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SOLVED BUSINESS CASES IN AI/IT FOR WORLD LEADERS: PHILIPS, EPAM, REGENERON, HUAWEI, ETC.

20+

10+

YEARS OF TEACHING THE BEST STUDENTS OF APPLIED MATH DEPARTMENT AT POLYTECH UNIVERSITY (RUSSIA)

10+

YEARS EXPERIENCE OF SCIENTIFIC WORK IN THE FIELD OF COMPUTER SCIENCES IN THE POSITIONS: CHIEF SOFTWARE ENGINEER, LEAD SCIENTIST, ALGORITHM DEVELOPER, RESEARCHER

40+

GRADUATE PROJECTS PREPARED ON COLLABORATIVE PROJECT IN IT & Technology domain with the leading companies

Skills

SCRUM
C++, C++0x (C++11/C++14/C++17
and other), GLSL (OpenGL Shading Language), HLSL (High Level Shading Language), NVIDIA Cg
Python
Keras/Tensorflow
Cloud Healthcare API,
Google Cloud Platform
Boost, NVIDIA CUDA, OpenMP, Qt
OOP
OpenGL/DirectX
Design patterns
JavaScript

interests

Decision Trees
Algorithms
Neural Networks
Machine Learning
Deep Learning
Pattern Recognition
Applied AI
Image Processing
Computer Vision
Signal, Image and Video Processing
Image Segmentation

Working with technoleaders

Team leader in research projects with world giants: PHILIPS, EPAM, REGENERON, HUAWEI

UNIQUE BUSINESS APPROACH

DEEP SCIENTIFIC EXPERTISE IN COMPUTER SCIENCE AND AI WITH MODERN AGILE METHODOLOGIES FOR MAKING DEVELOPMENT PROCESS TRANSPARENT AND CLIENT-ORIENTED

COOPERATION WITH UNIVERSITIES

10+ YEARS OF TEACHING COMPUTER SCIENCES, INVOLVING STUDENTS FOR THE IMPLEMENTATION OF PRACTICAL TASKS AND INTEGRATION OF DEVELOPED TECHNOLOGIES IN LEARNING PRACTICES

BUSINESS CASES

3 team members

2 years

CENTRALIZATION OF COMPUTING RESOURCES, DEVELOPMENT
OF DATA LAKE WITHIN SEVERAL RESEARCH LABORATORIES WITH A COMMON ROADMAP

Description

PLATFORM FOR MANAGEMENT AND VERSIONING
OF DATA AND DEEP LEARNING MODELS RELATED
TO BUSINESS PROCESSES

OPEN SOURCE ONLINE SERVICE
FOR REAL-TIME MEDICAL DATA VISUALIZATION

Description

ALGORITHMS FOR EFFICIENT RENDERING OF LOW-RESOLUTION MEDICAL DATA IN REAL TIME BASED ON RAYTRACING AND WEBGL

5 years

8 team members

INNOVATIVE ALGORITHMS FOR EFFICIENT NETWORK ROUTING

Description

APPLICATION OF ACADEMIC KNOWLEDGE IN DEVELOPING STATE OF THE ART DESCRETE MATH ALGORITHMS TO CREATE THE MOST ACCURATE AND PRODUCTIVE SOLUTION (*NP COMPLETE PROBLEMS, NEW ALGORITHMS IN DISCRETE MATHEMATICS)

6 months

7 team members

INTERACTIVE SEGMENTATION TOOLS FOR MEDICAL IMAGING (FULLSTACK, С++)

Description

COMPLETE PRODUCT DEVELOPMENT FROM RENDERING OF BUSINESS REQUESTS TO MANAGING EACH SPRINT TASKS AND SOFTWARE ARCHITECTURE DESIGN

3 years

13 team members

CLIENT-ORIENTED PROJECT LIFE CYCLE

DISCUSSION OF THE BUSINESS REQUEST WITH THE CUSTOMER

OFFERING BEST SOLUTIONS THAT CAN PRODUCE BEST OUTCOME, TAKING INTO ACCOUNT THE EXPERIENCE OF THE SCIENTIFIC TEAM, THE CUSTOMER'S OPPORTUNITIES. DEVELOPING STATEMENT OF WORK

00

OF HIGHLY MOTIVATED AND QUALIFIED SPECIALISTS WITH THE REQUIRED EXPERTISE

01

BUILDING A TEAM

WITH STRICT PROCESSES DESIGNED TO DELIVER MOST TRANSPARENT AND FLEXIBLE DEVELOPMENT PROCESS TO THE CUSTOMER. YOU CAN TRACK PROGRESS AND GIVE FEEDBACK TO GUIDE THE DEVELOPMENT WITH MINIMAL EFFORTS

02

AGILE METHODOLY

CUSTOMER CAN SOLVE ALL IMPORTANT QUESTIONS WITH THE TEAM LEAD

03

SINGLE WINDOW PRINCIPLE

1hr per week is enough to listen to the well-designed reports of the team and provide feedback to help fill the backlog with more prioritized tasks for the next sprint

04

MINIMAL FEEDBACK TO GUIDE THE DEVELOPMENT

MOST STUDENTS PARTICIPATED IN PROJECTS GET ONE OR MORE OFFERS FROM CUSTOMERS: YOU HAVE OPPORTUNITY TO HIRE MOST TALENTED ENGINEERS

05

HIRE MOST TALENTED

NEW PRACTICES AND SCIENTIFIC RESULTS OBTAINED DURING THE WORK PROCESS COULD BE INCLUDED IN EDUCATIONAL COURSES OF THE UNIVERSITY ON BEHALF OF THE COMPANY

06

CONTRIBUTION TO EDUCATION AND SCIENCE

Scientific projects

Publications

Kots, Mikhail, et al. «Semi-supervised Learning for Medical Image Segmentation». Proceedings of International Scientific Conference on Telecommunications, Computing and Control. Springer, Singapore, 2021.

Utkin, Lev V., et al. «Estimation of Personalized Heterogeneous Treatment Effects Using Concatenation and Augmentation of Feature Vectors». International Journal on Artificial Intelligence Tools 29.05 (2020): 2050005.

Utkin, Lev V., et al. «A New Adaptive Weighted Deep Forest and Its Modifications». International Journal of Information Technology & Decision Making 19.04 (2020): 963-986.

Utkin, L. V., Konstantinov, A. V., Chukanov, V. S., Kots, M. V., Ryabinin, M. A., & Meldo, A. A. (2019). A weighted random survival forest. Knowledge-Based Systems, 177, 136-144.

Utkin, L., Konstantinov, A., Meldo, A., Ryabinin, M., & Chukanov, V. (2019, April). A Deep Forest Improvement by Using Weighted Schemes. In 2019 24th Conference of Open Innovations Association (FRUCT) (pp. 451-456). IEEE.

Belyaev, S., Chukanov, V., & Shubnikov, V. (2017). Bump Mapping for Isosurface Volume Rendering. Journal of Image and Graphics, 5(2).

Media

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