The evolution of semiconductor process technologies has enabled the design of low cost, compact and high-performance wearable embedded systems. These new wearable systems are computing platforms with multi-processor system-on-chip (MPSoC) architectures that can be deployed ubiquitously, and can potentially provide computing capacity for real-time analysis of human bio-signals to continue the progress at our society. However, the inherent resource-constrained nature of wearable embedded systems, coupled with their increasing power requirements and heat density, can result in degraded performance or a global energy crisis if they are massively deployed in the new era of Internet-of-Things (IoT). However, IoT provides an ideal framework to develop detection and classification of human emotions from multiple bio-signals, which can then be used in wide variety of applications. In this talk I will address how our current electronic design methodologies have to be changed to conceive the next generation energy-efficient smart wearable systems in the IoT era. This talk advocates for a new system-level approach to synergistically design both hardware and software components, as well as capitalizing on a better understanding how living organisms operate. This new approach embeds more onboard intelligence and gracefully scales the energy consumption of next-generation smart wearable systems according to different operating requirements.

David Atienza Alonso is associate professor of electrical engineering and director of the Embedded Systems Laboratory (ESL) at the Institute of Electrical Engineering within the School of Engineering (STI) of EPFL, Switzerland. Previously he was associate professor at the Computer Architecture and Automation Department of Complutense University of Madrid (UCM), Spain. He received his M.Sc. and Ph.D. degrees in Computer Science from Complutense University, Madrid, Spain, and Inter-University Micro-Electronics Center (IMEC), Leuven, Belgium, in 2001 and 2005, respectively.

His research interests focus on system-level design methodologies for high-performance multi-processor systems-on-chip (MPSoC) and low-power embedded systems, including new thermal-aware design for 2D and 3D MPSoCs, design methods and architectures for wireless body sensor networks, dynamic memory management and interconnection hierarchy optimizations. In these fields, he is co-author of more than 200 publications in prestigious journals and international conferences, several book chapters and five U.S. patents. He is the recipient of the IEEE CEDA Early Career Award in 2013, the ACM SIGDA Outstanding New Faculty Award (ONFA) in 2012 and an External Research Faculty Award of Oracle in 2011 in the area of stable global thermal-aware control for enterprise computer servers. He has served as a Distinguished Lecturer (2014-2015) of the IEEE CASS. He is Senior Member of ACM, and IEEE Fellow.

He has also earned two best paper awards at the VLSI-SoC 2009 and CST-HPCS 2012 conference, and five best paper award nominations at the DAC 2013, DATE 2013, WEHA-HPCS 2010, ICCAD 2006 and DAC 2004 conferences. He serves or has served as associate editor of IEEE Transactions on Computers (TC), IEEE Design & Test of Computers (D&T), IEEE Trans. on CAD (T-CAD), and Elsevier Integration. He was the Technical Programme Chair of DATE 2015, General Chair of the GLSVLSI 2011 and the VLSI-SoC 2010 conference, and member of the technical program and organization committee of the most important conferences in EDA and embedded systems design. He is an elected member of the Executive Committee of the IEEE Council of Electronic Design Automation (CEDA) since 2008.

Geminoid that is an tele-operated android of an existing person can transmit the presence of the operator to the distant place. The operator recognizes the android body as his/her own body after talking with someone through the geminoid and has virtual feeling to be touched when someone touches to the geminoid. However, the geminoid is not the ideal medium for everybody. For example, elderly people hesitate to talk with adult humans and adult androids. A question is what is the ideal medium for everybody. In order to investigate the ideal medium, we are proposing the minimum design of interactive humanoids. It is called Telenoid. The geminoid is the perfect copy of an existing person and it is the maximum design of interactive humanoids. On the other hand, the minimum design looks like a human but we cannot know the age and gender. Elderly people like to talk with the telenoid. In this talk, we discuss the design principles and the effect to the conversation.

Hiroshi Ishiguro received his PhD in 1991 from the Graduate School of Engineering, Osaka University. He then worked in universities in Kyoto, California and Wakayama. He has also worked at the Department of Systems Innovation in the Graduate School of Engineering Science at Osaka University since 2003, as well as managing a group of laboratories named after him at the Advanced Telecommunications Research Institute International (ATR).

Hiroshi started creating his “family” of robots by making an android replica of his 4-year old daughter, while in 2006, he unveiled a robotic double of himself, which he developed to replace him in the classroom. The android was called “Geminoid HI-1” (from the Latin word Gemini meaning “twins”). The android doesn’t just share the professor’s appearance, but also replicates his movements and mannerisms; it breathes, blinks, frowns and responds to touch. Hiroshi created the female “Geminoid F” in 2009. The female android was designed to be a secretary, while her career took off when she got a small roll in a production called “Sayonara” at a Tokyo theatre, the robot then worked as a live manikin at a Tokyo shopping mall.

