Professor of Physics
University of Applied Sciences, Duesseldorf
Alex has over 20 years of experience with optical technologies. During his position as optical designer at Kostal (Tier 1) he was responsible for the optical quality of the camera ADAS, designing MTF test benches for all purposes. As a Professor for Physics at the University of Applied Sciences in Düsseldorf he is now looking at all the questions surrounding optical quality from a scientific point of view, and will share his enthusiasm for optics and cameras with you.
Modules: Optics for ADAS and AVs and Cameras for Automotive
Assistant Professor & Director of Robot Learning Lab
University of Freiburg
Abhinav Valada received his PhD in Computer Science specializing in robotics and machine learning. Before coming to Freiburg, he co-founded and worked as the Director of Operations of Platypus LLCfrom 2013 to 2015, a company developing autonomous robotic boats in Pittsburgh, USA.
His research now lies at the intersection of robotics, machine learning and computer vision and he will share his knowledge of deep learning algorithms with you.
Modules: Computer Vision Part 1; Deep Learning and AI and Computer Vision Part 2; Algorithms
Albert Theuwissen is author or coauthor of 200+ technical papers in the solid-state imaging field and issued several patents. He was co-editor of IEEE Micro special issue on Digital Imaging Nov./Dec. 1998 and of the IEEE Transactions on Electron Devices special issues on Solid-State Image Sensors, May 1991, October 1997 and January 2003. For the latest special issue IEEE-ED on image sensors, published in January 2016, he acted as the guest editor-in-chief. He was general chairman of the International Image Sensor Workshop in 1997, 2003, 2009 and 2015. He is member of the Steering Committee of the aforementioned workshop and founder of the Walter Kosonocky Award, which highlights the best paper in the field of solid-state image sensors. Together with his peers, Eric Fossum and Nobukazu Teranishi, he founded the International Image Sensor Society, a non-profit organization to stimulate sharing of technical knowledge in the field of digital image capturing.
Module: Image Sensors
Lidar and Optical Communications Institute (LOCI)
Paul F. McManamon received the Ph.D. degree in physics from The Ohio State University, Columbus, in 1977. He is an independent consultant and works part-time as the Technical Director of the Ladar and Optical Communications Institute, LOCI, at the University of Dayton, OH. He worked at Wright Patterson Air Force Base, OH, from 1968 to 2008, primarily in electrooptical sensors. He was Chief Scientist for the Avionics Directorate, Wright Lab, for more than two-and-a-half years. He was a Senior Scientist for infrared sensors for five years. He was Chief Scientist of the Sensors Directorate, Air Force Research Laboratory, from June 2005 to May 2008.,Dr. McManamon was on the SPIE Board of Directors for seven years and on the SPIE Executive Committee from 2003 through 2007. He was primary author of “Optical Phased Array Technology,” which received the IEEE W. R. J. Baker Award for the best paper in any IEEE refereed journal or Transactions. He is a Fellow of SPIE, OSA, the Air Force Research Laboratory, and the Military Sensing Symposia, MSS.
Module: LiDAR for Automotive
Uwe Artmann studied photo technology at the University of Applied Sciences in Cologne following an apprenticeship as a photographer and finished with the German ‘Diploma Engineer’. He is now the CTO at Image Engineering, an independent test lab for imaging devices and manufacturer of all kinds of test equipment for these devices. His special interest is the influence of noise reduction on image quality and MTF measurement in general.
Module: System Characterisation and Calibration
Department of Electrical and Computer Engineering Ben-Gurion University
Igal Bilik received B.Sc., M.Sc., and Ph.D. degrees in electrical and computer engineering from the Ben-Gurion University of the Negev. During 2006–2008, he was a postdoctoral research associate at the Duke University. During 2008-2011, he has been an Assistant Professor at the University of Massachusetts, Dartmouth. During 2011-2018, he was a Staff Researcher at GM RnD, leading automotive radar technology development. During 2018-2020 lead Smart Sensing and Vision Group at GM RnD. Currently Dr. Bilik is an Assistant Professor at the Ben Gurion University of the Negev. Dr. Bilik received the Best Student Paper Awards at IEEE RADAR 2005 and IEEE RADAR 2006 Conferences, Student Paper Award in the 2006 IEEE 24th Convention of Electrical and Electronics Engineers in Israel, and the GM Product Excellence Recognition in 2017.
Module: RADAR for Automotive
Prof. Wilfried Philips
IPI Research Group
Wilfried Philips is a senior full professor at Ghent University, where he leads the Image on Processing and Interpretation (IPI) research group and the research consortium iKnow, which has realized 9 spin off companies. At imec, he is scientific lead of the Center of Excellence on Image Processing and Sensor Fusion. He is co-founder of the IoT company Senso2Me. He is senior member of IEEE and fellow of the Belgian-American Educational Foundation.
Wilfried Philips’s and IPI’s research interests relate to image real-time computer vision and fusion of “rich” sensor data (radar/video/LiDaR/thermal/hyperspectral), with a strong focus on industrial applications.
Module: Sensor Fusion
Director Computational Vision and Imaging Technology
School of Computer Science &, Engineering University of Westminster
Dr Sophie Triantaphillidou is a Professor in Imaging Science at the University of Westminster, UK. She holds a BSc (Hons) in Photographic and Electronic Imaging Science (1995) and a PhD (2001) in the field of Digital Image Quality. She is the Director of the Computational Vision and Imaging Technology (CVIT) research group within the Department of Computer Science and Engineering.
Sophie’s research is interdisciplinary, exploring interrelationships between imaging system performance and image quality, image content, and image perception by human and machine vision systems.
Module: Optimising Image Quality