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Introduction to Educational Technology (Andri Ioannou)

Title: Introduction to Educational Technology.

Presenter: Andri Ioannou

Dates: June 1, 2 and 3, 2016

Time:  9:30 am - 3 pm

Organizer: Grupo Arcade, Departamento de Informática​

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)


The seminar analyzes the educational potential of technology and examines its current and prospective application in formal and informal education. The course gives a brief overview of modern learning theories in relation to the design of learning environments. For the main part of the course, students participate in hands-on examination of contemporary applications of educational technologies (such as Web 2.0 applications, social networks, mobile technologies, virtual worlds, augmented reality). Bring Your Own Device! (Laptops, tablets and smartphones - preferably android)!

Andri Ioannou is an assistant professor in the Department of Multimedia and Graphic Arts and co-director of the Cyprus Interaction Research Lab at the Cyprus University of Technology, Cyprus. Andri has a PhD in Educational Technology from the University of Connecticut (USA) and a BSc in Computer Science from the University of Cyprus. Her research interests include the design and evaluation of computer-supported collaborative learning environments, use of technology to support student collaboration, decision making, and knowledge creation in both distant and collocated settings, integration of technology in all levels of education, and use of technology for social change. More information about published work and current research projects here:

Many-Objective Optimization with Estimation Distribution Algorithms (Luis Martí)

Title: Many-Objective Optimization with Estimation Distribution Algorithms

Presenter: Luis Martí. Associate Professor at IC/UFF

Date: May 30, 2016

Time: 6pm - 8pm

Organizer: SCALAB, Departamento de Informática​

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)

ECTS: 0.3

Language: Spanish

Many theoretic and real-life problems are, or can be posed as, optimization problems. Frequently, these problems involve more than one aspect to be optimized. This class of problems is known as multi-objective optimization problems (MOPs). If a MOP has certain characteristics, e. g., linearity or convexity of the objective functions, the solution can be exactly determined by mathematical programming approaches. However, in the general case, finding the solution of  a MOP is an NP–complete problem. Therefore, heuristic or metaheuristic methods have to be applied in order to have solutions of practical value at an admissible computational cost. Evolutionary algorithms (EAs) have shown themselves as one of the most apt approaches to these problems. MOPs that has many objective functions poses a challenge to EAs, prompting the application and development of more advanced methods. Estimation of Distribution Algorithms (EDAs) are one of those methods. EDAs substitute the application of the evolution-inspired operators of EAs with the creation of an statistical or machine learning model of the best elements of the population. That model is then sampled to create new individuals. The extension of EDAs to the multi-objective domain calls for custom modeling methods. Prompting new issues that must be dealt with. In this tutorial we present the state-of-the-art on the multi-objective optimization problem and how it can tackled using estimation of distribution algorithms. We make an special emphasis on many-objective problems and how some classes of EDAs show themselves as more scalable when compared with "traditional" approaches.

Mini CV:
Luis Martí is Associate Professor at IC/UFF. Before that, he was at the Pontifical Catholic University of Rio de Janeiro with a CNPq Young Talent Attraction fellowship. He studied Computer Science at the University of Havana (UH), Cuba, and got a PhD on Computer Science and Technology from the University Carlos III of Madrid (UC3M), Spain. He has served as Junior Professor at UH, as Assistant Professor at UC3M and as Research Fellow at T.U. Dortmund (Germany). He has also been visiting researcher at the University of Udine, Italy; the Center of Research and Advanced Technologies (CINVESTAV), Mexico, and T.U.Dortmund, Germany. He is mainly interested in machine learning, evolutionary computation, multi-objective optimization and multi-criteria decision making, estimation of distribution algorithms, and other related matters.

Ambient Intelligence: Next Steps to Sense the Future (Nayat Sanchez-Pi)

Title: Ambient Intelligence: Next Steps to Sense the Future

Presenter: Nayat Sanchez-Pi.  Associate Professor, Rio de Janeiro State University

Date: May 30, 2016

Time: 4pm - 6pm

Organizer: SCALAB, Departamento de Informática​

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)

ECTS: 0.3

Language: Spanish

Ambient Intelligence (AmI) is a recent paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human computer interaction domain and focuses on offering ways to interact with systems in a more natural way by means user friendly interfaces. This field is evolving quickly as can be witnessed by the emerging natural language and gesture based types of interaction. The inclusion of computational power and communication technologies in everyday objects is growing and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. This seminar aims to present the multidisciplinary field of Ambient Intelligence and discuss the latest results, ideas, applications and lessons learned.

