Computer Vision Center (UAB) and University of Barcelona, Spain
Sergio Escalera obtained the P.h.D. degree on Multi-class visual categorization systems at Computer Vision Center, UAB. He obtained the 2008 best Thesis award on Computer Science at Universitat Autònoma de Barcelona. He is ICREA Academia. He leads the Human Pose Recovery and Behavior Analysis Group. He is Full Professor at the Department of Mathematics and Informatics, Universitat de Barcelona. He is an adjunct professor at Universitat Oberta de Catalunya and Dalhousie University, and Distinguished Professor at Aalborg University. He has been visiting professor at TU Delft and Aalborg Universities. He is a member of the Visual and Computational Learning consolidated research group of Catalonia. He is also a member of the Computer Vision Center at UAB, Mathematics Institut of the Universitat de Barcelona, and the Barcelona Graduate School of Mathematics. He is series editor of The Springer Series on Challenges in Machine Learning. He is vice-president of ChaLearn Challenges in Machine Learning, leading ChaLearn Looking at People events. He is co-creator of Codalab open source platform for challenges organization and co-founder of the NeurIPS competition track. He is also Fellow of the ELLIS European Laboratory for Learning and Intelligent Systems working within the Human-centric Machine Learning program, member of the AAAC Association for the Advancement of Affective Computing, AERFAI Spanish Association on Pattern Recognition, ACIA Catalan Association of Artificial Intelligence, AEPIA Artificial Intelligence Spanish Association, INNS International Neural Network Society, IEEE, and Chair of IAPR TC-12: Multimedia and visual information systems. He has different patents and registered models. He participated in several international funded projects and received an Amazon Research Award. He has published more than 300 research papers and participated in the organization of scientific events. He received a CVPR best paper award nominee and a CVPR outstanding reviewer award. He has been guest editor at TPAMI, JMLR, PR, TAC and IJCV, among others. He has been General co-Chair of FG20, Area Chair at CVPR, NeurIPS, FG, ICCV, and BMVC, and Competition and Demo Chair at FG, NeurIPS, and ECMLPKDD, among others. His research interests include automatic analysis of humans from visual and multi-modal data, with special interest in inclusive, transparent, and fair affective computing and people characterization.
Universitat Oberta de Catalunya, Barcelona, Catalonia
Xavier Baró received his B.S. degree in Computer Science at the Universitat Autònoma de Barcelona (UAB) in 2003. In 2005 he obtained his M.S. degree in Computer Science at UAB, and in 2009 the Ph.D degree in Computer Engineering. At the present he is a lecturer and researcher at the IT, Multimedia and Telecommunications department at Universitat Oberta de Catalunya (UOC). He is involved on the teaching activities of the Computer Science, Telecommunication and Multimedia degrees of the UOC, and collaborates as assistant professor on the teaching activities of the Computer Science degree at the Applied Mathematics and Analysis of the Universitat de Barcelona (UB). In addition, he is involved on the Interuniversity master on Artificial Intelligence (UPCUBURV). He is cofounder of the Scene Understanding and Artificial Intelligence (SUNAI) group of the UOC, and collaborates with the Computer Vision Center of the UAB, as member of the Human Pose Recovery and Behavior Analysis (HUPBA) group. His research interests are related to machine learning, evolutionary computation, and statistical pattern recognition, specially their applications to generic object recognition over huge cardinality image databases.
Computer Vision Center and Universitat Autònoma de Barcelona, Barcelona, Spain
Dr. Jordi Gonzàlez received the Ph.D. degree in Computer Engineering in 2004 from Universitat Autònoma de Barcelona (UAB), Catalonia. He was a postdoctoral fellow at the Institut de Robòtica i Informàtica Industrial (IRI), a Joint Research Center of the Technical University of Catalonia (UPC) and the Spanish Council for Scientific Research (CSIC). At present, he is Associate Professor in Computer Science at the Computer Science Department, UAB. He is also a research fellow at the Computer Vision Center, where he has co-founded 2 spin-offs and the Image Sequence Evaluation (ISE Lab) research group in 2004. His research interests lie on pattern recognition and machine learning techniques for the computational interpretation of human behaviours in image sequences, or Video Hermeneutics. He has co-organized the THEMIS (BMVC2008 and ICCV2009), ARTEMIS (ACM MM2010, ECCV2012 and ACM MM2013) and ChaLearn LAP (ICMI2013, ECCV2014 and CVPR2015) workshops related to the video-based analys is of human motion in surveillance, films and social media footage. He has served as Area Chair (ICPR2012 and ICIAP2015); Publicity Chair at AVSS2012; Workshop Chair (ICCV2011 and AVSS2015); Local Arrangement Chair at ICCV2011; and Tutorial Chair at ibPRIA2011. He has co-organized Special Issues in IJPRAI (2009), CVIU (2012), MVA (2013) and TPAMI (2015) journals. He is member of the Editorial Board of CVIU and IET-CVI journals. He is also member of IEEE, Spanish Association on Pattern Recognition (AERFAI) and Catalan Association for Artificial Intelligence (ACIA).
Microsoft Research Cambridge, United Kingdom
Jamie Shotton leads the Machine Intelligence & Perception group at Microsoft Research Cambridge. He studied Computer Science at the University of Cambridge, where he remained for his PhD in computer vision and machine learning for visual object recognition. He joined Microsoft Research in 2008 where he is now a Principal Researcher. His research focuses at the intersection of computer vision, AI, machine learning, and graphics, with particular emphasis on systems that allow people to interact naturally with computers. He has received multiple Best Paper and Best Demo awards at top academic conferences. His work on machine learning for body part recognition for Kinect was awarded the Royal Academy of Engineering’s gold medal MacRobert Award 2011, and he shares Microsoft’s Outstanding Technical Achievement Award for 2012 with the Kinect engineering team. In 2014 he received the PAMI Young Researcher Award, and in 2015 the MIT Technology Review Innovator Under 35 Award (“TR35”).