SmartTech-IC is an international conference conceived to attract researchers, scientists and technologists from some of the top companies, universities, research groups, and government agencies from Latin America and around the world to communicate their research results, inventions and innovative applications in the area of Smart Science and the most recent technological trends. The SmartTech-IC conference aims to provide an academic platform to promote the creation of technical and scientific collaboration networks. The first SmartTech-IC 2019 conference will be held at Universidad Politecnica Salesiana located in Quito-Ecuador.
We encourage the submission of original, unpublished technical papers on one or more of the listed topics and sub-topics, as are shown below. Potential authors should not feel limited by the listed topics as it is not exhaustive. Topics include, but are not limited, to the following research areas: Smart Technologies, Systems and their Applications. Unlisted but related sub-topics are also acceptable.
> Artificial Intelligence and Machine Learning
> Cloud Computing
> Computational Mathematics
> Data Management, Exploration and Mining
> Deep learnt networks and Evolutionary Systems
> High Performance Computing
> Identity Management and Object Recognition
> Mobile Computing
> Modeling Systems and Software Engineering
> Natural Language Processing
> Pattern Recognition and Analysis
> Reconfigurable Computing Robotics and Human Machine Interface
> Web-based Learning
> Cognitive Radio and Cognitive Networks
> Communication Architecture
> Smart Computing and Personal Area Networks
> Internet of Things (IoT)
> Information, Internet Security and Privacy Localization
> FPGA Development
> Sensor/Embedded Networks and Pervasive
> Social Network Behaviors
> Smart Grid Systems, Intelligent Control and Robotics
> Smart Communication System Models
> Smart Portable Devices
> System Automation
> Power Electronics and Control Scheme
> Vehicular Networking
> Wearables, Body Sensor Networks
> Agricultural Informatics and Communication
> Community Information Systems
> Computer-Aid Diagnosis Systems
> E-governance, E-Commerce and E-Business
> E-Learning and Informatics
> Medical Information Retrieval
> Smart Healthcare Systems
> Smart grid and Renewable Energy
> Storage, Transmission and Access to Medical Information
> Remote Sensing
Dr. Alfredo I. Hernández is a Research Director at the French National Institutes of Health and Medical Research (INSERM), in the commission “Technologies for Health, Therapeutics and Biotechnologies” and is assigned since 2001 to the Laboratory of Signal and Image Processing (LTSI), INSERM Unit 1099, located at the University of Rennes 1, in Rennes France. He has a background on Systems Engineering with an M.S. degree on biomedical electronics obtained in Venezuela. He received his Ph.D. degree in signal processing and telecommunications in 2000 and the Habilitation for Directing Research (HDR) in 2009, both from the University of Rennes 1, France, in the field of biomedical signal processing and physiological modelling. Dr. Hernández is the head of the INSERM research team “SEPIA” and co-leader of the MedTech axis of the Hospital-University Federation “TechSan”, devoted to technologies for health. His research is based on original methods combining multisource, high-dimensional data processing, mathematical modeling, analysis and parameter identification, mainly applied to the development of medical devices targeting the cardiorespiratory system. Dr. Hernández has developed a strong translational research activity, with longstanding partnerships with University Hospitals and the MedTech industry. He has participated as principal investigator or work-package leader in a number of regional, French, European or international projects. He has authored/co-authored more than 180 peer-reviewed publications and he is inventor of more than 50 patents, most of which have been transferred to or co-registered with MedTech companies.
Antoine Manzanera is a Professor of Computer Science at ENSTA ParisTech and Researcher in Computer Vision within the Autononous Systems and Robotics Laboratory. He graduated from Université Claude Bernard in Lyon (BSc Mathematics, 1991 and MSc Theoretical Computer Science, 1993), Télécom ParisTech (PhD Signal and Image Processing, 2000) and Université Pierre et Marie Curie (Habilitation Degree, 2012). For 18 years now he has taught Image Processing, Discrete Geometry, Mathematical Morphology, Computer Vision and Machine Learning in ENSTA, Université Paris Sorbonne, Université Paris Saclay, and in different Universities around the world. His Research interests extend across the broad range of mathematical, physical and technological foundations of Computer Vision, with a particular focus on Video Analysis, Image Representations, Scene Reconstruction, and Autonomous Visual Learning.
Juan Caicedo is a postdoctoral researcher at the Broad Institute of MIT and Harvard, where he investigates the use of deep learning to analyze microscopy images. Previous to this, he studied object detection problems in large scale image collections also using deep learning, at the University of Illinois in Urbana-Champaign. Juan obtained a PhD from the National University of Colombia and completed research internships in Google Research, Microsoft Research, and Queen Mary University of London as a grad student, working in problems related to large scale image classification, image enhancement, and medical image analysis. His research interest include computer vision, machine learning and computational biology.
Cèsar Ferri Ramírez is an associate professor in the Department of Computer Systems and Computation at the Universitat Politènica de València. Furthermore, he holds a longstanding research position in the DMIP team (a subgroup of ELP), which commenced in 1999. His research interest orients around Machine Learning and Artificial Intelligence. Cèsar has published papers in leading journals and at top conferences as a coauthor on the aforementioned topics. Cèsar Ferri Ramírez obtained an MSc in Computer Science in 1998 at the Facultad de Informática at the Universitat Politècnica de València. His PhD was awarded by the Universitat Politècnica de València (UPV) in 2003, and focused on the topic of applying declarative languages for machine learning. Cèsar Ferri Ramírez is the Assistant Dean for University-Enterprise Relations of the School of Computer Science ETSINF, a position that he has held since 2009.
Gloria Díaz got her undergraduate degree in System Engineering and Computation in 2000, and her Doctorate in Engineering in 2011 from Universidad Nacional of Colombia. She was with the Telemedicine Center of the National University of Colombia between 2005 and 2011, participating in Research and Development projects related to the provision of telemedicine services and the automatic analysis of medical images to support teaching and decision making. Actually, she is an associate professor in the Department of information systems at the Instituto Tecnológico Metropolitano (Medellín-Colombia), and researcher in the Pattern Recognition and Intelligent Machines Laboratory. Her research field is Medical Image Analysis and pattern recognition focused particularly on cancer diagnosis aiding.
Technical papers describing original, previously unpublished papers are solicited in all topics and sub-topics described above. Authors are invited to submit papers through easychair platform.
Submissions for are both accepted. Both kinds of submissions will have the same reviewing process and the accepted papers will be included in the same proceedings.