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 at UB, CVC, and the Barcelona Graduate School of Mathematics. He is an associate professor at the Department of Mathematics and Informatics, Universitat de Barcelona. He is an adjunct professor at Universitat Oberta de Catalunya, Aalborg University, and Dalhousie 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. 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. He is also member of ELLIS, the AERFAI Spanish Association on Pattern Recognition, ACIA Catalan Association of Artificial Intelligence, INNS, and Chair of IAPR TC-12: Multimedia and visual information systems. He has different patents and registered models. He has published more than 250 research papers and participated in the organization of scientific events, including CCIA04, ICCV11, CCIA14, AMDO16, FG17, NIPS17, NIPS18, FG19, and workshops at ICCV, ICMI, ECCV, CVPR, ICPR, NIPS. He has been guest editor at JMLR, TPAMI, IJCV, TAC, PR, MVA, JIVP, Expert Systems, and Neural Comp. and App. He has been General co-Chair of FG20, Area Chair at WACV16, NIPS16, AVSS17, FG17, ICCV17, WACV18, FG18, BMVC18, NIPS18, FG19, BMVC19, ICIAP21 and Competition and Demo Chair at FG17, NIPS17, NIPS18, ECMLPKDD19 and FG19. 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: personality and psychological profile computing.
Hacer Yalim Keles
Ankara University, Turkey
Assoc. Prof. Dr. Hacer Yalim Keles received her B.S., M.S. and Ph.D. degrees in Computer Engineering from Middle East Technical University, Turkey, in 2002, 2005 and 2010, respectively. Her Ph.D. Thesis received the Thesis of the Year award by Middle East Technical University in 2010. From 2000 to 2007 she worked as a researcher and senior researcher at The Scientific and Technological Research Council of Turkey (TUBITAK). In 2010, she received an R&D grant from the Ministry of Industry and Trade of Turkey and established her R&D company. Her follow-up project SOYA was funded by TUBITAK in 2011 and later awarded by TUBITAK as one of the best venture projects and sent to Silicon Valley for investment negotiations. She is the first woman who took this grant in Turkey. She is currently working as an Assoc. Professor in the Department of Computer Engineering at Ankara University. She is the creator and the director of the CVML lab in her department (https://cvml.ankara.edu.tr). Her research interests lie predominantly in the areas of computer vision and machine learning, particularly in deep learning. Recently, she has been working in sign language recognition problems; her research project on the generation of a large-scale Turkish Sign Language dataset, which is funded by TUBITAK, has recently been completed with a novel dataset, i.e. AUTSL. The AUTSL dataset that is used in the competition part of this workshop is generated by the team in her CVML lab.
Julio C. S. Jacques Junior
Universitat Oberta de Catalunya (UOC) and Computer Vision Center (CVC/UAB), Spain
Julio C. S. Jacques Junior received his Ph.D. degree in Computer Science from PUCRS in 2012, Brazil. Currently, he is a postdoctoral researcher at the Computer Science, Multimedia and Telecommunications department at Universitat Oberta de Catalunya (UOC). He collaborates within the Computer Vision Center (CVC) and Human Pose Recovery and Behavior Analysis (HUPBA) group at Universitat Autònoma de Barcelona (UAB) and University of Barcelona (UB), as well as within ChaLearn (LAP) Looking at People. He also have collaborated with the organization of some workshops and challenges organized by ChaLearn LAP (ECCV’16, ICPR’16, CVPR/IJCNN’17, NeurIPS'19). His research interests include, between others, computer vision-based applications with a particular focus on visual human behaviour analysis.
Ozge Mercanoglu Sincan
Ankara University, Turkey
Özge Mercanoglu Sincan is a Ph.D. candidate and working as a Research Assistant at the Department of Computer Engineering, Ankara University. She is a member of the Computer Vision and Machine Learning (CVML) Lab in her department. She has been working in a research project related to deep learning, in collaboration with the industry. Her research interests lie in the areas of computer vision and deep learning, particularly in the sign language recognition problems. With respect to the Challenge proposal, she has strong experience with large scale dataset formatting and baseline methods for sign language recognition.