The professor has also developed humanoid robots that look a bit like unpainted porcelain dolls, as well as their human-looking counterparts. Hiroshi believes that these faceless robots will help create more of a connection with people at the other end of the phone or over the internet. In his opinion, people can superimpose the image of a specific person onto the faceless robot. “Telenoid”, which was the size of a child, was launched in 2010, while “Elfoid”, which can fit in the palm of your hand, was release in 2011. The android family was then extended in 2012 with the introduction of “Hugvie”, which is a cross between a human and a pillow, and contained a mobile phone pocket. During a phone conversation, people must cuddle Hugvie, pressing their head to the robot’s, which moves depending on how fast the person talks.

Hiroshi Ishiguro believes that people shouldn’t waste time on things that can be done by robots. Robots can replace teachers, tend to a garden and work in the entertainment business. In his lecture, Hiroshi told guests how robot technology will develop in the future and how quickly robots will get to grips with things traditionally associated with living creatures, such as emotions and interactions.

En los últimos años ha habido una auténtica explosión de métodos meta-heurísticos de optimización, muchos de ellos basados en simulación de procesos naturales o con inspiración de base biológica. Aunque hay críticas sobre la novedad de algunas de estas nuevas aproximaciones, lo cierto es que muchas de ellas constituyen nuevos paradigmas de búsqueda y optimización que están revolucionando esta área de investigación, y que inciden directamente en otras, a través de aplicaciones específicas. En esta charla se describe una de las últimas propuestas, el Coral Reefs Optimization algorithm (CRO), meta-heurística basada en la simulación de los diferentes procesos biológicos que ocurren en un arrecife de coral. Se describirán las particularidades de la meta-heurística, y como ha dado lugar a diferentes variaciones, que incluyen potentes algoritmos de co-evolución en una única población. La charla incluirá la descripción de la aplicación del CRO a diferentes problemas reales, así como las últimas líneas de desarrollo de la meta-heurística.

El Dr. Sancho Salcedo Sanz es Profesor Titular de Universidad del Departamento de Teoría de la Señal y Comunicaciones de la Universidad de Alcalá. Es Licenciado en CC. Físicas por la Universidad Complutense de Madrid (1998) y Doctor en Ingeniería de Telecomunicación por la Universidad Carlos III de Madrid (2002). Tras el doctorado, ocupó diversas plazas de Profesor Ayudante (Univesidad Carlos III de Madrid), Research Fellow (School of Computer Science, University of Birmingham), Profesor Titular de Universidad Interino (Universidad de Alcalá) y Profesor Titular de Universidad (Universidad de Alcalá), plaza que ocupa desde 2006. El Dr. Salcedo es autor de más de 130 artículos en revistas internacionales con índice de impacto y ha recibido diversos premios de investigación, como el Premio de Jóvenes Investigadores de la Universidad de Alcalá (Ciencias Experimentales, 2009), Premio 3M a la Innovación (categoría de Medio Ambiente, 2010) y Premio del Consejo Social de la Universidad de Alcalá a la Transferencia de Tecnología Universidad-Empresa, 2011, con el trabajo “Mejora de la eficiencia y gestión de parques eólicos y fotovoltáicos mediante técnicas de Soft-Computing”. Desde el año 2006 el Dr. Salcedo es el director del grupo de Investigación GHEODE de la Universidad de Alcalá.

This talk introduces the topic of multimodal interaction and discusses some of the most important work in the area, with a focus on haptics, audio and smell based interaction. Each modality is presented in terms of perception, technology and applications. In particular, the talk covers the area of non-speech audio, with discussion of Earcons, Auditory Icons, sonification and other forms of sound. For haptics, force-feedback, vibrotactile, thermal feedback are described along with pressure and force input. For smell, the longer version of the talk goes into more details about the different modalities with more examples of each.

Stephen Brewster is a Professor of Human-Computer Interaction in the School of Computing Science at the University of Glasgow. He got his PhD in auditory interfaces at the University of York. After a period spent working in Finland and Norway, he has worked in Glasgow since 1995. He leads the Multimodal Interaction Group, which is very active and has a very strong international reputation. His research focuses on multimodal HCI, or using multiple sensory modalities and control mechanisms (particularly audio, haptics and gesture) to create a rich, natural interaction between human and computer. His work has a strong experimental focus, applying perceptual research to practical situations. A long term focus has been on mobile interaction and how we can design better user interfaces for users who are on the move. Other areas of interest include accessibility, wearable devices and in-car interaction. He pioneered the study of non-speech audio and haptic interaction for mobile devices with work starting in the 1990's.

According to Google Scholar, he has 375 publications. He has served as an Associate Chair, Sub-Committee Chair and Papers Chair, and has chaired the Interactivity, Doctoral Consortium and Student Design Competition tracks at ACM CHI.

En esta charla trataré de explorar el problema de clasificación de opiniones en entornos multingües y multi-dominio, en los cuales la disponibilidad de datos es escasa. ¿Cómo se pueden aprovechar los recursos de otros dominios y en otros idiomas para el desarrollo de buenos clasificadores? ¿Cómo el análisis de opiniones a nivel de aspecto afecta al problema del aprendizaje multi-dominio y multilingüe? Describiré una serie de enfoques actuales que son bastante eficientes y efectivos, dado que los cuales alcanzan los resultados del estado del arte con un uso mínimo de recursos lingüísticos.

