The team of organizers for ICDAR2019-ORF competition involves experienced researchers that have been involved in organizing scientific events (competitions, tutorials, workshops etc.) for major conferences like ICDAR and ICPR in recent past. We have senior professors and scientists in our team for having their expert opinion and feedback to ensure a high scientific level of the work, as well as young researchers with energy and state-of-the-art knowledge for ensuring smooth organization of the competition.
A brief CV of each co-organizer of ICDAR2019-ORF competition is provided in alphabetic order of names.
 | CAPOBIANCO Samuele received the Master Degree in Computer Engineering at University of Florence in 2016 and is a third year PhD student in Smart Computing of the Universities of Florence, Pisa and Siena. His Master thesis was co-supervised by Professor Simone Marinai and Professor Marcus Liwicki; and was titled “Document Analysis using Convolutional Neural Networks”. His research fields include Artificial Intelligence, Pattern Recognition, Signal Processing and Document Image Analysis. He has authored 2 articles in international journals as Future Internet, Pattern Recognition Letters and 6 articles in various national/international conferences including ICPR and ICDAR. His recent research interests are based around Deep Learning with a special focus on applications in Handwritten Document Analysis and Symbol Detection. |
| DUTTA Anjan (Ph.D.) is a Marie-Curie COFUND postdoctoral fellow under the P-SPHERE project at the Computer Vision Center in Barcelona. He received PhD in Computer Science from the Autonomous University of Barcelona (UAB) in the year of 2014. His doctoral thesis was awarded as Cum Laude qualification (highest grade) with International mention. Moreover, he received the Extraordinary PhD Thesis Award for the year 2013-14 by the UAB for outstanding dissertation. After completing his PhD, he worked as a postdoctoral researcher at a few academic institutes including Télécom ParisTech, Paris; Indian Statistical Institute, Kolkata. Until now, he has communicated 9 articles in ISI-JCR international journals including PR, PRL, MTA, IJDAR, IJPRAI and 23 articles in various international conferences including ACCV, ICDAR, ICPR, ICFHR, DAS etc. He is a regular reviewer for the journals named IJCV, IEEE TNNLS, IEEE TCYB, PR, PRL etc, he served as a program committee member of different scientific conferences such as BMVC, ICPR, ICFHR etc. His recent research interests have revolved around graph-based representation and algorithms, graph neural network and multimodal deep learning. Webpage: https://sites.google.com/site/2adutta |  |
 | LLADOS Josep (Professor) received the degree in Computer Sciences in 1991 from the Universitat Politècnica de Catalunya and the PhD degree in Computer Science in 1997 from the Universitat Autònoma de Barcelona (Spain) and the Université Paris 8 (France). Currently he is an Associate Professor at the Computer Sciences Department of the Universitat Autònoma de Barcelona and a staff researcher of the Computer Vision Center, where he is also the director since January 2009. He is visiting researcher of the IDAKS Lab of the Osaka Prefecture University (Japan). He is chair holder of Knowledge Transfer of the UAB Research Park and Santander Bank. He is the head of the Pattern Recognition and Document Analysis Group (2014SGR-1436). His current research fields are document analysis, structural and syntactic pattern recognition and computer vision. He has been the head of a number of Computer Vision R+D projects and published more than 200 papers in national and international conferences and journals. J. Lladós is an active member of the Image Analysis and Pattern Recognition Spanish Association (AERFAI), a member society of the IAPR. He is currently the chairman of the IAPR Educational Committee. Formerly he served as chairman of the IAPR Industrial Liaison Committee, and the IAPR TC-10, the Technical Committee on Graphics Recognition. He is chief editor of the ELCVIA (Electronic Letters on Computer Vision and Image Analysis) and he serves on the Editorial Board of the IJDAR (International Journal in Document Analysis and Recognition), the Cultural Heritage Digitization (specialty section of Frontiers in Digital Humanities), and also a PC member of a number of international conferences. He was the recipient of the IAPR-ICDAR Young Investigator Award in 2007. He was the general chair of the International Conference on Document Analysis and Recognition (ICDAR’2009) held in Barcelona in July 2009, and co-chair of the IAPR TC-10 Graphics Recognition Workshop of 2003 (Barcelona), 2005 (Hong Kong), 2007 (Curitiba) and 2009 (La Rochelle). Josep Lladós has also experience in technological transfer and in 2002 he created the company ICAR Vision Systems, a spin-off of the CVC/UAB. Webpage: http://www.cvc.uab.es/?page_id=62 |
