Multimodal Anomaly Detection Workshop 2026

About

Anomaly detection is highly important in many machine learning-driven fields, yet developing mostly independently for different data modalities such as audio, EEG signals, images, text, videos or time-series in general. This workshop aims at bringing together experts in anomaly detection from different communities and at promoting joint research activities of its members.

This workshop is part of the P1 Program Multimodal Anomaly Detection, directed by Kevin Wilkinghoff, Neelu Madan, and Juan Miguel Valverde.

Program

09.00 Registration

09.30 Opening remarks and introduction to the P1 Program

09.45 Keynote on Scalable real-time abnormal event detection by Radu Ionescu, Professor at the University of Bucharest

10.30 Keynote on Anomalous Sound Detection by Wenwu Wang, Professor at the University of Surrey

11.15 Coffee break

11.30 Contributed Talk on Anomaly detection and self-explainability of vessel behavior based on AIS data by Line Katrine Harder Clemmensen, Professor at the University of Copenhagen, Dept. of Mathematical Sciences

12.00 Contributed Talk on Detecting adversarial audio in deep speech systems by Zheng-Hua Tan, P1 Co-lead of the Signals and Decoding Collaboratory and Professor at Aalborg University

12.30 Lunch break

13.30 Contributed Talk by Rafal Wisniewski (TBA)

14.00 Poster Session and Networking

15.00 Coffee break

15.15 Keynote Talk on Privacy preserving video surveillance and detecting anomalies where it matters most by Kamal Nasrollahi, Director of Research at Milestones System and Professor at Aalborg University

16.00 Panel Discussion: Toward a unified agenda for multimodal anomaly detection

16.45 Closing remarks and next steps

17.00 End of workshop

Find more information about the workshop, program, and speakers on the Multimodal Anomaly Detection Workshop webpage.

This workshop offers travel grants for early-stage researchers.
Apply for travel grants and register here.

Deadline for registration for travel grant applicants is 31 December, 2025.
Deadline for registration is 11 January, 2026.