Menu
Supervisors:
,
Academic degree and current position at TSI: Master of Economics, Researcher of the Transport and Management Faculty, Director of Master Professional Program “Aviation Management”, PhD student on Telematics and Logistics Program
Experience – 12 years’ experience in Higher Education (Professional English, Digital Marketing, Career Management), 2 years experience as a Program Director (Aviation Management)
Teaching activity – Business English (Bachelor of Social Sciences in Management); Digital Marketing (Bachelor of Social Sciences in Management); English for Students of Computer Science (Bachelor of Computer Science); Career Management (Bachelor of Social Sciences in Management), English for Students of Logistics (Bachelor of Logistics), etc.
Publication activity – the author of 7 publications, indexed by Scopus and Web of Science
Projects – a national representative and Management Committee Member of COST Action CA19102 “Language In The Human-Machine Era”; member of the ERASMUS+ KA2 “SPREAD YOUR WINGS” 2017-1-PL01-KA203-038782 project; member of Cost Action: CA18231 Multi3Generation: Multi-task, Multilingual, Multi-modal Language Generation; member of the Cost Action: CA18209 European network for Web-centered linguistic data science. European Social Fund project “Strengthening Transport and Telecommunication Institute Academic Staff in the Areas of Strategic Specialisation” (Specific Objective 8.2.2 “To Strengthen Academic Staff of Higher Education Institutions in the Areas of Strategic Specialisation”, 1 year training at Riga International Airport Training Center, Latvia
Supervised theses – Supervisor of 8 Bachelor theses
Research fields/domains – Natural Language Processing, Value Proposition, Start-ups and Innovation Management, Aviation Management, Digital Marketing
Motto – It often seems impossible until it’s done
Project Type: Academic
Main Challenge
Identifying values from texts poses a complex and intricate problem. A data-driven methodology, based on natural language processing, is employed, involving the initial construction of a dataset and subsequent analysis using computational linguistic methods to identify the most effective features and techniques. Furthermore, a corpus linguistic perspective is embraced, underlining the importance of analysing language in its natural context through the use of corpora collected in the field for more reliable language analysis.
Funding: Internal
DA&AI tools:
Publications:
Lauvas street 2, Riga, LV-1019, Latvia, Phone.: +371 67100661