Learn from the Best

Dr hab. Łukasz Mateusz Skowron is an experienced researcher and expert in the field of management and marketing, combining academic work with research and advisory practice carried out for business and public institutions. He is a Professor at Lublin University of Technology, Faculty of Management, and serves as Chair of the Council of the Discipline of Management and Quality Sciences.

His work focuses on issues related to customer behaviour and relationships, satisfaction and loyalty, as well as the measurement and analysis of processes involved in building organisation–customer and organisation–employee relationships. He is the author of a habilitation thesis entitled Customer Learning in Conditions of Market Change, and previously defended a doctoral dissertation on customer loyalty in banking activity.

At the same time, he develops expert and implementation-oriented activities as President and Co-owner of the Total Effect Research Agency, where he has managed numerous nationwide and international research projects. As part of his cooperation with the socio-economic environment, he has carried out analytical and research activities for, among others, the City of Lublin, the LUX MED Group and academic institutions. He has also participated in R&D projects related to complex systems and artificial intelligence-based solutions.

He is the author or co-author of more than 60 scientific publications in peer-reviewed journals and three monographs. His academic achievements have been recognised with numerous awards, including a scholarship from the Minister of Science and Higher Education for outstanding young scientists, as well as Best Paper Award and Outstanding Paper Award distinctions from the Emerald Literati Network Awards for Excellence. He is also actively involved as a reviewer and statistical editor for scientific journals.

Dr hab. inż. Marcin Gąsior is an experienced researcher and expert with more than 20 years of experience in marketing, consumer behaviour and market research, conducted for both the academic and business sectors. He serves as Dean of the Faculty of Management at Lublin University of Technology and Head of the Department of Marketing, combining academic activity with management and development-oriented projects.

In his research and expert work, he focuses on consumer information acquisition processes, mechanisms of satisfaction and loyalty formation, perceived purchase risk, and marketing research methodology. As part of his research and expert activities, he carries out interdisciplinary projects involving the design of research tools, consumer and employee studies, modelling of decision-making processes, and analysis of measurement data using machine learning methods, including artificial neural networks. He has served as an expert and coordinator of research teams, including in the Eastern Business Accelerator project, and has participated in national grants and numerous commercial projects.

He is the author and co-author of numerous monographs, monograph chapters and several dozen scientific articles in the fields of marketing, consumer behaviour and social research methodology. He has also supervised more than ninety diploma theses, many of which have received awards in competitions organised by the Polish Scientific Marketing Society.

His approach integrates marketing research, research methodology and cooperation with business, enabling him to design and implement solutions that address real organisational challenges in the areas of decision-making, marketing strategy and data analysis. In his work, he applies and develops state-of-the-art, often non-standard data analysis methods, including advanced machine learning techniques and nonlinear modelling, adapted to the specific nature of complex market and organisational problems.

Dr Bartosz Przysucha is an experienced researcher, academic manager and data analytics practitioner, combining mathematical and engineering competences with the implementation of modern technologies in business. For many years, he has developed and coordinated initiatives at the intersection of management, artificial intelligence and quantitative methods, focusing on translating research results into useful solutions for organisations.

He serves as Vice-Dean for Education at the Faculty of Management, Lublin University of Technology, and as Acting Head of the Department of Quantitative Methods in Management. He is also the founder and head of the postgraduate programme Data Analysis. He co-created the degree programme Artificial Intelligence in Business and the English-taught programme AI in Business Solutions, ensuring a practical educational profile and a strong alignment of the curriculum with labour market needs.

In his research and development activities, he carries out projects in the fields of machine learning, deep learning, NLP/NLU and speech recognition, including applications supporting project management and service operations, as well as solutions for industry and diagnostics, such as cyber-physical systems, tomography and defectoscopy. He is the author and co-author of several dozen scientific publications, addressing, among other topics, the integration of data analytics and AI with organisational processes and systems.

