Santosh Mathan is an Engineering Fellow at Honeywell Aerospace and a Principal Scientist in the Human Centered Systems group at Honeywell Laboratories. His research lies at the intersection of human computer interaction, machine learning, and biological signal processing. Santosh is the principal investigator and program manager on several efforts to use neurotechnology in practical settings. These efforts, carried out in collaboration with academic and industry researchers around the world, have led to the development of machine learning and signal processing algorithms that can estimate changes in cognitive function following brain trauma, identify fluctuations in attention, boost the activity of cortical networks underlying fluid intelligence, and serve as the basis for hands-free robotic control. Papers describing these projects have won multiple best paper awards at research conferences, and have been covered by the press in publications including the Wall Street Journal and Wired. He has been awarded over 19 US patents. Santosh has a doctoral degree in Human Computer Interaction from the School of Computer Science at Carnegie Mellon University, where his research explored the use of computational cognitive models for diagnosing and remedying student difficulties during skill acquisition. His talk takes place in December 2017 / January 2018.
Scaling up Cognitive Efficacy with Neurotechnology
Cognition and behavior arise from the activity of billions of neurons. Ongoing research indicates that non-invasive neural sensing techniques can provide a window into this never ending storm of electrical activity in our brains, and yield rich information of interest to system designers and trainers. Direct measurement of brain activity has the potential to provide objective measures that can help system designers and trainers in a variety of ways, including estimating the impact of a system on users during the design process, estimating cognitive proficiency during training, and providing new modalities for humans to interact with computer systems. In this presentation, Santosh Mathan will review research in the Honeywell Advanced Technology organization that offer novel tools and techniques to advance Human Computer Interaction. While many of these research explorations are at an early stage, they offer the preview of practical tools that lie around the corner for researchers and practitioners with an interest in boosting human performance in challenging task environments.
Jan Kybic was born in Prague, Czech Republic, in 1974. He received a Mgr. (BSc.) and Ing. (MSc.) degrees with honors from the Czech Technical University, Prague, in 1996 and 1998, respectively. In 2001, he obtained the Ph.D. in biomedical image processing from Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland, for his thesis on elastic image registration using parametric deformation models. Between October 2002 and February 2003, he held a post-doc research position in INRIA, Sophia-Antipolis, France. Since 2003 he is a Senior Research Fellow with Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague and passed his habilitation (Associate Professor) in 2010 and became a full professor in 2015. He was a Vice-Dean in 2011-2013 and a Department Head in 2013-2017. Jan Kybic has authored or co-authored 31 articles in peer-reviewed international scientific journals, one book, two book chapters, and over 80 conference publications. He has supervised nine PhD students, six of them have already successfuly graduated. He has also supervised over twenty master, bachelor and short-term student projects.
He is a member of IEEE and served as an Associate Editor for IEEE Transactions on Medical Imaging and as a reviewer for numerous international journals and conferences. He was a general chair of the ISBI 2016 conference.
His research interests include signal and image processing, medical imaging, image registration, splines and wavelets, inverse problems, elastography, computer vision, numerical methods, algorithm theory and control theory.
He teaches Digital Image Processing and Medical Imaging courses.
His talk takes place on Thursday, March 1, 2018.
Torsten Sattler received a PhD in Computer Science from RWTH Aachen University, Germany, in 2014 under the supervision of Prof. Bastian Leibe and Prof. Leif Kobbelt. In December 2013, he joined the Computer Vision and Geometry Group of Prof. Marc Pollefeys at ETH Zurich, Switzerland, where he currently is a senior researcher and Marc Pollefeys’ deputy while Prof. Pollefeys is on leave from ETH. His research interests include (large-scale) image-based localization using Structure-from-Motion point clouds, real-time localization and SLAM on mobile devices and for robotics, 3D mapping, Augmented abd Virtual Reality, machine learning, (multi-view) stereo, image retrieval and efficient spatial verification, camera calibration and pose estimation. His current work focuses on making algorithms for localization and mapping “smarter” by incorporating higher-level scene understanding.
Torsten has worked on dense sensing for self-driving cars as part of the V-Charge project. He is currently involved in enabling semantic SLAM and re-localization for gardening robots (as part of the Trimbot2020 project, a EU Horizon 2020 project where he leads the efforts on a workpackage), research for Google’s Tango project, where he leads CVG’s research efforts, and in work on self-driving cars.
Torsten has organized multiple tutorials and workshops at CVPR and ICCV. He regularly serves as a reviewer for the top-conferences in Computer Vision (CVPR, ECCV, ICCV) and Robotics (IROS, ICRA) and is an area chair for CVPR 2018 and 3DV 2018.
His talk takes place in May / June 2018.
Miloslav Druckmüller is a Professor of Applied Mathematics at the Institute of mathematics, Faculty of Mechanical Engineering, Brno University of Technology and the head of the Department of Computer Graphics and Geometry. His main interests are numerical methods of image analysis, digital image processing, computer graphics and complex variable analysis. During the last 10 years he has been cooperating widely with the Institute for Astronomy, University of Hawaii in the field of solar coronal plasma research. He created a large archive of K-corona (photospheric light scattered on free electrons) images and temperature maps based on Fe and Ni ions observing based on data obtained during total solar eclipses during last two decades. Nowadays his research is mainly focused on processing and analysis of data obtained by NASA SDO spacecraft. His talk takes place in POSTPONED.
Kevin Köser is a senior researcher at the GEOMAR Helmholtz Centre for Ocean Research, Kiel. His main research interest lies in novel camera-based measurement techniques for (deep) sea environments and processes (3D underwater vision). These help to study resources, to explore and monitor (deep) sea habitats or to assess hazards, e.g. with respect to gas flux or seafloor dynamics. In the past years Dr. Köser has taught the classes 3D Photography and Computer Vision Lab at the Swiss Federal Institute of Technology (ETH Zurich) and has worked as a senior researcher in ETH’s Computer Vision and Geometry Lab on shape and motion extraction from photos and videos, geolocalization and image registration. POSTPONED