Keynote Speakers

Sergi Pujades graduated in applied mathematics and computer science in 2005. He majored in computer vision, computer graphics and virtual reality. After working in industry in the field of stereoscopic cinema, he did his PhD on “Camera models and algorithms for video content creation”. 

He was a Post-Doctoral researcher at Max Planck Institute in Tübingen, in Germany. Collaborating with Michael Black, he started working on human body models and their applications in the medical field. Since 2018 he is an associate professor at Grenoble Alpes University in France, teaching Computer Vision in the international master and conducting research at Inria Grenoble. Sergi’s research seeks to model and understand the human geometry and motion with the goal to create digital tools to support clinical practitioners.

After studying mathematics and physics, computer engineering and systems control, Prof. Navab did his doctorate at INRIA / Paris XI. He then did two years of postdoctoral research at MIT Media Laboratory in Cambridge, USA. 

Prior to becoming a full professor at TUM in 2003, Prof. Navab was a distinguished member of the technical staff at Siemens Corporate Research (SCR) in Princeton, USA. In 2006, he became a board member of MICCAI, the organizer of the world’s leading conference on medical image computing and computer assisted intervention. He is on the editorial board of many international journals, including IEEE TMI, MedIA and Medical Physics. Prof. Navab has authored hundreds of scientific publications and has filed over 60 international patents.

Dima Damen is a Professor of Computer Vision at the University of Bristol and Senior Research Scientist at Google DeepMind. Dima is currently an EPSRC Fellow (2020-2026), focusing her research interests in the automatic understanding of object interactions, actions and activities using wearable visual (and depth) sensors. 

She is best known for her leading works in Egocentric Vision, and has also contributed to novel research questions including mono-to-3D, video object segmentation, assessing action completion, domain adaptation, skill/expertise determination from video sequences, discovering task-relevant objects, dual-domain and dual-time learning as well as multi-modal fusion using vision, audio and language.

Georgios Pavlakos is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin. Before that, he was a Postdoctoral Researcher at UC Berkeley, advised by Angjoo Kanazawa and Jitendra Malik. He completed his PhD in Computer Science at the University of Pennsylvania advised by Kostas Daniilidis. He did his undergraduate studies at the National Technical University of Athens, where he worked with Petros Maragos. During his PhD, he spent time at the Max Planck Institute in Tübingen, working with Michael Black. 

Umar Iqbal is a Sr. Research Manager at NVIDIA Research, leading the Data-Drive AI for Robotics (DAIR) team. The team investigates how robots can learn directly from human data, such as videos, motion capture, and large-scale demonstrations, to acquire skills that generalize across tasks, embodiments, and environments. They work at the intersection of computer vision, machine learning, and robotics, developing models that understand, reconstruct, and imitate human behaviors. 

Umar earned his PhD in Computer Science (2014-2018) from the University of Bonn, Germany, under the guidance of Prof. Juergen Gall. Prior to that, he completed his masters (2011-2013) in Finland and undergrad (2006-2010) in Pakistan.