Finture is a company that brings together consultants and experts from various fields—people with exceptional experience. The knowledge and skills we’ve gained, which we strive to share both within teams and with our clients, are transformed into tools that support the businesses of our partners. Among us are also individuals who pass on their knowledge by teaching the next generation of students. One such person is Dr. Andrzej Jankowski, Ph.D., Professor at UWM—author of approximately 70 scientific publications and co-author of two patent applications in the field of AI, which have been cited in patents from corporations such as IBM, Google, Microsoft, Yahoo!, HP, Oracle, Canon, Boeing, and Sony.
Andrzej Jankowski researches and develops new AI technologies based on interactive granular computations, aimed at enhancing the quality of AI applications in constructing learning decision-making systems used in complex applications. Examples of such practical applications in banking include applications supporting risk management (e.g., the risk of violating certain aspects of banking security or preventing banking fraud). During his time as a visiting professor at the Department of Computer Science at the University of North Carolina at Charlotte, he conducted research on the application of stochastic process simulations to the evolution of logical structures that support machine-based autonomous improvement of board game strategies. As a result, he created programs capable of machine learning and developing strategies for board games like chess, checkers, Go, etc. The primary goal of this research was the development of machine learning and the creation of optimal logical structures for building and improving strategies in board games. For this purpose, he used techniques such as machine discovery of knowledge based on hierarchical control of multisearch systems implemented via evolutionary programming (e.g., genetic algorithms) and various Monte Carlo techniques.
One of Dr. A. Jankowski’s most important achievements was co-creating and co-managing the implementation of the IT system for tax administration in Poland—POLTAX. It is a distributed system for recording and processing taxpayer data, operating in a Linux/Oracle environment and used by tax offices across the country. The system consists of many subsystems, each handling a specific aspect of public services (e.g., taxpayer registration and assigning NIP numbers, tax declarations, accounting and tax settlements, asset management, tax control, document libraries, fines…). Dr. Andrzej Jankowski's role involved creating the architecture, implementing system requirements, supporting implementation, and building and managing an IT team within the Ministry of Finance (about 1,500 IT specialists). The implementation of this system was one of the conditions for Poland’s accession to the European Union.
Together with Professor Andrzej Skowron, Dr. Andrzej Jankowski also proposed a new paradigm in AI technology—Wisdom Technology (WisTech) in the paper "A WisTech Paradigm for Intelligent Systems," which, among other things, provides computational models for the next generation of IoT (Internet of Things). The WisTech paradigm is an attempt to address the problem of building autonomous decision-making systems (with a satisfactory degree of accuracy) in unknown, complex environments. The creation of this paradigm was based on the authors’ experiences in many projects, implementing WisTech components for applications such as MERIX—a prototype fraud detection system created for Bank of America, EXCAVIO—a dialog-based document search engine on the web, and an application for optimization and data mining within intelligent marketing for Ford Motor Company (GM). One of the key approaches to developing new computational models, for the authors, was previously discovered approaches to algebraic aspects of logic and approximate reasoning initiated by Z. Pawlak and H. Rasiowa, along with their students.
Dr. Jankowski is the author of the monograph "Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective (Lecture Notes in Networks and Systems)." This book is dedicated to examining the causes of the gap between theory and practice in complex systems engineering (e.g., economics or taxation) and minimizing the negative consequences resulting from these gaps. It is also an attempt to identify issues related to the generalization of computational models of complex adaptive systems, particularly natural computational models, by implementing the model of interactive granular computations (Interactive Granular Computing (IGrC)). This model refers to key mechanisms used to control processes related to building complex IT/AI applications.
Privately, Mr. Andrzej is an avid sailor of the Masurian lakes and equally enjoys spending his free time in the Beskid mountains.