Prof. Ali Abbasov

Director at Institute of Control Systems

A. Abbasov, born on January 1, 1953, into an intellectual family in Nakhchivan, boasts a distinguished academic and professional trajectory. Graduating from the Moscow Institute of Energy in 1976, he later earned the titles of Candidate of Technical Sciences (1981), Doctor of Technical Sciences (1994), and Professor (1996). Elected as a full member of the Azerbaijan National Academy of Sciences (ANAS) in 2001, Abbasov began his engineering career at the Institute of Cybernetics of ANAS in 1976, progressing through key roles until 1997.

Beyond academia, Abbasov served as the Rector of the State University of Azerbaijan (2000-2004) and held the position of Minister of Communications and Information Technologies of the Republic of Azerbaijan (2004-2015). Notably, he was a deputy of the AR Milli Majlis and a member of the delegation to the Parliamentary Assembly of the Council of Europe (PACE) from 2000 to 2004.

His scientific pursuits focused on information technology and management, covering topics such as topological methods for integrated circuits, control systems in computer networks, and the establishment of Internet infrastructure in Azerbaijan. Abbasov’s leadership in national and regional projects, including Azerspace-Telecommunications and Observation Satellites, has been pivotal.

With over 360 scientific works, including monographs, dictionaries, textbooks, and patents, Abbasov’s impact on academia is substantial. Under his guidance, 25 PhDs and 14 PhDs were prepared. In 2012, he was honored with the Order of Glory by the President of the Republic of Azerbaijan, solidifying his legacy as a distinguished academic and leader in information technology and management.

Keynote Speech:

An Intelligent Management System for Business Facilities Based on the Joint Use of Iot and Unmanned Technologies


The development of systems for intelligent control necessitates the creation of a comprehensive hardware and software complex capable of accurately emulating the methods of human decision-making. Unlike traditional computer modeling approaches, which often simulate abstract models, the emulation framework proposed in this article integrates processes for adaptation, learning, and planning within uncertain conditions, as well as handling vast volumes of data. This article presents a software and hardware complex based on both IoT and unmanned technologies. The convergence of these technologies on a unified IoT information platform significantly broadens the scope of adaptive (intelligent) management challenges faced by businesses amid uncertain conditions. Specifically, remote monitoring data (including multispectral imagery) captured by multicopters, combined with real-time sensor data from IoT devices, are used in the system to form the foundation for extracting contextual knowledge and facilitating prompt operational decisions