Jednostki i pracownicy - książka adresowa

dr Marek Mędrek

Personal information

Scientific Profile in Keywords
Business Intelligence, Data Science, Data Mining, E-business, Open data

 

Scientific Interest
My professional and research interests focus on two areas: Data Science and Computer Modelling. In the Data Science area, I am interested in the implementation of machine learning and analytical techniques in business, social and economic analysis. I have extensive experience in modelling using artificial intelligence techniques (e.g. neural networks, cellular automata) and using business process simulation techniques (BPMN). Another area of my scientific activity is e-government and open data - many years of experience in developing and implementing IT solutions in public institutions helps me in effective and efficient analysis and optimisation of processes in public institutions. I am a practitioner with a methodical approach focused on project objectives and innovative IT techniques that can be used during project delivery. Passionate about agile and lean application in project management.

Courses I Teach
Business Intelligence, Data Mining, Data integration, Databases, E-business, Process Modelling (BPMN, Adonis), Software Engineering (UML), Algorithms and Complexity


Scientific Activity

 Selected Publications
1. Mędrek M., Pastuszak Z., “Numerical simulation of the novel coronavirus spreading”, DOI: https://doi.org/10.1016/j.eswa.2020.114109, EXPERT SYSTEMS WITH APPLICATIONS, 2021
2. Medrek M., Tatarczak A, BUSINESS INTELLIGENCE AND DATA ANALYSIS IN AN ADAPTIVE WEB-BASED INTEGRATED LEARNING ENVIRONMENT, DOI: 10.21125/inted.2017.1395, INTED 2017, 11th annual International Technology, Education and Development Conference At Valencia, Spain, 2018
3. Holko A., Mędrek M., Pastuszak Z., Kongkiti P., “Epidemiological modeling with a population density map-based cellular automata simulation system”, DOI: 10.1016/j.eswa.2015.08.018, EXPERT SYSTEMS WITH APPLICATIONS, 2016
 

Selected Research Projects
1. Incubator of innovation+ No. MNISW/2017/DIR/33/II+: Modelling the energy consumption patterns of telecommunication facilities using predictive methods
2. Modelling of the reverse logistics processes for plastics waste in the perspective of international experience, https://projekty.ncn.gov.pl/index.php?projekt_id=468652
3. Development of algorithms for detecting anomalies in data transmission in data communication networks, using the PSO optimization method.

Planned Research or Teaching Activities
1. Analysis of open/public data sets using artificial intelligence methods..
2. Technology enhanced teaching and learning.
3. Data mining and Business Intelligence solutions and implementation.

 

ORCID iD iconorcid.org/0000-0001-5752-5084
 

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