Milan Jovovic has worked on informatics of complex systems for about 35 years. In different fields of study and perspectives. He has acquired a broad theoretical knowledge in applying mathematical modeling in physics, neuroscience, and bioinformatics.

He has written a theory of stochastic resonance synergies for the analysis and study of complex systems. In this theory, information is propagated by the Green function of scale-space waves, and quantum tunneling. The evolution dynamics along a path integral have been derived, applying the principle of least action. Multidimensional scaling properties of quantum information electromagnetism have been described, making it a bridge to the mathematical foundation of quantum field theory.

“3-6-9” algebraic structure has been introduced in describing the invariance properties of the Lagrangian dynamics descriptors. The mass conservation principle applies synergistic binding of stochastic resonances, regardless of light and/or dark energies. The scale—periodic arrangements of atomic compositions—has been explained.

Asymptotic freedom of motion in triplet synergies translates to the so-called “fine structure constant.” The mirror image analysis of twin primes’ synergies confirms Riemann’s hypothesis. The scale-space wave function preserves information about the prime number structure distribution. Showing, accordingly, the mathematical interpretation of quantum number descriptors.

Triplet synergisms have been studied in experiments with human perception and movements. Cross-modal analysis of intensity-independent auditory distance perception, color constancy, and synergistic control of equilibrium positions in reaching movements has been presented. The holographic principle of quantum information carriers has been proposed in attention, memory, and behavioral data studies.

At Safarik University, in an auditory perception experiment, behavioral paradigms have been studied along the signal intensity and distance dimensions. The methodology of stochastic resonances showed that the intensity-independent auditory distance feature detector is within a synergistic information flow of the tonotopic map of the auditory cortex.

At Indiana University, they have examined covariant differentiability for data mining applications in chemistry and bioinformatics. Numerical schemes for scale-space computing with high-dimensional data sets have been derived. Parallel algorithm implementation on multicore processors has been analyzed, and the statistical maps of data decomposition have been shown.

On his postdoc stage at the INRIA, they have worked on a harmonic signal decomposition of the IR satellite images. Turbulent flow dynamics has been studied, and a rain process shown, corresponding to perturbations caused by the fusion of convective clouds.

For his doctoral thesis at the University of Belgrade, they have described learning and synergistic control of reaching movements. While an undergraduate, he took part in the Balkan’s students competition in mathematics as a representative of Yugoslavia.

He had started working in computational neuroscience and physics as a graduate student at Caltech. His common line of research describes complex systems dynamics based on coupled wave information propagation and quantum information expression in 5-dimensional scale-spaces. The initial report has been published on random stereograms. Introducing, consequently, a new way of scale-space topology mapping in neuroscience and physics.

His current research interests include bioinformatics, neural data science, and quantum computing.

References

¹ Jovovic, M., [1994], A Markov random fields model for describing unhomogeneous textures: generalized random stereograms. IEEE Workshop Proceedings on Visualization and Machine Vision and IEEE Workshop Proceedings on Biomedical Image Analysis, Seattle.

² Jovovic, M., [1996], Image segmentation for feature selection from motion and photometric information by clustering. SPIE Symposium on Visual Information Processing V, Orlando.

³ Jovovic, M., S. Jonic, D. Popovic, [1999], Automatic synthesis of synergies for control of reaching—hierarchical clustering. Medical Engineering and Physics 21/5:325-337.

⁴ Jovovic, M., [2001], Space-Color Quantization of Multispectral Images in Hierarchy of Scales, Int. Conf. on Image Processing, Thessaloniki, Greece, pp. 914-917.

⁵ Jovovic, M., H. Yahia, I. Herlin, [2003], Hierarchical scale decomposition of images—singular feature analysis, Technical Report—INRIA, AIR Lab.

⁶ Jovovic, M., G. Fox, [2007], Multi-dimensional data scaling—dynamical cascade approach, Technical Report—Indiana University.

⁷ Jovovic, M., [2015], Stochastic Resonance Synergetics—Quantum Information Theory for Multidimensional Scaling, Journal of Quantum Information Science, 5/2:47-57.

⁸ Jovovic, M., [2019], Attention, Memories, and Behavioral Data-Driven Study, 6th International Conference on Neuroscience and Neurological Disorders, Prague.

⁹ Jovovic, M., [2021], Multidimensional Information Scaling: Manifestation of the Mind-Body Connection. EC Neurology, 13, 11.

¹⁰ Jovovic, M., [2023], The Light and Sound Triplet Codes in Human Perception—Making Sense of the World in 5D, Acta Scientific Neurology 6.7: 22-23.