Alan Hanjalic

Professor, IEEE Fellow, AAIA Fellow
Antoni van Leeuwenhoek Chair
Head of the Multimedia Computing Group
Head of the Intelligent Systems Department

Prof. Hanjalic is a globally recognized scientific leader in Multimedia Information Retrieval (MIR). His research focuses on developing effective, intuitive and socially responsible methods for accessing and interacting with vast multimedia data collections. His groundbreaking research has shaped the MIR field and has had high and lasting impact along several MIR research directions, earning him the prestigious IEEE Fellow recognition in 2016.

His early work on content-based video segmentation and representation resulted in foundational techniques and publications that have served as standard references in the field for many years. Later on, recognizing the limitations of traditional semantic-based video retrieval, he pioneered the concept of affective content analysis in 2001, aiming to understand and respond to viewers' emotional reactions to videos. He was the first to propose an integral framework for affective video content representation and modeling, enabling video indexing using emotional cues and in this way facilitating access to video segments based on the emotions they evoke. By modeling videos as curves in the arousal-valence space, he revealed the expected affective reactions of a user to a video over time and enabled more nuanced video browsing and retrieval, surpassing traditional classification-based methods. Over the years, affective content analysis, indexing and retrieval have become a major subfield of MIR.

Prof. Hanjalic's research focus has gradually shifted to address critical challenges in recommender systems. His group's pioneering work, awards and recognitions, including the ACM Recommender Systems Grand Challenge win in 2010 and Best Paper Award in 2012, have solidified their international leadership in the field. Building upon their successes, Prof. Hanjalic and his team are committed to developing socially responsible recommender systems with a focus on bias, fairness, and privacy.

For a comprehensive overview of Prof. Hanjalic's career and achievements, please refer to his CV, ACM profile, and list of publications.