2016 ChaLearn Looking at People Workshop ECCV

Björn W. Schuller

University of Passau, Passau, Germany

schuller@ieee.org

Björn W. Schuller is Full Professor and Chair of Complex and Intelligent Systems at the University of Passau/Germany, Reader (Associate Professor) in Machine Learning at Imperial College London/UK, and the co-founding CEO of audEERING. Further affiliations include HIT/China as Visiting Professor and the University of Geneva/Switzerland and Joanneum Research in Graz/Austria as an Associate. Previously, he was with the CNRS-LIMSI in Orsay/France and headed the Machine Intelligence and Signal Processing Group at TUM in Munich/Germany. There, he received his diploma in 1999, doctoral degree in 2006, his habilitation in 2012, and was entitled Adjunct Teaching Professor – all in electrical engineering and information technology. Best known are his works advancing Intelligent Audio Analysis and Affective Computing. Dr Schuller is President Emeritus of the AAAC, elected member of the IEEE SLTC, and Senior Member of the IEEE. He (co -)authored 5 books and >500 peer reviewed technical contributions (>10,000 citations, h-index = 49). Selected activities include his role as Editor in Chief of the IEEE Transactions on Affective Computing, Associate Editor of Computer Speech and Language, IEEE Signal Processing Letters, IEEE Transactions on Cybernetics, and IEEE Transactions on Neural Networks and Learning Systems. Professor Schuller was General Chair of ACM ICMI 2014, Program Chair of ACM ICMI 2013, IEEE SocialCom 2012, and ACII 2015 and 2011, as well as organiser of the INTERSPEECH 2009-2016 annual Computational Paralinguistics Challenges, the 2011-2016 annual Audio/Visual Emotion Challenges, and the MAPTRAITS Personality Challenge. He won several awards including best results in research challenges such as CHiME, MediaEval, or of ACM Multimedia. In 2015 and 2016 he has been honoured as one of 40 extraordinary scientists under the age of 40 by the World Economic Forum.

Maja Pantic

Imperial College, London, United Kingdom

m.pantic@imperial.ac.uk

Maja Pantic is a Professor of Affective and Behavioral Computing in the Imperial College and leader of the i·BUG group, working on machine analysis of human non-verbal behaviour and its applications to humancomputer, human-robot, and computer-mediated human-human interaction. Prof. Pantic published more than 200 technical papers in the areas of machine analysis of facial expressions, machine analysis of human body gestures, audiovisual analysis of emotions and social signals, and humancentered machine interfaces. She has more than 12,000 citations to her work, and has served as the Key Note Speaker, Chair and Co-Chair, and an organization/ program committee member at numerous conferences in her areas of expertise.

Michel Valstar

University of Nottingham, Nottingham, United Kingdom

michel.valstar@nottingham.ac.uk

Michel Valstar is an Associate Professor at the University of Nottingham, School of Computer Science, and a researcher in Automatic Visual Understanding of Human Behaviour. He is a member of both the Computer Vision Lab and the Mixed Reality Lab. Automatic Human Behaviour Understanding encompasses Machine Learning, Computer Vision, and a good idea of how people behave in this world.Dr Valstar is currently coordinator of the H2020 LEIT project ARIA-VALUSPA, which will create the next generation virtual humans. He has also recently been awarded a prestigious Melinda & Bill Gates foundation award to automatically estimate babies' gestational age after birth using the mobile phone camera, for use in countries where there is no access to ultrasound scans. Michel was a Visiting Researcher at the Affective Computing group at the Media Lab, MIT, and a research associate with the iBUG group, which is part of the Department of Computing at Imperial College London. Michel’s expertise is facial expression recognition, in particular the analysis of FACS Action Units. He recently proposed a new field of research called 'Behaviomedics', which applies affective computing and Social Signal Processing to the field of medicine to help diagnose, monitor, and treat medical conditions that alter expressive behaviour such as depression.

Daniel Gatica-Perez

IDIAP, Switzerland

daniel.gatica-perez@epfl.ch

Prof. Daniel Gatica-Perez directs the Social Computing Group at Idiap Research Institute and the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland. His work integrates methods from ubiquitous computing, social media, machine learning, and social sciences to understand human and social behavior in everyday life. His research has studied connections between behavioral cues and human traits and states in social video and face-to-face interaction.

Roland Goecke

Unviersity of Canberra, Australia

roland.goecke@canberra.edu.au

Since January 2015, I am Professor of Affective Computing at the newly created (merged) Faculty of Education, Science, Technology and Mathematics at the University of Canberra. Before that, I was an Associate Professor in Software Engineering at the same Faculty and prior to that an Assistant Professor (Senior Lecturer) at the Faculty of Information Sciences and Engineering, University of Canberra from January 2010 until December 2012. Previously, I was also employed as a Research Fellow and Senior Lecturer since December 2008 at the same Faculty. I lead the Vision and Sensing Group and am Deputy Director of the Human - Centered Computing Laboratory.. My research focus continues to be in the areas of face and facial feature tracking and its applications, and more generally in Computer Vision, Affective Computing and Multimodal Human-Computer Interaction. I am also holding an adjunct research fellow / lecturer position with the Department of Information Engineering of the Research School of Information Sciences and Engineering (RSISE) at the Australian National University (ANU). I was an elected executive member of the Australian Speech Science and Technology Association (ASSTA) from December 2004 until September 2008. I am a member of the Human Communication Sciences Network (HCSNet), an ARC research network bringing together researchers and other interested parties on how humans communicate with each other and with computers. It was established in January 2005 for 5 years. I am also a member of the IEEE (Computer Society, Signal Processing Society), the International Speech Communication Association (ISCA), and the Australian Pattern Recognition Society.