Hugo Jair Escalante
Hugo Jair Escalante is researcher scientist at Instituto Nacional de Astrofisica, Optica y Electronica, INAOE, Mexico. Previously, he was assistant professor at the Graduate Program on Systems Engineering at UANL. He holds a PhD in Computer Science, for which he received the best PhD thesis on Artificial Intelligence 2010 award (Mexican Society in Artificial Intelligence). He was granted the best paper award of the International Joint Conference on Neural Networks 2010 (IJCNN2010). He is secretary and member of the board of directors of ChaLearn, The Challenges in Machine Learning Organization, a non-profit organism dedicated to organizing challenges, since 2011. Also, he is member of the board of the CONACYT Network on Applied Computational Intelligence, regular member of AMEXCOMP and member of the National System of Researchers (SNI). Since 2017, he is editor of the Springer Series on Challenges in Machine Learning, a new book series focused on academic competitions within machine learning and related fields. He has been involved in the organization of several challenges in computer vision and machine learning, collocated with top venues in machine learning and computer vision, see http://chalearnlap.cvc.uab.es/. He has served as co-editor of special issues in IJCV, IEEE TPAMI, and IEEE Transactions on Affective Computing. He has served as area chair for NIPS 2016 and NIPS 2017, and has been member of the program committee of venues like CVPR, ICPR, ICCV, ECCV, ICML, NIPS, IJCNN. His research interests are on machine learning, evolutionary computing and its applications on language and vision.
University Paris-Saclay, France and ChaLearn USA
Isabelle Guyon ( http://guyon.chalearn.org/ ) is chaired professor in “big data” at the Université ParisSaclay, specialized in statistical data analysis, pattern recognition and machine learning. She is one of the cofounders of the ChaLearn Looking at People (LAP) challenge series and she pioneered applications of the MIcrosoft Kinect to gesture recognition. Her areas of expertise include computer vision and and bioinformatics. Prior to joining ParisSaclay she worked as an independent consultant and was a researcher at AT&T Bell Laboratories, where she pioneered applications of neural networks to pen computer interfaces (with collaborators including Yann LeCun and Yoshua Bengio) and coinvented with Bernhard Boser and Vladimir Vapnik Support Vector Machines (SVM), which became a textbook machine learning method. She worked on early applications of Convolutional Neural Networks (CNN) to handwriting recognition in the 1990’s. She is also the primary inventor of SVMRFE, a variable selection technique based on SVM. The SVMRFE paper has thousands of citations and is often used as a reference method against which new feature selection methods are benchmarked. She also authored a seminal paper on feature selection that received thousands of citations. She organized many challenges in Machine Learning since 2003 supported by the EU network Pascal2, NSF, and DARPA, with prizes sponsored by Microsoft, Google, Facebook, Amazon, Disney Research, and Texas Instrument. Isabelle Guyon holds a Ph.D. degree in Physical Sciences of the University Pierre and Marie Curie, Paris, France. She is president of Chalearn, a nonprofit dedicated to organizing challenges, vicepresident of the Unipen foundation, adjunct professor at NewYork University, action editor of the Journal of Machine Learning Research, editor of the Challenges in Machine Learning book series of Microtome, and program chair of the upcoming NIPS 2016 conference.
