About

With a PhD in AI from Gdansk University, his academic and professional journey encompasses pioneering research, teaching at Sydney University, and leading innovative projects in logistics, cybersecurity, and computer vision. Dr. Kaplanski’s work, underscored by 45 papers and multiple patents, reflects his commitment to leveraging technology for optimizing supply chains and enhancing data security. As the founder and leader of teams behind several successful startups, his contributions not only push the boundaries of AI application but also aim to solve complex societal challenges.

Education

Doctor of Philosophy (Ph.D.) in Computer Science

  • Institution: Gdańsk University of Technology, Faculty of Informatics and Telecommunication
  • Location: Gdańsk, Poland
  • Dates: 06/02/2009 - 23/04/2013
  • Thesis Title: “Ontology-Aided Software Engineering”
  • Thesis Overview: Explores the intersection of Artificial Intelligence, Knowledge Representation and Reasoning, and Software Engineering to address challenges in software development methodologies. The thesis proposes the use of Description Logic as a formalization of software engineering methods and tools, bridging the gap between theoretical principles and practical software development through the novel approach of Ontology-Aided Software Engineering (OASE). This approach leverages Controlled Natural Language for clearer, machine-processable communication within software development, aiming to improve quality, manage knowledge, and enhance the software production process.

Master of Science (M.Sc.) in Computer Science

  • Institution: Wrocław University of Technology, Faculty of Computer Nets and Systems
  • Location: Wrocław, Poland
  • Dates: 01/10/1996 - 17/10/2001
  • Details: Focused on computer networks and systems, emphasizing the design and optimization of network infrastructures and robust system security measures.

Selected Publications

  1. Kaplanski, P., Seganti, A., Ciesliński, K., Chrabrowa, A., & Lugowska, I. (2017). Automated reasoning based user interface. Expert Systems with Applications, 71, 125-137. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0957417416306686

  2. Rizun, N., Kaplanski, P., & Taranenko, Y. (Year). The method of a two-level text-meaning similarity approximation of the customers’ opinions. Studia Ekonomiczne, 296, 64-85.

  3. Rizun, N., Kaplanski, P., & Taranenko, Y. (2016). Development and research of the text messages semantic clustering methodology. In Proceedings of the 2016 Third European Network Intelligence Conference (ENIC), September 2016, pp. 180–187.

  4. Rizun, N., Kaplanski, P., Taranenko, J., & Seganti, A. (2016). Text-mining Similarity Approximation Operators for Opinion Mining in BI tools. Proceedings of the 11th Scientific Conference “Internet in the Information Society-2016”, pp. 121–141.

  5. Orłowski, C., Ngoc-Thanh, N., Kapłański, P., & Pietranik, M. (2016). The use of an ontotrigger for designing the ontology of a model maturity capsule. International Journal of Software Engineering and Knowledge Engineering. [Online]. Available: http://www.worldscientific.com/doi/abs/10.1142/S0218194016500236

  6. Kaplanski, P., Orłowski, C., Bach-Dąbrowska, I., & Wysocki, W. (2016). Hybrid Fuzzy-Ontological Project Framework of a Team Work Simulation System. International Journal of Knowledge and Systems Science (IJKSS), (7). [Online]. Available: http://www.igi-global.com/article/hybrid-fuzzy-ontological-project-framework-of-a-team-work-simulation-system/142837

Patents

  1. Atomically processing obligation payments for transactions in real time
    • Patent Number: WO2022120417A1
    • Issued: Jun 16, 2022
    • Summary: The patent provides systems and methods for atomically processing transactions including obligation payments. It features an automated system that automatically calculates and processes payments for transactions between both the primary parties and third parties. The system maintains the atomicity of financial transactions and ensures appropriate payments to third parties through an obligations account.
    • See Patent
  2. System and methods for dynamically automating reverse auctions
    • Patent Number: US20220148075A1
    • Issued: Sep 11, 2021
    • Summary: This patent describes systems and methods for automating reverse auctions dynamically. The technology allows for increased efficiency and transparency in conducting reverse auctions by automating various aspects of the auction process.
    • See Patent