Yuki M. Asano

Yuki M. Asano is a full Professor at the University of Technology Nuremberg, leading the Fundamental AI (FunAI) Lab. Previously, he led the QUVA Lab at the University of Amsterdam and earned his PhD at the Visual Geometry Group (VGG) of the University of Oxford under Andrea Vedaldi and Christian Rupprecht.

• University of Technology Nuremberg (2024–present)
• University of Amsterdam (prior to 2024)
• University of Oxford (PhD, 2020)

His research spans Artificial Intelligence, Machine Learning, and Computer Vision, with a focus on Causal Representation Learning, Self-Supervised Learning, and Efficient Model Adaptation. He pioneered techniques like BISCUIT (causal variable identification) and VeRA (parameter-efficient fine-tuning). His work extends to Medical Imaging and Environmental Monitoring through applications in fetal ultrasound analysis and marine debris detection.

Recent publications (2023–2025) highlight advancements in Self-Supervised Learning, Vision-Language Models, and 3D Understanding. Notable papers include TWIST & SCOUT (multimodal LLM grounding), SIGMA (masked video modeling), and GeneralAD (anomaly detection). His ICCV 2023 work on Self-Ordering Point Clouds and MoSiC (optimal-transport motion trajectories) underscores his interdisciplinary approach.

He received the JUPITER compute grant (2025) and an Outstanding Paper Award at ICLR 2024. His collaborations span institutions like MIT-IBM Watson AI Lab, Qualcomm AI Research, and University of Amsterdam.