R&D Projects - The best Solution for Complex Problems
If you have a complex problem and would like to solve it - you are on the right place!
What are your biggest business problems?
What are the things that worry you the most?
Do you have a problem that can be analyzed, solved, automated or optimized using mathematical modeling?
1D? 2D? 3D? Stationary / Time dependent? Linear / Nonlinear? Direct / Inverse?
Would you like to be able to quickly and easily predict behavior of your complex system, estimate values of all relevant parameters,
answer what-if type of questions (how does a quantitative change of input data affect the results), automate or optimize it?
Would you like to use mathematical modeling, robust algorithms, advanced numerical simulations and intuitive visualizations of quantitative results
to avoid expensive and time-consuming experiments, save time and money, and beat the competition with innovation, quality and price?
Do you have a bunch of data or dataset (a table or a database or a bunch of text) that hides useful information that can reduce business costs, increase profit,
improve risk management, or significantly influence decision-making and strategic planning?
Do you have a bunch of digital signals, time series, 2D/3D images, audio or video files, that you would like to analyze, process and interpret, and for some reason
you cannot do it by yourself?
Do you have an interdisciplinary / multidisciplinary problem that goes beyond your current competencies, or that you cannot solve for any reason
(mathematical or numerical)?
Do you have a problem that you cannot solve, you have no idea who could solve it, and you do not have an address for a help?
A lot of questions. One answer. R&D projects based on MM or AI/ML are the best solution for your complex problems.
Formula for success and sustainable business growth:
Complex Problem + R&D Project based on MM or AI/ML = The best Solution
Slow food is great, but slow business is NOT!
There is a lot of room for efficiency improvement, automation and optimization.
It is more important to start quickly, and it is okay to start small.
It is okay to do a small R&D project to start and learn what it feels like to use research and development,
and then continue to set higher goals and achieve greater success.
Research and development is causing a shift in the dynamics and bring new quality.
So if your company is not already making smart investments, it is a good time to start.
Do NOT waste your time. Do NOT be afraid of change.
Utilize the power of R&D Projects based on MM or AI/ML to solve all your complex problems.
How?
For the beginning, describe your real business problem or business idea in a few sentences and send it.
Later on, we can talk about it in more details on a video-call or face-to-face in a live meeting.
In case of Mathematical Modeling, describe your real problem or system in a few sentences:
what is known, what is unknown, and what would you like to find out.
In case of Artificial Intelligence, describe in short where and how you would like to apply it
or what you would like to optimize or automate.
In case of Machine Learning, describe your data and what you would like to do with them:
clustering, classification, or regression (value prediction), or analysis and forecasting.
Send to:mathmodels@mathmodeling.rs
Feasibility study (feasible / not feasible, time frame and price for R&D Project) will be provided free of charge!
Status quo or change? Innovate and accelerate your business. Feel the difference!
Plan wisely. Manage risk. Reduce costs. Increase efficiency, quality, and revenue. Beat competition.
Utilize the power of decision-making based on mathematical models, algorithms, and numerical simulations,
or on meaningful information, structures, relationships, patterns, and trends hidden in the data.
Save time and money by replacing expensive and time-consuming experiments with computer simulations, estimate the values of all relevant parameters,
predict the behavior of a complex system, automate or optimize it, answer what-if type of questions, speed up prototyping.
Use all relevant information hidden in the data to better understand that data and to group them into clusters,
or for complex classifications of new data and for advanced quantitative predictions on new data.
Turnkey system. Tailor-made solution. Competitive price. Professional service. Top quality. Lifetime warranty.
R&D Projects are research and development projects that are used to innovatively solve complex problems, develop new products and services,
or improve existing ones.
The aim of the research is to discover the best way the problem can be solved, while the development implies
design, development and implementation of the solution, and testing as well as preparation of the documentation.
How long do R&D Projects last?
Depending on complexity of the problem or system and required results, R&D Projects can last: 0.5-1, 1-3, 3-6, 6-12, 12-24, or 24+ months.
Usually, 50% of the time is spent on research and 50% of the time on development.
What is Mathematical Modeling in a narrow sense?
Mathematical Modeling (MM) in a narrow sense is a description of a real problem or system with abstract mathematical language - with mathematical equations, i.e., with mathematical model.
What is Mathematical Modeling in a wider sense?
Mathematical Modeling (MM) in a wider sense is quantitative solving of a real problem using mathematical models, mathematical algorithms, and
numerical simulations.
Visualization, analysis, processing, and interpretation of obtained numerical results are the final part of mathematical modeling in a wider sense.
Mathematical modeling represents an extremely powerful tool for static or dynamic quantitative analysis.
Where can mathematical modeling be applied?
Mathematical modeling can be applied wherever a real problem or system can be described with mathematical equations or represented by a mathematical
model - almost everywhere.
How can mathematical modeling help us?