Andrea Esuli desarrolla su carrera investigadora desde el año 2005, primeramente como investigador asociado y desde 2010 como investigador, en el Consejo Nacional de Investigación de Italia (Consiglio Nazionale delle Recerche). Su investigación se centra en recuperación de información multimedia, aprendizaje automático y clasificación de texto, con especial atención a la tarea de análisis de opiniones. Andrea es doctor en Ingeniería de la Información por la Universidad de Pisa, y en 2010 fue galardonado con el premio Cor Baayen del Consejo de Investigación Europeo de Informática y Matemáticas.

Many real-world classification problems have unbalanced classes, e.g., in fault detection and software defect prediction, where there are a large number of training examples for the normal class, but few for the abnormal classes. This talk gives an overview of some recent algorithms for dealing with class imbalance in machine learning, including ensemble approaches, sampling methods, evolutionary computation methods, and their combinations. First, we will discuss how diversity influences the classification performance, especially on the minority class, in ensemble classification algorithms. Then new ensemble algorithms are introduced and evaluated experimentally. Multi-class imbalance will be analysed and considered. The combination of ensemble learning and sampling techniques for dealing with class imbalance will be presented.

Finally, we consider a new problem — online class imbalance learning of data streams, where the majority and minority classes are not pre-defined and have to be learned and detected online. This talk is partially based on the following publications:

• S. Wang and X. Yao, “Relationships Between Diversity of Classification Ensembles and Single-Class Performance Measures,” IEEE Transactions on Knowledge and Data Engineering, 25(1):206-219, January 2013.
• S. Wang and X. Yao, “Multi-Class Imbalance Problems: Analysis and Potential Solutions,” IEEE Transactions on Systems, Man and Cybernetics, Part B, 42(4):1119-1130, August 2012.
• M. Lin, K. Tang and X. Yao, “A Dynamic Sampling Approach to Training Neural Networks for Multi-class Imbalance Classification,” IEEE Transactions on Neural Networks and Learning Systems, 24(4):647-660, April 2013.
• U. Bhowan, M. Johnston, M. Zhang and X. Yao, “Evolving Diverse Ensembles using Genetic Programming for Classification with Unbalanced Data,” IEEE Transactions on Evolutionary Computation, 17(3):368-386, June 2013.
• S. Wang, L. L. Minku and X. Yao, “Resampling-Based Ensemble Methods for Online Class Imbalance Learning,” IEEE Transactions on Knowledge and Data Engineering, 27(5):1356-1368, May 2015.

Xin Yao is a Chair (Professor) of Computer Science and the Director of CERCIA (Centre of Excellence for Research in Computational Intelligence and Applications) at the University of Birmingham, UK. He is an IEEE Fellow and a Distinguished Lecturer of IEEE Computational Intelligence Society (CIS). He previously served as the Editor-in-Chief (2003-08) of IEEE Transactions on Evolutionary Computation and the President (2014-15) of IEEE CIS. His main research interests include evolutionary computation, ensemble learning, and their applications, especially in software engineering.

His papers won the 2001 IEEE Donald G. Fink Prize Paper Award, 2010 and 2015 IEEE Transactions on Evolutionary Computation Outstanding Paper Awards, 2010 BT Gordon Radley Award for Best Author of Innovation (Finalist), 2011 IEEE Transactions on Neural Networks Outstanding Paper Award, and many other best paper awards.He won the prestigious Royal Society Wolfson Research Merit Award in 2012 and the IEEE CIS Evolutionary Computation Pioneer Award in 2013. Over the years, he has collaborated with many industrial partners in his research, including Honda, BT, Thales, Marconi Communications, IBM, Unilever, STMicroelectronics, GSK, Rolls Royce, etc.

El concepto de Ciudad Inteligente puede entenderse a partir de una aproximación holística que considere un enorme número de facetas del trabajo en la ciudad del futuro junto con los dominios de investigación involucrados y los actores implicados. Con el objetivo de crear nuevos servicios y mejorar la calidad de vida efectiva de los ciudadanos, se están abriendo numerosas oportunidades para proponer nuevas ideas que requerirán extender los conocimientos actuales, suponiendo un desafío científico importante para los algoritmos y tecnologías actuales. La participación de empresas y de los responsables políticos de la ciudad además representan un nuevo entorno de trabajo rutinario donde desarrollar los avances científicos que claramente determina la manera y resultados que pueden obtenerse.

El concepto de inteligencia en la nueva Ciudad Inteligente es, entre otros desafíos, un tema que no está bien desarrollado. A veces se trata de dar nuevos servicios per se, o de usar nuevas tecnologías sin más, o de generalizar a la población un nuevo resultado científico. Pero en general no está claro cuánto de inteligentes son los sistemas inteligentes que ahora se hacen para la Ciudad Inteligente. Tampoco está claro cómo puede usarse el estado del arte actual en sistemas inteligentes y cuánto debe crearse nuevo para conseguir el trabajo ubicuo, en tiempo real, con nuevas interfaces y para los nuevos tipos de problemas que tendrán que resolverse en este dominio.

