Associate Professor Dr. Dariusz Siudak is a distinguished scholar in management sciences whose academic journey reflects continuous advancement in research excellence, interdisciplinary expertise, and leadership in the field of management and quality studies. He holds a Habilitated Doctor degree (2020) in social sciences with a specialization in management and quality studies, awarded by the Wroclaw University of Economics and Business. Earlier, he earned his Ph.D. in economic sciences (2012) with honors, focusing on enterprise value migration in the Polish capital market, under the supervision of Professor Krzysztof Jajuga. His academic foundation began at the Warsaw University of Technology, where he completed both his bachelor’s (2002) and master’s degrees (2006) with outstanding distinction, specializing in management, marketing, and enterprise functioning within integrated European markets. Throughout his career, Dr. Siudak has served in several academic roles, beginning as a specialist and assistant at the Warsaw University of Technology before joining the Lodz University of Technology, where he progressed from Assistant Professor to Associate Professor and currently serves as Head of the Division of Economics and Finance and a member of the Management and Quality Studies Discipline Council. Dr. Siudak’s research expertise focuses on the relational perspective of organizations, complex networks in financial markets, system dynamics, artificial intelligence, machine learning, and value-based management. His contributions integrate advanced analytical methods, network theory, and computational intelligence to study value migration, interlocking directorates, and corporate behavior within dynamic market structures. He has successfully led and contributed to several national research projects funded by the National Science Center and the Ministry of Science and Higher Education, emphasizing corporate value migration and network-driven firm behavior. His scholarly output includes highly cited publications in prestigious journals such as Expert Systems with Applications, PLOS ONE, Complexity, Physica A, and Social Network Analysis and Mining. These works demonstrate impactful contributions to understanding financial network structures, company value dynamics, and market behavior modeling using machine learning and network analytics. A recipient of numerous scientific awards, including multiple Rector’s Awards of the Lodz University of Technology, Dr. Siudak has been consistently recognized for his research excellence, innovative contributions, and organizational achievements. His accolades also include first place in the NetMiner 20th Event competition and nominations for the esteemed Beta Award in financial management. Additionally, he serves as an Academic Editor for PLoS One and PLOS Complex Systems and contributes to editorial boards supporting global scientific dissemination. With an aggregate impact factor exceeding 21, Dr. Siudak continues to be an influential figure in advancing modern management science through interdisciplinary methodologies and network-based research.
Featured Publications
Siudak, D. (2025). The dependency structure of the financial multiplex network model: New evidence from the cross-correlation of idiosyncratic returns, volatility, and trading volume. PLOS ONE, Published April 18, 2025.
Siudak, D. (2025). Unsupervised learning modeling of the impact of Black Swan events on financial network reconfiguration: New insights from the COVID-19 outbreak and the Russia–Ukraine war. Physica A: Statistical Mechanics and its Applications, 130277.
Siudak, D. (2024). Black Swan events in the financial market: A network approach [Data set]. Mendeley Data.
Siudak, D. (2022). The effect of self-organizing map architecture based on the value migration network centrality measures on stock return: Evidence from the US market. PLOS ONE, 17(11).
Siudak, D. (2022). A network analysis of the value migration process on the financial market: The effect of value migration network structure on stock returns. Expert Systems with Applications, 195, 116129.