Research Group

We help to research advanced models of Artificial

Intelligence in the following directions:

Predictive analytics
We create diagnostic methods for complex systems for timely and preventive impact.
Computer Vision
We investigate complex architectures (img2img, Transformer) for detection, segmentation, resolution enhancement, 3D reconstructions, etc.
NLP Analytics
We create a complete set of text analysis methods: hard and soft clustering, summarization, classification and tagging, search tasks.
Wearable devices
We apply algorithms to data from inertial and biomedical sensors to solve problems of HAR, pressure detection, navigation, etc.
We study the applicability of AI methods to encoding information of various nature: from the video stream to the human genome.
Interpreted models
We create deep learning models that can be interpreted and managed in the process of use.
Clients of research teams form the goals of R&D projects. We have highlighted the most common research requests:
Preliminary Research
Preliminary and detailed study of the subject area with the search for scientific articles, available data, and open source in order to obtain a base of materials for a quick dive into a new area and form requirements for future R&D results
Technological Pipeline Development
Development of a complete technological pipeline for solving a problem based on client data, based on existing algorithms and open source in order to obtain a strong basic solution for subsequent modifications and growth of target metrics
Negative Effect Removal
Elimination of a key negative effect in the operation of the existing model: from excessive sensitivity to fluctuations in the data to the quality of work in corner cases. The goal is to grow certain metrics of the customer model within the given constraints
Industrial Pipeline Development
Development of a Proof-of-the-Concept pipeline for solving an industrial business problem based on artificial intelligence algorithms in the absence of known approaches to its solution. The goal is the fundamental possibility of solving such a problem
The methodology for the implementation of R&D projects developed on the basis of our experience allows us to quickly carry out a full cycle of research and reduce risks
Flexible approach to managing the project scope and transparency of the development process
Using the methodology of AI projects to reduce risks and systematically achieve breakthrough results
Deep understanding of both basic business needs and the use of SotA AI methods
Short iterations with the transfer of a useful and exploitable result
Research results are fully transferred to the client
Software implementation
Easy to use library for with readable and reproducible code
Materials base
Base of materials with reviews for a quick dive into the field and a technical report
Trained Models
Parameters of trained models packed in the format required by the client
Anything else
We can prepare project artifacts in the format required by the customer
MIL Team Research conducted research for
Scientific consultants of the Research Group
Konstantin Vorontsov
Prof, MSU
Specialisation: NLP
Vadim Strijov
Prof, Grenoble
Specialisation: Sensors
Mikhail Burtsev
Prof, AIRI
Specialisation: NLP
Radoslav Neychev
Specialisation: Sensors
Andrey Leonidov
Prof, CERN
Specialisation: ML
Andrey Raygorodsky
Prof, Yandex
Specialisation: ML, Graphs
Ilya Zharikov
Specialisation: DL & Sensors
Oleg Bakhteev
Specialisation: DL
Some Research Results
Made on