Esta charla discutirá los componentes de la Ciudad Inteligente del futuro (movilidad, energía, construcción...) y especialmente las oportunidades para investigar con sistemas inteligentes que, además de suponer un desafío intelectual, resulten en aplicaciones de escritorio, web y apps útiles para los ciudadanos y los gestores de la ciudad.

Dr. Enrique Alba is a Professor of Computer Science at the University of Málaga, Spain. He got his Ph.D. degree on designing and analyzing parallel and distributed genetic algorithms. His current research interests involve the design and application of metaheuristics and bio-inspired systems to real problems in smart cities, telecommunications, combinatorial optimization, software engineering, and bioinformatics.

The main focus of all his work is on parallelism, having long experience in cluster computing, grid/cloud algorithms, P2P techniques, multi/many-core systems, GPU developments, Myrinet/Gigabit Ethernet analysis and WiFi ad-hoc networks in MANET and VANET (vehicular networks).

Part of his ongoing research lies in the fields of discrete and continuous optimization, ad-hoc metropolitan network optimization, smart mobility, optimal design of GSM networks, logistics, vehicle routing, DNA fragment assembly, gene microarrays, software testing and validation, and in general hard problems lying in the base of real world problems.

New fields like multiobjective techniques, grid/P2P/Internet platforms, dynamic optimization of problems whose definition change in time, self-adaptive efficient techniques, and heterogeneous algorithms are dealt with as part both of basic and applied research.

As to the techniques, Prof. Alba and his group are dealing mainly with metaheuristics, either bio- inspired or not, and also hybridization with other (maybe exact) methods. In concrete, evolutionary algorithms, particle swarm, ant colonies, simulated annealing, variable neighborhood search, branch and bound, and related solvers are used. Theory and methodology is stressed in all developments.

Prof. Alba has published 12 monographs on complex problem solving, 68 papers in ISI indexed journals, and more than 250 conference papers. He has coordinated several national and international research projects in the past. Some of these projects are TRACER, OPLINK, M*, roadME, INRIA PERFOM and MOID, European projects like CARLINK or COADVISE, and Excellence Projects in Andalucía like DIRICOM. Prof. Alba holds active collaborations (join publications, visits, and exchanges) with more than 20 international universities and labs, and his research in Málaga is also provoking industrial transferences to several companies like OPTIMI, ARELANCE, NOVASOFT, ACERINOX, VTT, ETRA, etc. Collaboration in two software packages that are in exploitation by OPTIMI (now Ericsson) protected under intellectual policy (x-AFP ad x-ACP).

All PhD theses directed by Prof. Alba in Málaga have the European mention of quality. He has supervised dozens final degree theses, 15 master theses, 10 PhD theses, and currently works in co-direction to more than 14 running new theses around the world. This evidences a large vocation to human training in research, with demonstrable results in terms of highly cited publications (H index 36), more than 6000 cites, and more than 45 international seminars and plenary talks.

Finally, Prof. Alba works in the program committee of well-known important conferences in several fields, like ACM GECCO, IEEE CEC, PPSN, EvoCOP, IPDPS and many more, as well has he organizes international events like NIDISC, IEEE/ACM MSWiM and the next GECCO 2013 (as general chair in this top conference in the field). He also works as reviewer for IEEE Transactions (on EC, PDS, Education, SMC), JPDC, PARCO, Journal of Heuristics, JMMA, EJOR, Computer Communications, etc. Besides, Prof. Alba works in the editorial board of several international journals related to optimization, telecommunications, and parallel systems.

Los llamados algoritmos de propagación basados en paso de mensajes en modelos gráficos permiten realizar de forma eficiente tareas de inferencia en casos de gran tamaño. Pero, como el problema es NP-difícil, surge la necesidad de diseñar algoritmos aproximados.

En esta conferencia haremos un repaso a los distintos problemas de cálculo asociados al razonamiento probabilísticos (cálculo de probabilidades condicionadas, MAP, MPE, máxima utilidad esperada) y las distintas estrategias que se han usado en su resolución. Para ello usaremos un lenguaje abstracto basado en las valuaciones de Shafer y Shenoy tratando de dar una versión unificada tanto de los algoritmos deterministas (‘mini-buckets’, métodos variacionales, etc..) como de los estocásticos (muestreo por importancia o basado en cadenas de Markov). Dada la naturaleza distribuida de los algoritmos de propagación, especial atención se dará a estrategias iterativas basadas en aprender a realizar cada vez mejores aproximaciones de una información teniendo en cuenta la calidad de las aproximaciones en otros elementos del problema. La idea será tratar de extraer los principios básicos de los métodos empleados, con el objetivo de poderlos emplear en problemas de razonamiento asociados a otros modelos de representación de la información, lo que se ilustrará fundamentalmente con inferencia en lógica proposicional (SAT, MAXSAT, MAJSAT). De esta manera, se pretende poner en relacción los desarrollos en este campo con uno de los más antiguos e importantes objetivos de la IA: la construcción de motores universales de inferencia.

