Nadbystrzycka 38, room 19
20-618 Lublin, Poland
phone: (+48 81) 538 46 19
e-mail: wz.kmiwz@pollub.pl
The Department is an academic unit integrating research, teaching, and cooperation with the socio-economic environment in response to contemporary challenges related to data analysis, process modelling, and decision support. Its activity focuses on issues located at the intersection of management and quality sciences, applied mathematics, statistics, economics, logistics, entrepreneurship, and artificial intelligence. The Department brings together scholars representing complementary fields of expertise, which supports an interdisciplinary approach to technical, economic, social, and organisational problems.
The research profile of the Department encompasses both classical and emerging areas related to modelling, analysing, and improving processes. Its key scientific interests include statistical and econometric modelling of economic, technical, business, and managerial processes, time series analysis, forecasting, simulations, operations research, game theory, and decision support methods. An important part of the Department’s research also concerns entrepreneurship, self-employment, business diversification, smart specialisation strategies, persistence of entrepreneurship over time, path dependency, the emergence of new industries, the geography of entrepreneurship, knowledge creation and diffusion, and spatial analyses. The Department also develops research in data science, machine learning, deep learning, and intelligent IT systems for enterprises, as well as their applications in science, engineering, industry, logistics, and business.
Another important area of the Department’s scientific activity includes issues related to the quality of technical and business processes, machine diagnostics, mathematical modelling, inverse problems, industrial tomography and image reconstruction, as well as optimal control of stochastic systems. The research conducted within the Department also addresses measurement uncertainty, error analysis, and uncertainty budgeting, particularly in relation to acoustics and the statistical modelling of road traffic noise. This profile is complemented by studies on inventory and warehouse management, supply chain management, customer logistics service, project management, and the application of modern automatic identification technologies in logistics. Such a broad research agenda enables the Department to analyse complex processes from quantitative, technological, organisational, and socio-economic perspectives.
The teaching profile of the Department reflects the breadth of its research interests and is oriented toward both academic foundations and the development of practical analytical and decision-making competencies. Staff members of the Department teach courses in mathematics, statistics, econometric modelling, operations research, decision support methods, entrepreneurship, and selected topics related to data analysis, logistics, and management. An important element of the Department’s educational activity is also the development of practical skills related to the use of spreadsheets, databases, data warehouses, and artificial intelligence and machine learning methods in solving both scientific and real-world problems.
An important part of the Department’s activity is the development of a modern educational offer responding to the growing importance of data analytics and artificial intelligence in the economy and management. In 2019, the Faculty launched the postgraduate programme “Data Analysis”, which was developed within the Department on the basis of experience gained through cooperation with business and scientific centres in Poland and abroad. This offer is complemented by the postgraduate programme “Artificial Intelligence for Managers”, aimed at developing competencies related to the use of AI tools in management, analytics, process design, and decision-making in organisations. The Department also co-creates the first-cycle engineering degree programme “Artificial Intelligence in Business”, whose curriculum combines analytical, technological, and managerial competencies, preparing students for the practical application of artificial intelligence methods, data analysis, and digital tools in the business environment.
The Department also develops broad scientific and expert cooperation, including experimental design, selection of statistical tools for research, statistical elaboration of scientific problems, modelling of economic and technical processes, process quality improvement, and automation of decision-making. In terms of cooperation with business practice and the institutional environment, important areas of activity include the application of artificial intelligence and machine learning in industry, business, and scientific research, fault detection in technical systems, and the preparation of expert opinions on innovativeness in industry and the IT sector.
Projekt współfinansowany ze środków Unii Europejskiej w ramach Europejskiego Funduszu Społecznego, Program Operacyjny Wiedza Edukacja Rozwój 2014-2020
"PL2022 - Zintegrowany Program Rozwoju Politechniki Lubelskiej" POWR.03.05.00-00-Z036/17