Akademia Innowacyjnych Zastosowań Technologii Cyfrowych

The AITECH will educate new generation of specialists in domains of artificial intelligence and machine learning, being the key topic influencing development of digital societies and novel industries. Students will be learning the current trends and state of the art in two specialisations, will propose and conduct research and development project, will be tutored and mentored by the most renowned specialists. The project will: 1. initiate the Project Board, supervising all endeavours and realisation of the project. 2. define guidelines for the specialisations at MSc level, reflecting actual needs of key industries and employers. 3. preparation of study materials, study programs and courses, starting new specialisations, organizing and conducting the education. Project financial support will cover: preparation of materials, conducting the education, participation in study visits, intern programs, international conferences for all students of AITECH, conducting research projects. The project goals require enrolling at least 100 students in total (for 2 cycles of 2 specialisations), and at least 64 persons should complete the whole programs of MSc course. The diploma is not required.

Details

Project's acronym:

AITECH

Financial Program Name:

Program Operacyjny Polska Cyfrowa

Organization:

Centrum Projektów Polska Cyfrowa

Agreement:

POPC.03.02.00-00-0001/20-00 z dnia 2021-01-19

Realisation period:

2021-01-19 - 2023-12-31

Research team leader:

dr hab. inż. Piotr Szczuko

Realised in:

Registrar's Office of Electronics, Telecommunications and Informatics

External institutions participating in project:

Ministerstwo Cyfryzacji (Poland)
Uniwersytet Adama Mickiewicza (Poland)
Politechnika Poznańska (Poland)
Uniwersytet Warszawski (Poland)
Politechnika Wrocławska (Poland)

Project's value:

51 521 859.00 PLN

Request type:

Fundusz Strukturalny

Domestic:

Domestic project

Verified by:

No verification

Papers associated with that project

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total: 2

Year 2022

Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication
- A. Frączek
- G. Karwowska
- M. Miler
- J. Liss
- A. Jezierska
- M. Mazur-Milecka
- Year 2022
(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...

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Year 2021

Towards Cancer Patients Classification Using Liquid Biopsy
Publication
- S. Cygert
- F. Górski
- P. Juszczyk
- S. Lewalski
- K. Pastuszak
- A. Czyżewski
- A. Supernat
- Year 2021
Liquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...

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