Mathematical modeling can accelerate analysis or prototyping, replace costly and long-lasting experiments, enable better understanding, control, automation and optimization,
improve risk management, and significantly reduce costs of the business and increase profit.
What is Machine Learning?
Machine Learning (ML) is ability of mathematical models to statistically learn complex patterns or structures hidden in data and use that knowledge
for clustering of the data or for complex classifications and advanced predictions on new data.
Machine learning is the core of artificial intelligence.
Where can machine learning be applied?
Machine learning can be applied wherever there is a large amount of data (a large table or database, or a large amount of text or images) hiding useful information we want to
utilize for data-driven decisions.
How can machine learning help us?
Machine learning can be used for better understanding of the data, complex data clustering and classifications, advanced analysis and predictions, risk control,
and strategic planning.
What is Deep Learning?
Deep Learning (DL) is part of machine learning. Deep learning is based on deep artificial neural networks.
Deep learning is used to solve large and extremely complex machine learning problems.
What are Artificial Neural Networks?
Artificial Neural Networks (ANN) are inspired by biological neural networks and consist of interconnected artificial neurons (mathematical models) that process input signals
and calculate the output signal. Shallow neural networks have an input layer, several so-called hidden layers, and the output layer, and deep neural networks have a larger number of
so-called hidden layers.
What is Artificial Intelligence?
Artificial Intelligence (AI) is the ability of a machine to perform a complex but narrowly specialized job as well as a human being, or even better.
Artificial intelligence involves mimicking human cognitive abilities such as learning and problem solving.
What does it mean by turnkey system?
This means that you get a complete service, from idea to solution, i.e., from end-to-end.
Brief description of several completed R&D projects
Field: Thermodynamics. Imagine a tank with a few thousands liters of a liquid (e.g. wine).
The tank-liquid should be heated or cooled with another liquid, with a given and constant temp., which is going through the heating/cooling system
attached to the tank.
Starting from a given or room temp., the temperature of the tank-liquid should be increased or decreased to the desired temp. having in mind a given
speed limit in Celsius degrees per hour, i.e., not to slow and not too fast, or, the tank-liquid should stay at the given/constant temp.
during the process of fermentation (wine).
Тhe project could be defined as a direct problem, if the tank is defined (given) and the heating/cooling system should be designed to fulfill given
requirements and restrictions, or, as an indirect problem, if the heating/cooling system is already specified (given) and the tank should be chosen
or designed in order that the system fulfill given constraints.
Imagine that you can solve the problem in both directions in a few seconds.
Field: Computed tomography. Imagine that you have a 3D image (a collection of 2D slices/images called 3D study) of a 3D object, e.g., a patient head.
The 3D study can be obtained by a reconstruction of 600 2D images produced with X-Ray Cone Beam Computed Tomography scanner.
In order to be able to make the implants, a dentist has to know exact locations of both mandibular canals (left and right) for each patient.
The blood vessels and nerves pass through the mandibular canals so the canals should not be touched or damaged with the implants.
Each mandibular canal has a unique shape even for the same patient, almost like a fingerprint, and the dentist can trace one mandibular canal on the
screen, point-by-point, using a mouse in 90 - 120 min.
Imagine that you only point the entrance of a mandibular canal and that the computer can automatically trace the canal in 10 - 15 seconds so that you can trace both
mandibular canals in less than 1 min.
Field: E-commerce. Imagine a website where different products are sold (e-store).
In order for an e-store to be successful, it needs to meet two basic criteria.
The first criterion is satisfied e-store users, and the second criterion is satisfied e-store owners.
In order for e-store users to be satisfied, personalization of the user experience on the website is required.
In order for the owners of the e-shop to be satisfied, it is necessary to sell as many products as possible on the e-shop and make as much profit as possible.
Imagine an intelligent autonomous system that learns and adapts in real time and makes data-driven decisions to satisfy both of these criteria.
A system that collects all relevant raw data, calculates all relevant KPIs, shows all relevant reports, takes care of zero search results prevention, personalized recommendations, demand forecasting and inventory optimization, price markdown optimization, and personalized marketing as well as reasoning and data informed strategic decision making.
Imagine a system that is based on the application of artificial intelligence and business intelligence (AI-BI) and that achieves this completely independently, without involvement of humans.
Result oriented problem solver with PhD in Electrical Engineering in the field of mathematical modeling and more than 25 years of professional experience.
10+ years of professional experience in scientific research and 15+ years of professional experience in applied research and development (R&D projects).
Interested in science, innovations, research and development, mathematical modeling, algorithms, artificial intelligence, machine learning, and deep learning.
Likes intellectual challenges. Likes to understand what is going on under the hood. Likes to learn. Likes to solve hard and complex problems.
Can-do, holistic, and strategic approach to the problems. Open mind and an interdisciplinary mindset. Eye for details and ear for deadlines.
Willingness to run the extra mile in order to meet high quality standards.
Prefers Matlab, Python, and R.
