Björn Granström (KTH, Stockholm, Sweden) 

Björn Granström joined the department of Speech, Music and Hearing at KTH, Stockholm in 1969, after graduating as MSc in Electrical Engineering. After further studies in Phonetics and General Linguistics at Stockholm University he became Doctor of Science at KTH in 1977 with the thesis "Perception and Synthesis of Speech". In 1987 he replaced Gunnar Fant as Professor in Speech Communication. He has been the director of CTT, The Center for Speech Technology, since its start in 1996.

The research at CTT initially includes the following five areas:

-    Speech technology in interactive dialogue systems

Integration of speech technology in advanced interactive demonstrators

-    Language models for spoken language, including dialogue models

Creation of speech technology-motivated language and dialogue models for Swedish

-    Methods for automatic speech understanding

Development of state-of-the-art automatic speech recognition for Swedish

-    Principles of speaker characterisation

Creation of models of speakers for use in systems for speaker verification, speech recognition with rapid speaker adaptation and individualized speech synthesis

-    Speech production for multi-modal speech synthesis

Development of articulatorily motivated, highly natural multi-modal parametric


Jürgen Schmidhuber (IDSIA, SUSPI & University of Lugano, Switzerland & TU Munich, Germany) 

Jürgen Schmidhuber: 1963 born in Munich;1987 Diploma in computer science from TUM; 1991 PhD; 1991-93 postdoc at University of Colorado at Boulder, 1993 Habilitation at TUM. Since 1995 co-director of the Swiss AI lab IDSIA in Lugano, which he helped transform into one of the world's top 10 AI labs (the smallest!), according to Business Week (1997). Since 2003 Prof. SUPSI, Switzerland. Since 2004 Head of TUM Cogbotlab. 2004-2009 also Professor Extraordinarius of Cognitive Robotics in the Faculty of TUM Computer Science, working on robot learning. Since 2009 also Professor of Artificial Intelligence at the University of Lugano, Switzerland. Best known for his algorithms for learning programs running on recurrent neural networks (RNNs) and other computers (e.g., OOPS and GP), non-halting Turing machines and generalizations of Kolmogorov complexity, optimal universal learners, Goedel machines and earlier self-referential meta-learners, reinforcement learning, artificial evolution, non-linear ICA, artificial curiosity, a complexity-based theory of beauty, low-complexity art (a new minimal art form based on algorithmic information theory), the speed prior for optimal computable inductive inference in quickly computable universes, and an algorithmic theory of everything. Interested in statistical robotics, evolving RNNs for robot control, learning attentive vision, hierarchical learning, time series prediction, financial forecasting, robot cars, resilient machines with self-models, robot hands and arms with elastic tendons and muscles, artificial music composition, artificial ants.

IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale) is a non-profit oriented research institute for artificial intelligence, affiliated with both the Faculty of Informatics of the University of Lugano and the Department of Innovative Technologies of SUPSI, the University of Applied Sciences of Southern Switzerland. We focus on machine learning (artificial neural networks, reinforcement learning), optimal universal artificial intelligence and optimal rational agents, operations research, complexity theory, and robotics.


Bernt Schiele (TU Darmstadt, Germany) 

Bernt Schiele is Full Professor of Computer Science at TU Darmstadt since April 2004.

He studied computer science at the University of Karlsruhe, Germany. He worked on his master thesis in the field of robotics in Grenoble, France, where he also obtained the "diplome d'etudes approfondies d'informatique". In 1994 he worked in the field of multi-modal human-computer interfaces at Carnegie Mellon University, Pittsburgh, PA, USA in the group of Alex Waibel. In 1997 he obtained his PhD from INP Grenoble, France under the supervision of Prof. James L. Crowley in the field of computer vision. The title of his thesis was "Object Recognition using Multidimensional Receptive Field Histograms". Between 1997 and 2000 he was postdoctoral associate and Visiting Assistant Professor with the group of Prof. Alex Pentland at the Media Laboratory of the Massachusetts Institute of Technology, Cambridge, MA, USA. From 1999 until 2004 he was Assistant Professor at the Swiss Federal Institute of Technoly in Zurich (ETH Zurich).

His main research interests are in computer vision, perceptual computing, robotics, statistical learning methods, wearable computers, and integration of multi-modal sensor data. He is particularly interested in developing methods which work under real-world conditions.


Moshe Bar (Harvard, USA) 

Moshe Bar was born in Beer-Sheva, Israel. He received his B.Sc. degree in Electrical Engineering from Ben-Gurion University, Israel in 1988, and his M.Sc. degree in Computer Science and Applied Mathematics from The Weizmann Institute of Science, Israel in 1994. He went on to obtain his Ph.D. in Cognitive Neuroscience Program from the University of Southern California in 1998. He then completed a post-doctoral research fellowship in the Department of Radiology at Martinos (NMR) Center for Biomedical Imaging and at Harvard University from 1988 to 2001. Bar is an Associate Professor in Radiology at Harvard Medical School and an Assistant in Neuroscience at the Martinos Center for Biomedical Imaging at MGH.

Bar uses a Cognitive Neuroscience approach to study the underlying cortical and behavioral mechanisms. Specifically, combining cognitive methods with neuroimaging technology (functional magnetic resonance imaging, fMRI and magnetoencephalography, MEG), his laboratory addresses this goal from multiple directions. His long-term goal is to define and test individual unifying principles that would provide an overarching explanation for many of the astonishing feats of the cognitive brain in simple terms.


Toon Goedemé (De Nayer Institute, associated to KU Leuven, Belgium) 

Toon Goedemé obtained a Masters in Electrotechnical Engineering (Multimedia and Signal Processing) at the Katholieke Universiteit Leuven in Belgium in June 2002. Since September 2002, he has been working as a research assistant at the Computer Vision Lab (VISICS) under the supervision of Prof. Luc Van Gool. Since september 2006 he is a professor at the De Nayer Institute, Sint-Katelijne-Waver, Belgium.

Research interests:

-    Wide baseline matching

-    Panoramic cameras

-    Vision-based robot navigation

-    Topological world models

-    Vision-based localization

-    Visual servoing

-    Assistive robotics for disabled persons

-    Embedded and Real-time systems

-    Implementation of Computer Vision algorithms in programmable hardware (FPGA)

-    Model-based design of digital algorithms