| LUQMAN Muhammad Muzzamil (Ph.D.) is a research scientist in Document Image Analysis, Pattern Recognition and Computer Vision. Luqman is currently working on the post of Research Engineer (Permanent) at the L3i Laboratory, University of La Rochelle (France) since November 2015. Luqman has worked as a Research Engineer at the Bordeaux Bioinformatics Center (Centre de Bioinformatique de Bordeaux), France and has worked as a Postdoctoral researcher with Professor Jean-Marc Ogier, at L3i Laboratory, University of La Rochelle (France). Luqman has a PhD in Computer Science from François Rabelais University of Tours (France) and Autonoma University of Barcelona (Spain). His PhD thesis was co-supervised by Professor Jean-Yves Ramel and Professor Josep Llados; and was titled “Fuzzy Multilevel Graph Embedding for Recognition, Indexing and Retrieval of Graphic Document Images”. Luqman participated in GEPR contest of ICPR 2010 and his method was ranked 3rd. His research interests include Structural Pattern Recognition, Document Image Analysis, Camera-Based Document Analysis and Recognition, Graphics Recognition, Machine Learning, Computer Vision, Augmented Reality and Biomimicry. Luqman has authored more than 25 scientific publications including a book, a journal paper and international conference papers. Luqman is a regular reviewer for journals (PR, PRL, IJDAR, IJPRAI, IJCSAI, TALLIP), he regularly serves on the program committees of many international scientific events (ICDAR, ICPR, DAS, CIFED, ICET, GREC, CBDAR, IWRR) and has actively participated in organizing several international conferences and workshops (CLA 2013, DAS 2014, IDAKS 2016, ICDAR 2015, ICPR 2016, CBDAR 2017). Luqman actively participated recently for organizing the SmartDoc competition for ICDAR 2015, SSGCI competition for ICPR 2016 and Multilingual Text detection/recognition (RRC-MLT) for ICDAR 2017. Luqman was co-presenter of the GMPRDIA (Graph-based Methods in Pattern Recognition and Document Image Analysis) tutorial for ICDAR 2017 and was co-organizer of the workshop CBDAR 2017. Webpage: http://pageperso.univ-lr.fr/muhammad_muzzamil.luqman |  |
 | MARINAI Simone (Professor) received the Master Degree in Electronic Engineering in 1992 and the PhD Degree in Computer Engineering in 1996 both from the University of Florence, Italy. In 1996 he has been visiting researcher at CENPARMI, Concordia University, Montréal. Currently he is Associate Professor of Computer Engineering at the Information Engineering department of the University of Florence. He is also visiting researcher of Osaka Prefecture University (Japan) in the Institute of Document Analysis and Knowledge Science. His main research interests are in Artificial Intelligence and Pattern Recognition with a special focus on applications in Document Engineering and Document Image Analysis. Prof. Marinai is Past-President of the International Association for Pattern Recognition (IAPR), editor in chief of the International Journal on Document Analysis and Recognition (IJDAR) and of the Electronic Letters on Computer Vision and Image Analysis (ELCVIA) journal; has been President of IAPR (2016-18); 2nd vice-president of IAPR (2014-16) and Chair of the Conferences and Meetings (C&M) committee of IAPR (2008-2014); Past chair of the IAPR Technical Committee on Neural Networks and Computational Intelligence (TC3) (2004-2008); He is co-editor of the book “Machine Learning in Document Analysis and Recognition” published by Springer Verlag in 2008. He is author of more than 60 peer-reviewed publications and editor of four volumes. Webpage: https://www.unifi.it/p-doc2-2013-200006-M-3f2a3d2f3b3030-0.html |
| RAMOS Oriol (Ph.D.) is an associated professor of the Computer Science (CS) Department and researcher of the Document Analysis and Pattern Recognition Group (DAG) since september 2010. Before, I’ve been in other research groups like the Pattern Recognition and Human Language Technology (PRHLT) group in the Instituto Tecnológico de Informática and the CVPR Unit from ISI, Kolkata. I get my BSc degree in Mathematics in 2001 and the PhD in Computer Science, in 2006, by the Universitat Autònoma of Barcelona, Spain, and the Université Nancy 2, France, in 2006. My research interests are probabilistic graphical models (PGMs), in particular learning and inference algorithms and how we can applied them to different document analysis tasks such as layout analysis, community detection, document forensics and symbol retrieval, among others. I’m also interested in parallel computing paradings, specially on GPUs programing. See my publication’s list and the research and transfer project list in which I’m also involved into. Webpage: http://www.cvc.uab.es/~oriolrt/ |  |
 | ZIRAN Zahra is a third year Ph.D student in the information engineering department(DINFO) at the university of Florence,Italy. Her doctoral research investigates the use of deep learning techniques for the recognition of document images. She has recently published a paper on “Object detection in floor plan images”. Her current research is deep learning on graphs with graph convolutional networks. Her primary field of research interest is Artificial Intelligence (AI). Within AI, she is interested in problems related to Document Analysis , machine learning, data mining and graph neural network. |