Jacek Marczyk PhD

Intellectual Property

Dr. Marczyk has authored and co-authored various books and owns the following Intellectual Property:

SDI Algorithm: SDI (Stochastic Design Improvement) is a method for finding solutions to very large-scale design problems, that would be impossible to solve using classical optimization techniques. The method is a mix of genetic techniques and Monte Carlo simulation and allows one to identify multiple solutions via an inverse approach: the user specifies what performance he seeks, SDI provides which values of the design variables deliver that particular performance. Unlike conventional optimization, the method allows to use very realistic models instead of simplistic response surfaces. The SDI has been developed in 1998.

Eigenvalue Orbits: A novel approach to the problem of characterizing and controlling generic dynamic systems without a-priori knowledge of their structure. The approach stems from the concept of Eingenvalue Orbit, introduced by J. Marczyk in 1999, which provides a new means of viewing the general transient and stability properties of dynamic systems. Eigenvalue Orbits are a generalization of the concept of eigenvalue. The theory of Eigenvalue Orbits has been published in the Journal of Guidance, Control and Dynamics, a peer-reviewed publication of the American Institute of Aeronautics and Astronautics.

Generalized correlation: A novel approach to correlation which takes into account nonlinear aspects of data. The method treats data as images, emulating an expert “looking at it”. Data is analyzed by emulating the brain without the need to build math models. The method has its roots in quantum physics, nonlinear mechanics and biology.

Complexity metric: The first complexity metric for generic systems and the algorithm to compute it has been introduced by Dr. J. Marczyk in 2005. A part of the algorithm has been patented in the USA in 2009. Complexity is defined as a function of the structure of information flow within a system and entropy, which measures disorder as well as information content. Formally, complexity is defined as C = f(S; E), where S reflects structure and E is entropy (‘disorder’). Based on this formulation, complexity measures the total amount of structured information in a system. The metric is bounded – the upper bound is known as critical complexity. Marczyk’s metric is the first one which combines explicitly structure and entropy and shows that complexity is not just a number; it is an intrinsic property of all dynamical systems and its importance is comparable to that of energy. The formulation is a candidate Fourth Law of Thermodynamics and established the foundations of Artificial Intuition, an advanced form of Artificial Intelligence that does not require learning.

Artificial Intuition: The fourth generation of AI is ‘artificial intuition,’ which enables computers to identify threats and opportunities without being told what to look for, just as human intuition allows us to make decisions without specifically being instructed on how to do so. Artificial Intuition reaches beyond the conventional Machine Learning (ML) approach. While ML works well when it comes to recognizing a face or handwriting, in the case of expensive and complex hardware it is impractical. The fact is that often there are not enough anomalies to learn from. Such anomalies can be hugely expensive and nobody – manufacturers or users – can provide a sufficient number of cases from which to learn. Besides, the number of possible anomalies is immense and it is impossible to define and learn to recognize them.

A large, transparent acrylic cube suspended above a minimalist pedestal, inside of which thousands of tiny illuminated points and filaments form a dynamic, three-dimensional web representing artificial intuition. Each point glows with a distinct color temperature, suggesting different data streams converging into emergent understanding. The cube stands in a pristine, gallery-like space with polished concrete floors and clean white walls. Overhead, soft, diffused spotlights create crisp highlights on the acrylic edges and delicate shadows beneath the pedestal. Photographic realism, shot at a three-quarter angle with ample negative space, produces a contemplative, almost museum-like atmosphere, emphasizing the elegance and sophistication of advanced cognitive systems.
An ultra-modern, matte-black workstation dominated by a large curved monitor displaying a detailed visual of quantitative complexity: multicolored nodes and directed links woven into a dense, three-dimensional network. On the desk, a heavy open notebook filled with tidy, handwritten equations is flanked by a brushed aluminum mechanical keyboard and a precision-engineered metal pen. The environment is a quiet, high-tech study with dark wood shelves lined by abstract, spine-free volumes and geometric metal objects. Cool, indirect LED strip lighting traces the edges of the desk, creating subtle rim light and reflections. Photographic realism, captured from a slightly elevated angle with balanced composition, establishes a mood of disciplined research and theoretical depth.

Intellectual Property Pillars

My core contributions—Quantitative Complexity Theory and Artificial Intuition—provide rigorous, computable ways to measure complexity and embed intuition into decision‑making systems. Explore how these frameworks translate into patents, methods, and tools, and dive deeper in the Publications section.

View publications

Engagements

A sleek, glass-topped executive desk covered with precisely arranged scientific instruments and entrepreneurial artifacts: a polished metal rocket model, a transparent 3D-printed brain sculpture glowing faintly from within, and a black tablet displaying a complex network graph of interconnected nodes. The desk sits before a floor-to-ceiling window overlooking a modern cityscape at dusk. Cool, diffused twilight blends with the warm glow of a minimalist desk lamp, casting crisp, professional reflections on the glass surface. Photographic realism, shot at eye level with a shallow depth of field, keeps the objects in sharp focus while the city blurs into soft bokeh, conveying intellect, innovation, and high-level scientific entrepreneurship.

Partner with Jacek for strategic advisory, deep‑dive research collaborations, or structured licensing discussions around Quantitative Complexity and Artificial Intuition.

A large, transparent acrylic cube suspended above a minimalist pedestal, inside of which thousands of tiny illuminated points and filaments form a dynamic, three-dimensional web representing artificial intuition. Each point glows with a distinct color temperature, suggesting different data streams converging into emergent understanding. The cube stands in a pristine, gallery-like space with polished concrete floors and clean white walls. Overhead, soft, diffused spotlights create crisp highlights on the acrylic edges and delicate shadows beneath the pedestal. Photographic realism, shot at a three-quarter angle with ample negative space, produces a contemplative, almost museum-like atmosphere, emphasizing the elegance and sophistication of advanced cognitive systems.

Engagements are tailored for startups, R&D teams, and investors seeking defensible innovation grounded in rigorous complexity metrics and intuition‑driven frameworks.