Serafín Moral obtuvo la Licenciatura de Matemáticas en 1981 y el título de Doctor en 1985, ambos en la Universidad de Granada. Es Catedrático del área de Ciencias de la Computación e Inteligencia Artificial desde 1998. Trabaja en razonamiento con incertidumbre en Inteligencia Artificial, modelos gráficos probabilísticos y probabilidades imprecisas.

Ha publicado más de 90 trabajos en revistas internacionales y sobre 110 trabajos en actas de congresos y capítulos de libros. Su índice h es de 37 en Google Académico. Ha dirigido 13 tesis doctorales y ha participado en más de 20 proyectos de investigación obtenidos en convocatorias competitivas de carácter nacional y europeo.

Ha sido responsable del comité de programa y organizador de 5 congresos de carácter internacional. Es resposable de área de las revistas Artificial Intelligence Journal, International Journal of Uncertainty, Fuzziness and Knowledge Based Systems y Progress in Artificial Intelligence.

Es Fellow del European Coordinating Committee for Artificial Intelligence (ECCAI).

La minería de texto juega un papel clave en la extracción automática de metadatos semánticos dirigiendo la extracción hacia la información estructurada a partir de documentos no estructurados que incluyen términos, entidades y relaciones complejas entre ellos (eventos) En la primera parte de la charla se describirá la construcción automática del inventario de términos de gran escala para biodiversidad, en el que se han aplicado métodos de semántica distribucional a los documentos de la Biodiversity Heritage Library, para identificar grupos de términos, sinónimos y términos relacionados.

En la segunda parte de la charla, se comentarán los desarrollos recientes sobre técnicas de extracción de eventos usados en el contexto del proyecto Big Mechanism financiado por DARPA. Las técnicas descritas no solo sirven para identificar los eventos sino también para capturar diferentes aspectos de su interpretación contextual como la incertidumbre y la negación. En la parte final de la charla, se discutirá el trabajo desarrollado en el contexto del proyecto OpenMinted (http://openminted.eu) sobre problemas de incompatibilidad que se suelen dar cuando se procesan textos de diferentes dominios o cuando se combinan herramientas con diferentes formatos en la entrada/salida, distintos idiomas y representaciones semánticas. La incompatibilidad puede ser manejada utilizando infraestructuras de minería de texto, que abordan la interoperabilidad de recursos dando acceso a los usuarios a entornos que soportan la integración de distintos corpora, terminologías y herramientas en soluciones unificadas.

Sophia Ananiadou es catedrática de la School of Computer Science en la University of Manchester. Actualmente, también es la directora del National Centre for Text Mining (NaCTeM), que es el primer centro enfocado a la minería de texto financiado públicamente en el mundo.

Software Testing involves the development of smart techniques to automatically find test inputs which uncover faults in programs. An emerging trend in this area, called ``Constraint-Based Testing'', aims at exploiting constraint solving techniques for this goal. My talk will review different techniques including dynamic symbolic execution, path-based exploration and constraint-based exploration and will emphasize the usage of advanced Constraint Programming tools.

Arnaud Gotlieb is a French research scientist in Computer Science, currently leader of the Certus Centre, Simula's Centre for Research-based Innovation (SFI) on Software Verification & Validation. Dr. Gotlieb's expertise is on the application of constraint solving to software testing. At the beginning of his career, he spent 7 years in Industry working for Dassault Electronics, Thomson-CSF and Thales. He joint INRIA, the French National Institute on Computer Science and Automatisms in 2002 where he made advances on constraint-based testing in a group specialized in static analysis and verification. He has contributed to several projects that aimed at improving static analysis, testing and verification tools of critical embedded software in civil and military avionics. He was the coordinator of the ANR CAVERN project (2008-2011) that explored the capabilities of constraint programming for program verification and participated to several large European Project proposals. Since October 2011, he has joint the Simula Research Laboratory in Norway as a senior research scientist. He is the main author of more than forty publications and co-author of more than seventy, and he is the main architect of several constraint-based testing tools for the testing of C and Java programs. He has served in the program committee the IEEE International Conference on Software Testing, Validation and Verification (ICST) since 2008 and many other conferences such as ISSRE, TAP, CP, SEIP; he co-chaired the technical program of QSIC in 2013 and the SEIP track of ICSE in 2014 and the Testing and Verification track of CP in 2016. He initiated the Constraints in Software Testing, Verification and Analysis (CSTVA) workshop series and was its main organizer during the first editions. He successfully co-supervised ten PhD students and was the head of the Software Engineering department at Simula from 2012 until 2015. He completed his PhD on automatic test data generation using constraint logic programming techniques in 2000 at the University of Nice-Sophia Antipolis and got habilitated (HDR) in Dec. 2011 from University of Rennes, France.

