Prof. Hiqmet Kamberaj is a Professor at International Balkan University in Skopje, North Macedonia, where he also serves as the Coordinator of the PhD Program in Computer Engineering. He previously held the position of Acting Dean of the Faculty of Engineering (2017–2019). Prof. Kamberaj has an extensive academic and research background with over 100 publications, including journal articles and book chapters in internationally recognized journals. He is the author of five scholarly books published by leading academic publishers such as Springer Nature and De Gruyter. His interdisciplinary research focuses on macromolecular systems, computational modeling, thermodynamics, biophysics, applied mathematics, and machine learning methods to study complex biological and physical systems. Prof. Kamberaj actively contributes to the global scientific community as an editor-in-chief, editorial board member, and peer reviewer, and has presented his research at more than 40 international conferences worldwide.

Protein Structure Dynamics Manifolds and Topological Data Analysis:This presentation aims to communicate the advances and challenges in analyzing the computer simulation data of biomolecules and to present effective algorithms for analyzing protein structural dynamics. The focus is on emphasizing their impact and practical applications. We present new frameworks, such as topological data analysis and persistent homology, to describe the manifold of protein structure dynamics, focusing on their impact for advancing the understanding in the field. Furthermore, the asymmetric dynamic kernel-directed graphs, driven by entropic forces, describe information flow in this manifold and characterize protein configuration dynamics. The primary goal is to characterize changes in protein structure topology induced by mutations and to define the embedded manifold of the amino acid sequence interaction network using graph theory. In this communication, we demonstrate that encoding amino acid sequence information on a low dimensional manifold is statistically efficient. Then, using the topological data analysis, we observe protein structure changes in a multi-dimensional manifold, for example, due to amino acid mutations. The analysis highlighted that short equilibrium structure fluctuations at nanoseconds enable the construction of such a manifold, suggesting further exploration of these approaches.