DOUBLE DEGREE MASTER’S PROGRAM
“MASTER OF COMPUTATIONAL SCIENCE”
PARTNER UNIVERSITY: LAPPEENRANTA UNIVERSITY OF TECHNOLOGY, FINLAND
FIELD OF STUDY: COMPUTER VISION AND ARTIFICIAL INTELLIGENCE
PHOTONICS AND OPTICAL INFORMATION TECHNOLOGY FACULTY
COMPUTER PHOTONICS AND VIDEOMATICS CHAIR
DEGREES AWARDED:


MASTER OF COMPUTATIONAL SCIENCE (ITMO UNIVERSITY)
MASTER OF SCIENCE (LUT)
ELIGIBILITY: AN APPROPRIATE BACHELOR´S DEGREE OR AN EQUIVALENT QUALIFICATION.
PERIOD OF STUDY:
2 YEARS, 120 ECTS
LANGUAGE:
ENGLISH
MAIN DEADLINES:
EU: JUNE EACH YEAR
About the Programme
The study program is extended over 2 calendar years according to the following scheme:
The Program provides up-to-date knowledge, skills and capabilities required in development of
computer vision systems using modern technologies and efficient teaching methods.
Master’s Degree Program educates for the requirements of IT-industry, research institutions and
business within the field of Computer Science. The general objective of the degree program is to
train efficient teamwork-capable experts and to provide them a solid ground for the independent
continuation of learning in the ever changing field of computer science and IT industry. Postgraduate studies are possible both in NRU ITMO and LUT.
Goals
The students who will successfully complete this course will be able to
 Understand the fundamental concepts of designing and programming modern computer
vision systems, including requirements specifications, architectural and detailed design,
and implementation;
 Design models of intelligent systems processing;
 Develop software for complex systems of image understanding, analysis and processing;
 Implement management skills for modern intelligent computer systems development in
IT companies;
 Administrate promising trends in computer vision systems progress
Eligibility requirements
Students are required to present and maintain an e-portfolio & research record which represents
them as a student as well as a professional.
Enquiries
If you have any questions, or require further information, please contact:
Computer Photonics and Videomatics Chair
NRU ITMO
Dr. Igor P. Gurov, Head of Chair
Phone: +7 (812) 315-7534
E-mail: gurov@mail.ifmo.ru
The programme structure
Structure of DD Programme – ITMO (1ST YEAR)
Logic and Methodology of Science
Methodology of IT engineering and development
Image Analysis in Optical Coherent Tomography and Digital
Holography
Systems Analysis and AI/ General Artificial Intelligence
Modern Videomatics
Image Recognition
Mathematical Modelling/ Advanced Applied Mathematics
Research Methods, laboratory Project
Structure of DD Programme – LUT (2ND YEAR)
Digital Imaging and Image Preprocessing
Seminar on Intelligent Computing
Introduction to Computer Graphics
Pattern Recognition
Machine Vision and Digital Image Analysis/ Computer Vision
Academic Writing in English
Research Methods, Laboratory Project
Main research areas
Computer Vision Systems Design
Main goal of this course is to develop understanding and implementation skills of all aspects of
modern computer vision science. Historical background will be considered in relation to image
post and preprocessing methods, pattern recognition approaches and biological background
which laid the foundation to computer vision discipline. Student will know about implementation
of these methods and their modifications. Modern methods will also be learned: their
implementation, areas of usefulness, problems and modifications.
Artificial Intelligence
This course is devoted to general theory of artificial intelligence, stages of its evolution, modern
trends and techniques. Special attention will be given to chapters of machine learning, pattern
recognition, but problems of knowledge representation and reasoning will also be considered.
Development of Intelligent Systems
This course is focused on implementation of artificial intelligence knowledge to highly
automated software development. Different approaches to such development will be considered.
Advanced Image Analysis
The point of that course is the optical coherence tomography and digital holography images
processing. History of tomography and holography will be spoken. This course delivers special
tricky techniques to imaging, transmission and analysis of such images. Basic theory of signal
processing will be considered too.
IT Engineering
Main aspects of software development process will be learned during this course. Teamwork,
basics of extreme programming, stages of development and integration of IT projects is going to
be studied.
Special Features
Our laboratories supplied with modern equipment, including optical coherence tomography
installations, humanoid robots, quadcopters, kinect cameras, stereo cameras, high resolution 3D
scanner and highly performance computers especially for intelligent computer vision systems.
Highly qualified training staff, modern hardware and software, equipped laboratories, qualitative
methodological support of educational programmes have significant impact on competitive
advantage of training.
Learning Environment
The Master’s degree programme is mainly given in English and the modules included are
common both for native students continuing from Bachelor’s programme and international
students accepted directly into International programme of the NRU ITMO and LUT IT.
Education process is a combination of group and individual work relating to the information
technologies and the development of individual project which based on theoretical knowledge
(seminars, tutorials, lectures) and practical workshops (research methods).
Careers
Our graduates are highly employable and can look forward to rewarding careers in the design,
development, and maintenance of software for computer vision and intelligent systems, image
analysis, product development and other kinds of IT projects development. Professional duties
may include software and systems analysis and design, participation in software development
projects, scientific research and product development. Graduates may also occupy positions in
computer vision project planning and management and be engaged in modern computer vision
technologies research.