Datu analīzes un mākslīgā intelekta pētniecības klasteris ir koncentrēts uz datu izpēti, konsultēšanu un apmācību, tostarp lielo datu analīzi, statistisko modelēšanu, svešvalodu apstrādi un galvenajiem mākslīgā intelekta aspektiem. Klastera darbība aizpilda plaisu starp progresīvajiem pētījumiem un uzņēmumiem dažādās nozarēs un sektoros.
Klastera dalībniekiem ir pieredze šādās jomās:
- Daudzveidīga analīze un statistiskā modelēšana
- Laikrindu prognozēšana
- Uzlaboti neironu tīkli un to lietojumprogrammas
- Teksta un attēla ieguve
- Lēmuma pieņemšanas metodika
Lietišķās zonas klastera grupas ietver (bet neaprobežojas ar to) gaisa transporta nozari, pilsētas satiksmes plūsmas, sabiedrisko transportu, sociālos medijus, teritorijas plānošanu, krājumu kontroli un loģistiku.
Datu analīzes un mākslīgā intelekta pētniecības klastera brošūra
Klastera dalībnieki
Klastera vadītājs:
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Academic degree: doctoral degree in Economics (2005) and Engineering (2015).
Current position at TSI: professor (since 2019), pro-dean of the Engineering Faculty (since 2021), researcher and head of Data Analytics and Artificial Intelligence research cluster at Transport and Telecommunication Institute, TSI (since 2020).
Experience: academic career from an assistant position at Saratov State University, Russia, in 2002 to an associate professor at TSI. Chair of TSI Mathematical Methods and Modelling Department (2014-2020).
Academic experience: Nineteen years of teaching experience in higher education, development and presenting study courses: Probability Theory and Mathematical Statistics; Econometrics; Operation Research; Optimisation Theory; Discrete Mathematics; Introduction to Stochastic Processes; Data Analysis and Business Forecasting. Member of TSI final attestation commissions on MSc in Computer Science and Management of Information Systems. Dr Dmitry Pavlyuk has supervised 15 successfully promoted MSc and 10 BSc theses. Teaching mobility to Higher School of Transport, Bulgaria (2013), Vilnius Gediminas Technical University, Lithuania (2017).
Research experience: Author of more than 50 publications, including 22 journal articles in Sensors (ISSN: 1424-8220), European Transport Research Review (ISSN: 1867-0717), Algorithms (ISSN: 1999-4893), Transport and Telecommunication (ISSN: 1407-6179), Research in Transportation Economics (ISSN: 0739-8859), Transport (ISSN: 1648-4142) and 12 book chapters in Springer’s Lecture Notes in Networks and Advances in Intelligent Systems and Computing book series. Postdoctoral researcher at TSI (2017-2020) for spatiotemporal urban traffic modelling; presenter at more than 30 international conferences in Latvia, Austria, Cyprus, France, Greece, Germany, Poland, Russia, Spain. The reviewer at many top scientific journals, including Transportation Research, Parts A, C, E, Transport Reviews, IEEE Access, Transportmetrica B. Guest editor at Information (ISSN: 2078-2489); member of programme committees of Reliability and Statistics in Transportation and Communication (RelStat-2017-2020), Latvia, and Computer Modelling in Decision Making (CMDM 2017-2020), Russia. Member of PhD promotion committee, expert of the Latvian Council of Science (since 2017) in Civil Engineering.
Participation in research projects: Dr Pavlyuk has successfully completed the postdoc research project 1.1.1.2/VIAA/1/16/112 “Spatiotemporal urban traffic modelling using big data” (2017-2020); researcher in “Enhancing excellence and innovation capacity in sustainable transport interchanges” (Horizon 2020 Nr. 692426, 2016-2018), “Learning with ICT use” (Erasmus+, 2014-2017) and several commercial research projects.
Research Interests: Research interests include: spatial and spatiotemporal statistical modelling, multivariate time series analysis, econometric models and statistical estimators, stochastic frontier models and machine learning in applied domains of banking, airport industry, urban road traffic, public transport, venture markets, and environmental management.