Multimedia Information Retrieval Lab Delft University of Technology, Netherlands
University of Applied Sciences Western Switzerland (HES-SO), Switzerland
University Politehnica of Bucharest, Romania
Coordinates the Multimedia Lab at University Politehnica of Bucharest (UPB), research center CAMPUS, and the Video Processing Group at LAPI-UPB. He holds a double PhD in image/video processing from UPB and University of Savoie, France. He is currently a tenured Professor with ETTI-UPB and courtesy faculty member of University of Savoie. His research interests cover multimedia information retrieval, social multimedia, image/video content processing and analysis and human-computer interaction. He has authored over 150 scientific publications. He serves/served as: reviewer for several journals (SPIE JEI, IS&T JIST, IEEE TPAMI, IEEE TIP, IEEE TM, IEEE TCSVT, IEEE SPL, IEEE TAC, IET CV, MTAP, ACM CS); lead editor for a Springer ACVPR book; lead guest editor for a special issue with Elsevier Image and Vision Computing and with Multimedia Tools and Applications; technical programme committee (EUSIPCO, CBMI, ACM MM & workshops, ECCV workshops, EUVIP, SIGIR workshops, IPTA, PCM, ACM ICMR, KSE, ICDM, ISM, IEEE ICME & workshops); conference committee chair for EUSIPCO (local co-chair), CBMI (publication co-chair), ACM Multimedia (proceedings co-chair), IEEE ICIP (local co-chair), general chair for CBMI 2016 and ACM ICMR 2017; organizer of workshops: "Information Fusion in Computer Vision for Concept Recognition" at ECCV 2012, "Event-based Media Integration and Processing" at ACM MM 2013, "Human-Centered Event Understanding from Multimedia" at ACM MM 2014 & 2015; as well as lead organizer/co-organizer for several benchmarking campaigns: MediaEval Retrieving Diverse Social Images, Affect Task: Violent Scenes Detection and Predicting Media Interestingness; lead organizer for ImageCLEF 2017-2018. He contributed to over 21 Romanian/EU funded research and strategic programmes, as principal investigator or as part of the research team. He is senior member of IEEE and member of SPIE, ACM, EURASIP and GDR-ISIS and technical program expert for the Horizon 2020 Programme.
UAM-C, Mexico City, Mexico
Obtained the MS and PhD degrees in Computer Science from the Instituto Nacional de Astrofisica, Optica y Electronica (INAOE), Mexico in 2010. He did a postdoctoral fellowship at the Instituto Mexicano del Petroleo (IMP) from 2010 to 2012. Since 2012 he is Titular Professor C at the Universidad Autonoma Metropolitana (UAM) campus Cuajimalpa. He is member of the Language and Reasoning Research Group from UAM, member of the Mexican Association for Natural Language Processing (AMPLN), the Hispano-American Network for Automatic Human Language Processing (RedHisTAL) and member of the Mexican Academy of Computer Science (AMEXCOMP). His research interests are related to Natural Language Processing and Knowledge Representation, with special emphasis in Automatic Text Summarization, Plagiarism Detection and Author Profiling. He has participated in the organization of the SOurce COde Plagiarism Detection series SOCO and SOCO-CL during 2014 and 2015 respectively, a competition held jointly with the FIRE conference.
Gabriela Ramirez de la Rosa
UAM-C, Mexico City, Mexico
is a Computer Engineer from the Universidad Tecnológica de la Mixteca (UTM), Mexico in 2008. Then, in 2010 she obtained a master's degree in Computer Science from the Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE) Mexico. During 2011 and 2013 she worked at the University of Alabama at Birmingham, USA. Currently, Gabriela is an invited professor at the Universidad Autónoma Metropolitana Unidad Cuajimalpa (UAM-C), Mexico. She is a member of the Language and Reasoning Research Group at UAM-C since 2013, she is also member of the Mexican Society of Artificial Intelligence SMIA, the Mexican Association for Natural Language Processing (AMPLN), and the Language Technologies Thematic Network RedTTL. Her topics of interest among the Natural Language Processing field are knowledge representation for author profiling, automatic approaches for close duplicates identification in source code, and generally speaking supervised methods for text classification. Presently she is working in her doctoral thesis in finding a new multi-modal representation for personality identification.
Computer Vision Center (UAB) and University of Barcelona, 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 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 Editor-in-Chief of American Journal of Intelligent Systems and editorial board member of more than 5 international journals. 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 co-founder of PhysicalTech and Care Respite companies. He is also member of 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 area chair at WACV16, NIPS16, AVSS17, FG17, ICCV17, WACV18, FG18, BMVC18, NIPS18, FG19 and competition and demo chair at FG17, NIPS17, NIPS18, ECMLPKDD19 and FG19. His research interests include, statistical pattern recognition, affective computing, and human pose recovery and behavior understanding, including multi-modal data analysis, with special interest in characterizing people: personality and psychological profile computing.