While most business people nowadays have heard of the term big data, not everybody has a concrete idea of what big data means in practice and what it can achieve. Once organisations do understand the opportunity, and have decided to embark on their big data journey, for many it is not clear where to start and how to approach the journey. This talk will give concrete examples and use cases of big data, and discuss various relevant aspects to consider when implementing a big data strategy, including technology, analytics, use cases, data culture & organisational aspects.

Dr. V.R. (Richard) Benjamins is Group Director BI & Big Data responsible for internal exploitation across Telefonica. Previously he was Director of Business Intelligence at Telefonica Digital, the digital branch of Telefoncia. Before that he was responsible for Global BI programs across Telefonica's footprint, and Director of User Modelling, where he was responsible for research and development in areas related to customer intelligence. His responsibilities included the development and technology transfer of products in data mining, big data, targeted advertising, personalisation, and privacy. Richard is a frequent speaker on big data, BI and analytics events. Previously he was Director of Technological Strategy at Telefonica R&D, which he joined in July 2007.

Before joining Telefonica, he was director and board member at iSOCO, which he co-founded in 1999. Based on his work, iSOCO were granted the National Award for Computer Science in 2005. Dr. Benjamins has held positions at the Technical University of Madrid, the University of Amsterdam, the University of Sao Paulo, Brazil, the University of Paris-South, France, and the Spanish Artificial Intelligence Research Institute in Barcelona.

Dr. Benjamins is one of the founding members of a European Incubator for Open Data start-ups (http://opendataincubator.eu/)

He has published over 100 scientific articles (http://www.researchgate.net/profile/ V_Richard_Benjamins/) about artificial intelligence, knowledge-based systems, semantic web. He co-chaired numerous international workshops and conferences. He is on advisory boards of several start-ups and international research projects. He was general chair of the K-CAP 2013 Conference and co-chair of the Industrial track at ISWC 2014.

He is a member of the editorial board of IEEE Intelligent Systems. Dr. Benjamins received his Ph.D. (1993) in Cognitive Science/Artificial Intelligence from the University of Amsterdam.

En el mundo actual, sobrecargado de datos, es necesario explorar nuevas formas de hacer que la información sea comprensible para los usuarios de aplicaciones o servicios. En este contexto, los sistemas de generación automática de lenguaje natural "de datos a texto" (D2T) se están utilizando cada vez más para eliminar la barrera que existe entre los datos y las personas que debe utilizar. Los sistemas D2T generan automáticamente narrativas de muy alta calidad, en las que recoge la información más relevante oculta en los datos y se proporciona en una forma comprensible directamente por parte de los usuarios humanos.

En este charla se plantean las bases generales de los sistemas sistemas, se describe el rol que juega actualmente en ellos –o podría jugar- el Soft Computing y otras metodologías de la Inteligencia Artificial. Realizaremos también una revisión de los casos de mayor impacto de sistemas D2T, en ámbitos como robot-periodismos, previsiones meteorológicas, sistemas de supervisión médica o industrial, entre otros.

He participado en 50 proyectos de I+D+i, contratos con empresas y actividades de estructuración de la investigación en las áreas de modelado de sistemas inteligentes con incertidumbre (sistemas basados en reglas borrosas), aprendizaje automático de modelos de predicción (escalables a Big Data) y data mining descriptivo (sistemas "Data-To-Text). En 14 de estas actividades he sido investigador principal y nueve de ellas han sido contratos/proyectos con empresas. La investigación se ha aplicado en ámbitos como la generación automática de descripciones de datos en lenguaje natural, la mejora de procesos de producción industrial, recuperación de información documental, e-learning y monitorización inteligente en dominios médicos e industriales. Esta actividad se describe en casi 200 trabajos científicos con proceso de revisión en las áreas anteriormente indicadas.

EasyChair started in 2002 as a small collection of scripts helping the author to organise submission and reviewing for the conferences LPAR and CADE. Since then it has served over 47,000 conferences and 1,700,000 users. The system has over 320,000 lines of source code and automates paper submission, reviewing, proceedings generation, publishing, conference registration and conference programme generation. Several new modules are about to be released. EasyChair generates more Web traffic than 80% of UK universities.

The design and architecture of every very large Web service is unique, and EasyChair is not an exception. This talk overviews design features of EasyChair, which may be interesting for the database and software engineering community:

• (1) Highly agile development methodology
• (2) Design centred around a small number of concepts
• (3) Automatic generation of efficient and secure code
• (4) An object caching technique eliminating mismatch between objects and relational data
• (5) Server-side generation of client-side code
• (6) Automation of code management
• (7) Light-weight code analysis
• (8) Automatic generation of documentation
• (9) Integrity constraint management
• (10) Separation of visual design of pages from their content

Andrei A. Voronkov is a Professor of Formal methods in the School of Computer Science at the University of Manchester and he was educated at Novosibirsk State University,[2] graduating with a PhD in 1987.