Vecākie pētnieki:
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Academic degree and current position in TSI: professor, leading researcher of the Engineering Faculty, Director of MSc Program “Transport and Logistics”
Previous experience: more than 10 years was Vice-rector for Research and Development, Transport and Telecommunication Institute (TSI), founder of the Laboratory of Applied Systems and chair of Mathematical Methods and Modelling Department in TSI
Membership: From 01.2017 member of ECTRI Board and from 2019 – vice-president of ECTRI; an external scientific expert in Association of Paneuropa Coach Terminals from 2009; has been chair or member of the organizing and the programme committees of the International Conference on Applied Statistics (6 events), Transportation Research (15 events), Complex Systems (4 events), etc. and reviewer in transportation journals and conference proceedings. Member of Editorial Board of Journals: Transport (WoS, SCOPUS); Maintenance and Reliability (SCOPUS), Transport and Telecommunication (WoS, SCOPUS), etc. Guest redactor of Volumes of Lecture Notes in Networks and Systems and Lecture Notes in Intelligent Transportation and Infrastructure in Springer; Procedia Engineering published by Elsevier etc.
Academic experience: Author more than 170 publications, incl. 9 books and textbooks, chapters in the books “From Transit Systems to Models: Purpose of Modelling” in book: “Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems” (Springer Verlag, 2016), “3D City Models and urban information: Current issues and perspectives” (edpsciences, 2014), papers in International Journal of Transport, Transport and Telecommunication, Advances in Intelligent Systems and Computing, etc. Guest redactor of Volumes of Lecture Notes in Networks and Systems and Lecture Notes in Intelligent Transportation and Infrastructure in Springer; Procedia Engineering published by Elsevier etc. An Expert in Transport and Logistics (2008-2021) and Civil Engineering (from 2021) at the Latvian Council for Science; member of the PhD promotion committee
Teaching at post- and graduate levels: Data Analysis (PhD in Business Management, RSEBAA-BA); Multivariate Statistical Analysis, Transport Modelling, Scientific Seminar (Dr. Ing. in Telematics and Logistics, TSI); Data Mining (MSc in Computers Science, MIS, TSI); Research Seminar; Methods of Data Analysis and Business Forecasting (MSc in Transport and Logistics, TSI); etc.
Participation in projects: as leading researcher has participated in more than 20 European and Latvian research projects and more than 14 national transportation studies, and was scientific coordinator in 8 of them. Is/was national representative and management committee member of COST Actions CA16222 (WISE-ACT), TU1306 (CYBERPARKS), TU1004, TU0903, TU0804 and TU0801. Has great experience in coordinating different kind of projects in frame of Horizon 2020, FP, INTERREG, BSR programmes, she was coordinator of Horizon 2020 project “Enhancing excellence and innovation capacity in sustainable transport interchanges” (ALLIANCE)
Research interest: Data analysis, data mining, statistical analysis, mathematical modelling and simulation with application in different fields (transportation sphere, business, economics, networks, logistics and others)
Supervised Doctoral, Master and Bachelor Theses: Promoted 6 Doctoral, more than 90 Master theses and 70 Bachelor theses an official reviewer of 7 PhD theses
Awards: (2019) by Ministry of Education and Science; (2017, 2010, 2008) Latvian Education Funds; (2011, 2010, 2008) Riga Municipality
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Academic degree and current position in TSI: associate professor, researcher at the Engineering Faculty.
Previous experience: worked at the Mathematical Methods and Modelling Department in TSI for more than 10 years (assistant, lecturer, assistant professor), postdoc researcher.
Membership: A member of the Latvian Simulation Society since 2004, a member of the Latvian Operations Research Society (LatORS) since 2019.
Teaching activity: Discrete Mathematics (undergraduate level); Probability Theory and Mathematical Statistics (undergraduate level); System Modelling (undergraduate level); Introduction to machine learning (undergraduate level); Statistics (undergraduate level).
Publication activity: Author of on average two to three academic articles a year.
Projects: as a researcher has participated in more than 5 European and Latvian research projects.
Supervised Doctoral, Master and Bachelor Theses (number): 1 Master thesis and more than 10 Bachelor theses.
Research fields/domains: Data analysis, statistical analysis, mathematical modelling and simulation (in transportation), machine learning.
Motto: “Any problem can be turned into opportunity”.
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Dr Neil Rubens is a graduate of the Massachusetts Institute of Technology, visiting professor and leading project manager at Stanford University (USA) on projects, related to applications of artificial intelligence for industry analysis, was working as assistant professor at University of Electro-Communications in Tokyo (Japan), has excellent work experience in business sector as software engineer, as well as founder of own startup sectormap.net in Japan.
Doktorantūras studenti:
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