Neelu Madan

Neelu Madan is a Postdoctoral Researcher at the Department of Architecture, Design and Media Technology, Section for Media Technology, within The Technical Faculty of IT and Design at Aalborg University, Denmark. Her research focuses on computer vision and machine learning with applications in video surveillance and anomaly detection.

Dr. Madan completed her PhD in Computer Science at Aalborg University in 2023. Her doctoral thesis, "Towards Limited Label Learning for Visual Surveillance", established her expertise in limited-label learning paradigms for surveillance systems.

Her research spans anomaly detection, deep learning, and computer vision, with significant contributions in self-supervised learning for video analysis. She specializes in transformer architectures, masked autoencoders, and synthetic data generation, addressing challenges in multi-object tracking and event detection under limited supervision.

Recent publications (2023-2024) reveal a strong trend toward foundation models for video understanding and self-supervised anomaly detection. Her work bridges theoretical advances in representation learning with practical applications in thermal imaging, fashion technology, and harbor safety systems.

Scientific recognition includes:

• Spar Nord Fondens Forskningspris (2024)

Dr. Madan is actively involved in externally funded research as Co-Investigator on three major projects: AICF: AI Color Fashion (2023-2026), Generic Object Tracking (2020), and Self-Supervised Learning For Video Anomaly Detection (2020-2023). While no formal advisees are documented, her postdoctoral role likely involves mentoring junior researchers.

She operates within Aalborg University's Visual Analysis and Perception research group, maintaining strong industry collaborations with Milestone Systems on video surveillance applications and harbor safety technology.