Voronkov is known for the Vampire automated theorem prover, the EasyChair conference management software, the Handbook of Automated Reasoning (with John Alan Robinson, 2001), and as organiser of the Alan Turing Centenary Conference 2012. Voronkov's research has been funded by the Engineering and Physical Sciences Research Council. In 2015, his contributions to the field of automated reasoning were recognised with the Herbrand Award.

Today we take for granted the ability to freely and seamlessly collaborate with others on document editing, with applications such as Dropbox and Google Docs. The 3D industry though is still in its infancy in supporting this type of workflows. In this talk, I will describe a few of our research prototypes that allow seamless collaboration for editing meshes and game levels. I will then discuss challenges that we face as a community in developing these types of systems.

Since the Winter of 2011 Fabio is an Associate Professor in Computer Science at Sapienza Universita' di Roma, where he runs the Computational Design Lab, a group dedicated to using Computer Graphics methods to solve content creation and design problems. Before then he was an Assistant Professor (2005-2009) and then an Associate Professor (2009-2011) in Computer Science at Dartmouth College, an Ivy League University. Before Dartmouth he was a Visiting Assistant Professor (2004-2005) in Computing and Information Science at Cornell University. Fabio also worked in the research division of Pixar Animation Studios (2002-2004) developing new algorithms used in various award winning feature films (Monster's Inc., Finding Nemo, The Incredibles, Cars). He received a Ph.D. in Computer Science from Cornell University in 2002, working at the Program of Computer Graphics, and a Laurea degree in Physics (equiv. to BS and MS) from the University of Parma, Italy. He received an NSF CAREER award in 2008, and an Alfred P. Sloan research fellowship in 2009.

Today, the digital life of people in developed markets is dominated by PCs and smartphones. Yet, as successful as PCs and smartphones are, the dominant era of PCs and smartphones is about to come to an end. Device shipment trends indicate that the number of web-enabled devices other than PCs and smartphones will grow rapidly. In the near future, people will commonly use various types of internet-connected devices in their daily lives. Unlike today, no single device will dominate the userís digital life. The transition to a world of multiple device ownership is still rife with problems. Since devices are mostly standalone and only stay in sync in limited ways, the users will have to spend a lot of time managing them. These device management chores become much more tedious as the number of devices in a personís life increases. In this paper we look at the ongoing paradigm shift towards multiple device ownership and its implications for software architecture. In this keynote, we argue that the transition to multiple device ownership will eventually lead us to liquid software ñ an approach that will allow data and applications to seamlessly move between multiple devices and screens. The new era will imply significant changes in the development, deployment and use of software, opening up new opportunities in software engineering research as well.

In the light of the evolution towards simpler user experience, multiple device ownership should be as casual, fluid and hassle-free as possible. By casual computing, we refer to a model of computation that is constantly available, capable of delivering meaningful value even in a few moments, without requiring active attention from the userís part. Casual computing is as much a mindset as a specific set of technologies ñ the idea is to make technologies themselves so natural, effortless and calm that they will effectively disappear. A central aspect of a true casual computing experience is the ability to move fluidly from one device to another. By liquid software, we refer to an approach in which applications and data can flow from one device or screen to another seamlessly, allowing the users to roam freely from one device to another, no longer worrying about device management, not having their favorite applications or data, or having to remember complex steps. In a true liquid software environment, device management chores such as backups, application installation, application upgrades, restarting the recently used applications, account migration, copying settings across devices, or other similar activities that burden the daily lives of users today should be things of the past.

Tommi Mikkonen works as a professor of software engineering at Tampere University of Technology, Tampere, Finland. During his career, he has been pioneering mobile device programming as well as web applications as academic research topics. Overall, he has published over 200 articles of different types, and participated in numerous initiatives regarding collaboration of universities and industry.

The fundamental paradigms for the definition of Critical-Real Time Embedded Systems (CRTES) architectures are changing due to cost pressure, flexibility, extensibility and the demand for increased func- tional complexity. CRTES have been based on the federated architecture paradigm, which simplifies verifi- cation by providing a separation of responsibilities, hence enabling each provider to implement the hardware and software for a particular function independently from other suppliers. However, implementing an in- creasing amount of functionality on a Federated Architecture requires a high number of hardware units, mak- ing federated implementations inefficient in terms of size, weight and power consumption.

To cope with such problem, the automotive and avionics industries are adopting Integrated Architectures (IA). One fundamental requirement of integrated architectures is to ensure that incremental qualification (verification) is possible, whereby each software partition can be subject to verification and validation – including timing analysis – in isolation, independent of the other partitions, with obvious benefits for cost, time and effort. In this talk I will focus on the timing component of incremental qualification. I will present some hardware support that can enable composability while providing high performance. I will also talk about existing soft- ware support to increase time predictability and time composability. I will also talk about the feasibility of a probabilistic timing analysis approach, and the hardware support required in order to enable it, as a way to provide high performance and time composability.

