Albert Ali Salah

Dr. Albert Ali Salah is professor and chair of Social and Affective Computing at the Information and Computing Sciences Department of Utrecht University. His research is broad, but mainly uses pattern recognition and machine learning for computer analysis of human behavior, with over 250 publications in these areas, including edited textbooks Computer Analysis of Human Behavior (2011, Springer), Data Science for Migration and Mobility (2022, Oxford University Press) and Privacy-Aware Monitoring for Assisted Living (2025, Springer Cham).

Dr. Salah has a PhD in Computer Engineering from Boğaziçi University (2007). He subsequently held positions at CWI, University of Amsterdam, and Boğaziçi University, as well as a one-year visiting position at Nagoya University. His research group at Utrecht University investigates behavior at different scales; looking at individual behaviors (such as facial expression analysis), dyadic and group behaviours (e.g. child-parent or patient-doctor interactions), and at computational social science (e.g. mobile phone based analysis of migration and mobility). He was the coordinator of the Data for Refugees (D4R) Challenge between 2016-2019, and directed the mobile phone workpackage in the HumMingBird EU project. He is also a member of the AI and Animal Welfare Lab in Utrecht.

Dr. Salah was the inaugural recipient of the EBF European Biometrics Research Award (2006), and a recipient of the GEBIP award of Science Academy (2017). He served as a program committee member of over 200 conferences, and as associate editor of several journals, including IEEE Trans. Affective Computing, IJHCS, and Pattern Recognition. He chaired ACM ICMI 2014, ISSI 2015, SPECOM 2019, IEEE FG 2024 conferences, and served in the Steering Boards of ACM ICMI and IEEE FG, and as VP Conferences for the IEEE Biometrics Council. He is a Senior Member of the ACM and of IEEE.

• Computer vision based assessment of animal pain
  Rapid progress in computer-based automation approaches created new opportunities - and posed new challenges- for research and applications in animal wellbeing. Innovative systems are being...
• Data collaboratives and using mobile phone data for social good
  New sources of human behavior data can empower humanitarian projects, but they need to be carefully handled, properly anonymized and aggregated. In this talk, I will discuss the potential...
• Designing computational tools for behavioral and clinical science
  Automatic analysis of human affective and social signals brought computer science into closer alignment with social sciences, enabling new collaborations between computer scientists and...