, regardless of finding the relevant project in the list uploaded here. Note that professional mathematical modelling can provide solution to your problem irrespective of the consultant's previous experience in the subject area of the problem itself.
MMCESP because of the nature of the subject is most certainly not restricted to a particular class or type of projects, which entails a great diversity in the types of possible clients we anticipate to have. Whatever business or company you want to solve a problem for, you are welcome to contact us for enquiries. If visiting this web-page could plant the possibility in your mind that MMCESP could be a place to look for solution, send us an email.
MMCESP is a commercial but deeply scientific platform founded in ©2019 with the main objective to offer data-driven solution services for industrial and scientific problems by the use of contemporary applied mathematics combined with data science and state of art machine-learning applications. We serve to develop and simulate novel mathematical models that are supported by data-driven techniques and employ these to solve problems arising in areas of their immediate and rightful applications both for the commercial and scientific industries. We offer the skills and specialised team of expertise within a global network of experienced contacts that can tackle problems arising in computational weather prediction, biotechnology, agricultural prediction, soil science, financial industry, aerospace industry, pharmaceutical industry and many more.
The conventional criteria for reward and success within the majority of academic institutions worldwide operate almost completely independent from the way such criteria are set out in the non-academic and industrial sectors (both private and public). This lack of sufficient dependence leads to accumulating long-term consequences, which ultimately impose a limitation on public accessibility for collaboration across the expanding frontiers of data science and applied mathematics with the creative world of entrepreneurship. MMCESP particularly serves to reduce the space between the commercial world of entrepreneurship and the intellectual frontline of academic research especially in areas of data science, machine learning, AI and other areas of applied mathematics. We are consistently determined to pave a much easier and interactive path through this commercial platform for the ambitious and creative individuals or companies to make the most of their creativity, talent and investment without the necessity for connections and formalities required for a conventional collaboration.
About the team:
Information to be updated:
In spite of our awareness about a small number of companies that practice commercialization of modern research in applied mathematics, we believe enough is not being done towards effectively submerging the frontiers of academic progress with its applications in industry. However, with the advantage of a strong and diverse academic background equipped with a wealth of creativity and programming experience, the Founder of MMCESP assures to bring to you the advantages of a strong global network of contacts from expertise in all types of problems that can adopt rational use of mathematical modelling.
Our network of contacts currently spans three of the world's continents namely Europe, America, and Asia, from which we envision to build our team of expertise. It is, therefore, that MMCESP and this website is not only about convincing people to book paid sessions, but we are also really determined to challenge problems that both industrial and scientific institutions face on regional, national and ultimately global level. MMCESP is the most convenient meeting point where industry and technology are exposed to the application of contemporary methods in data science and advanced mathematics for solving problems.