Francisco J. Cazorla is a researcher at the National Spanish Research Council (CSIC). He is currently the leader of the group on Interaction between the Operating System and the Computer Architecture at Barcelona Supercomputing Centre (http://www.bsc.es/caos). His research area focuses on multithreaded architectures for both high-performance and real-time systems. He has co-authored over 100 papers in inter- national refereed conferences. He has participated in several projects with industry including several proces- sor vendor companies (IBM, Sun microsystems) and European FP6 (SARC) and FP7 Projects (MERASA, parMERASA, SAFURE, PROARTIS). He currently leads the PROXIMA project and one project with the European Space Agency.

Se describe la experiencia del conferenciante sobre cómo mejorar considerablemente los conocimientos que adquieren los alumnos utilizando la metodología de clase al revés (flipped classroom).

La experiencia se inició grabando en vídeo 37 clases (“videoclases”) correspondientes al curso completo de Fundamentos de Informática que se imparte en el primer curso de las titulaciones de Ingeniería de Telecomunicación y de Ingeniería Electrónica Industrial de la Universidad de Granada e integrándolas en Youtube. Estas videoclases se proyectaron para nuestros alumnos, y sin embargo en cerca de dos años ya han tenido más de 83.100 accesos desde 92 países.

Nuestros alumnos siguen el curso como si fuese un MOOC, pero complementándolo con las clases presenciales que ahora se dedican únicamente a interacción directa con el alumno a través de la resolución de dudas, problemas, debates, etc.

La conferencia se centrará en los aspectos prácticos relacionados con la puesta en marcha y desarrollo de la experiencia, mostrando resultados sobre la mejora del rendimiento académico y aceptación de la nueva metodología por parte de los alumnos.

Palabras clave: Clase invertida, Enseñanza semipresencial, Docencia aprendida, Flipped Classroom, Flipped Learning, Blended Learning, Lessons Learned.

Alberto Prieto Espinosa, es Catedrático Emérito del Departamento de Arquitectura y Tecnología de Computadores de la Universidad de Granada.

Además de sus actividades de investigación, enfocadas principalmente al desarrollo e implementación de Sistemas Inteligentes, ha participado en distintos proyectos de innovación docente y publicado 5 libros de texto de enseñanza universitaria en las editoriales McGraw-Hill, Thomson y Garceta.

En la actualidad está interesado en el desarrollo de métodos y técnicas orientadas a la docencia semipresencial (Blended Learning).

http://atc.ugr.es/APrieto_CV

The conversion of raw geometric data (that typically comes in the form of unstructured triangle meshes) to high quality quad meshes is an important and challenging task. The complexity of the task results from the fact that quad mesh topologies are subject to global consistency requirements which cannot be dealt with by local constructions. This is why recent quad meshing techniques formulate the mesh generation process as a global optimization problem. By adding hard and soft constraints to this optimization, many desired properties such as structural simplicity, principal direction alignment, as well as injectivity can be guaranteed by construction. An even more challenging problem is the computation of quad layouts, where a coarse segmentation of the input surface into essentially rectangular patches is sought which also satisfies global consistency and shape quality requirements. While being structurally related, both problems need to be addressed by fundamentally different approaches. In my talk I will present some of these approaches and demonstrate that they can generate high quality quad meshes and quad layouts with a high degree of automation but that they also allow the user to interactively control the results by setting boundary conditions accordingly.

Leif Kobbelt is a full professor of Computer Science with a specialization in Computer Graphics and Geometry Processing. Since 2001 he is the head of the Institute for Computer Graphics and Multimedia at RWTH Aachen University.

After having received his diploma in 1992 and his PhD in 1994 in Computer Science from the Karlsruhe Institute of Technology (both with distinction) he worked at the University of Wisconsin in Madison, the University of Erlangen-Nuremberg and the Max Planck Institute of Computer Science before he moved to RWTH Aachen University in 2001. His major research interests include 3D reconstruction, efficient geometry processing, realistic real-time rendering and (mobile) multimedia applications. Kobbelt published a substantial number of influential papers in international top-conferences and journals. In addition, he acts as a consultant, reviewer, and editor for international companies, research organizations and journals respectively. For his research he was awarded with a number of renowned academic prices including the Heinz-Maier-Leibnitz price in 2000, the Eurographics Outstanding Technical Contribution Award 2004, the Günther Enderle Award (in 1999 and 2012), an ERC Advanced Grant 2013 and the Gottfried Wilhelm Leibniz Prize in 2014. He has been named a Fellow of the Eurographics Association (2008) and a Distinguished Professor of RWTH Aachen University (2013). In 2015 he became a member of the Academia Europaea and in 2016 a member of the North Rhine Westphalian Academy of Sciences, Humanities and the Arts.

La ponencia versará sobre la experiencia de IBM en el sector TI, con el objetivo de dar una visión sobre las líneas de desarrollo en las que está involucrada, las tendencias tecnológicas presentes en el mercado, las previsiones futuras sobre el sector tecnológico, así como las áreas de investigación y otros mecanismos que posibilitan el avance tecnológico y la integración en todo ecosistema involucrado.

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