He holds IPMA Level D certification and has extensive tool-related competences, as well as expert and organisational experience, including as the owner of StatTex, a company providing analytics and support for scientific research, an expert of the Eastern Business Accelerator, Vice-President of AIIQ Consulting, and a participant in work on recommendations concerning AI development policy in Poland.

Dr inż. Jakub Pizoń is an experienced manager and practitioner with more than twelve years of professional experience in business systems solutions for enterprises and public institutions. As a speaker, he actively participates in industry conferences, sharing expert knowledge gained through extensive consulting practice.

He conducts research and teaches in the areas of process management, artificial intelligence and modern information technologies related to Industry 4.0 and 5.0. As part of his R&D activities, he carries out advanced projects involving the application of large language models (LLMs) in medical transcription and project management.

He holds certifications in project management, including IPMA Level D, PSM I and AgilePM Foundation, as well as in business analysis, including ECBA issued by IIBA, and software sizing, including COSMIC Foundation. He is the author of more than forty scientific publications on the integration of technology with business processes.

He combines the perspective of an IT industry practitioner, a researcher involved in innovative R&D projects and an academic teacher, which enables him to deliver solutions addressing real organisational challenges in the era of digital transformation.

Dr hab. inż. Monika Kulisz, Associate Professor at Lublin University of Technology, is an experienced researcher and practitioner with more than 13 years of teaching and research experience at Lublin University of Technology. Since 2013, she has combined academic work with activities carried out at the interface of science and business practice. As a speaker, she actively participates in scientific and industry conferences, sharing expert knowledge gained through practice and experience in preparing expert reports and opinions for implementation and innovation projects.

She conducts research and teaches in the areas of artificial intelligence and machine learning, production engineering and manufacturing technologies, as well as logistics and process analysis related to digitalisation and process improvement in industrial environments. As part of her R&D activities, she carries out advanced projects involving the modelling and prediction of machining process parameters, including magnesium alloys, using artificial neural networks, as well as the application of AI and deep learning methods in process monitoring and control systems and in the area of supply chains.

She is the author of 70 scientific articles and 10 popular science articles, as well as one monograph and more than 30 chapters in monographs. Her work also has an implementation-oriented dimension: she holds a total of nine granted patents or submitted patent applications, and the results of her research and development activities are reflected in technical solutions developed also in cooperation with the business environment.

She combines the perspective of an engineer and AI researcher with teaching experience and practical cooperation with the socio-economic environment, which enables her to design methodical and useful solutions supporting data analysis, prediction and process optimisation in real industrial and logistics applications, in the spirit of digital transformation and the concept of Industry 5.0.

Dr inż. Marta Juszczyk is an experienced researcher specialising in information technologies in organisations. As a speaker and lecturer, she actively participates in training activities, sharing expert knowledge in the field of automation.

She conducts teaching and research in the areas of automation and the implementation of new technologies in enterprises. As part of her training activities, she carries out outreach and educational projects for young people, teachers, Polish and international students, as well as foreign universities. She also cooperates with practitioners in the area of knowledge exchange.

She is a graduate of the postgraduate programme Business Process Automation at Kozminski University and has completed specialist training courses, including AI in the work of analysts and architects, as well as business process modelling.

She draws on scientific literature, her own research and knowledge gained from practitioners, which gives her access to a broad spectrum of good practices in automation.

MSc Eng. Konrad Kania is an experienced analyst with more than nine years of professional experience in algorithm design and data analysis for companies operating in the R&D sector. As a speaker, he actively participates in conferences, sharing expert knowledge in the broad field of artificial intelligence.

He conducts research and teaches in the areas of machine learning, artificial intelligence and data analysis related to industrial applications. As part of his R&D activities, he carries out innovative projects involving the application of mathematical modelling and non-ionising tomography.

He is the author of thirty-eight scientific publications in the fields of image processing, industrial tomography and machine diagnostics.

He combines the perspective of an R&D researcher and academic teacher, which enables him to deliver solutions addressing real organisational challenges in the context of data-driven management.