Professor Adil Bagirov delivers a presentation at the institute’s scientific seminar

The Institute of Information Technology of the Ministry of Science and Education and Federation University Australia have maintained a productive collaboration for many years. Within the framework of this collaboration, scientific visits are organized, research experience and knowledge are exchanged, and joint PhD training programs are conducted.

The next scientific seminar of the Institute of Information Technology was dedicated to a presentation by Professor Adil Bagirov of Federation University Australia entitled “An Optimization Model and Algorithm for Semi-Supervised Clustering.” This seminar was an important scientific event that demonstrates the consistent and purposeful development of this collaboration, as well as the successful continuation of the Institute’s integration into the international scientific community.

Opening the scientific seminar with a welcoming address, Academician Rasim Alguliyev, Vice-President of ANAS and Director General of the Institute of Information Technology, emphasized that Prof. Adil Bagirov is one of the distinguished Azerbaijani scientists widely recognized for his significant scientific research. He noted that Prof. Adil Bagirov has been working at Federation University Australia for 26 years and is engaged in the study of fundamental and applied problems in the field of data mining.

The Director General of the Institute also noted that Professor Adil Bagirov heads a number of scientific grant projects in Australia and maintains extensive and productive collaborative ties with researchers from various countries. Academician R. Alguliyev informed the seminar participants that Professor Adil Bagirov is currently conducting joint scientific research with scholars of the Institute of Information Technology in the fields of artificial intelligence and big data analytics.

Then, Professor Adil Bagirov delivered his presentation, noting that semi-supervised clustering can be viewed as a cluster analysis problem in which limited information about the data is available. He emphasized that such information typically appears in two forms: as class labels for a limited number of individual data points or as pairwise relationships indicating whether data items belong to the same cluster or to different clusters.

The researcher also noted that recent studies have further improved optimization approaches by enriching them with local methods. This has allowed for more effective management of constraints and the attainment of higher-quality clustering results.

Professor Adil Bagirov also provided information on the performance metrics used in semi-supervised clustering through optimization and presented the results obtained.

A broad exchange of views followed the presentation, and all questions were addressed.

Academician Rasim Alguliyev, in his remarks, highly praised the presentation. On behalf of the Institute’s staff, he expressed gratitude to Prof. Adil Bagirov. He also stressed the importance of continuing joint research and highlighted the significance of conducting future studies in AI, big data analytics, and other related fields.

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