Mini CV:
Nayat Sanchez-Pi is Associate Professor of Computer-Human Interaction at the Department of Informatics and Computer Science  of the Institute of Mathematics and Statistics of the Rio de Janeiro State University (Universidade do Estado do Rio de Janeiro, UERJ). Dr. Sanchez-Pi research interests have broadened over the years and span topics that range from artificial intelligence, machine learning and data mining to ambient intelligence, ubiquitous computing and multi-agent systems. This is a consequence of the collaboration with several research groups: the Active Documentation  and Intelligent Design Laboratory (ADDLabs) of the Institute of Computer Science of the Fluminense Federal University; the Laboratory of Agent Modelling (LabMAg) at theFaculty of Science of the University of Lisbon; the School of Computer Science and Informatics at University College Dublin, and the Group of Applied Artificial Intelligence at the Computer Science Department of University Carlos III of Madrid. Her research profile for the last 10 years includes active research in the area of applied artificial intelligence. She has several publications in national and international peer reviewed conferences, books chapters and high standard international journals.

Accessibility in egoverment services (Jose Ángel Martínez Usero)

Title: Accessibility in egoverment services: present situation, key EU initiatives and future trends.

Presenter: Dr. Jose Ángel Martínez Usero (Funka AB)

Date: May 24 and 25, 2016

Time: Tuesday 24 May: 3-7 pm / Wednesday 25 May: 3-8 pm

Organizer: Grupo SINTONIA, Departamento de Informática, UC3M

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)


The seminar will introduce a holistic approach of different accessibility aspects in the context of egovernment services: key concepts, EU policy, legal framework, standards.

The ICT technological context will be introduce, presenting overall concepts on user centre design, reactive web, WCAG 2.0, navigation good practices, etc.

Moreover, some EU projects and studies will be presented as a reference of present research and state of the art in the field, pointing out specific methodologies, platforms, frameworks and technologies that are being used.

Finally, some challenges and potential research trends in the field of accessibility in egovernment services will be a matter of discussion in the seminar.

Jose Angel Martinez holds a PhD in Information Science (Hons) from Madrid’s Universidad Carlos III, with the Thesis dissertation on “Interoperability technologies and Knowledge management in e-government services”. He also holds a Doctorate Course in Business Administration, a MSc in Corporate Networks and a Postgraduate Course in Information Management. In the last 15 years he has combined teaching at University with consultancy for ICT companies. During the period 2007-2010, he was the Director of the online Master on ICT Technologies for the access to information society services, at Open University of Catalonia.

Dr. Martinez-Usero has an extensive experience as Project coordinator of EU projects, such as: PROEIPAHA, a H2020 CSA to support EIP on AHA, The 7th FP CLOUD4all on Cloud platforms Lead to Open and Universal access for people with Disabilities and for All, The CIP Pilot APSIS4all on Accessible and personalised self-service terminals. 2010-2013; The Thematic Network ATIS4all on Assistive Technologies and inclusive solutions. 2010-2013. Dr. Martinez-Usero has been also project coordinator of several major European Studies on ICT accessibility.

Dr. Martinez Usero is the Responsible for international affairs of Funka AB a Swedish company in the ICT accessibility field. At present, he is the coordinator of the EU study on web accessibility monitoring methodologies and the CSA to support EIP on AHA, as well as accessibility partner in the EU project WeGOVNow

Computer Vision: Basics and Examples (Sergio Velastin)

Títle: Computer Vision: Basics and Examples.

Presenter: Sergio Velastin

Dates: May 13 and 20, 2016

Time: 3pm - 6pm

Organizer: SCALAB, Departamento de Informática​

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)



"Computer Vision: Basics and Examples"
We will start by giving an overview of what computer vision aims to do, looking at a number of application domains and highlighting its main processes: image processing, segmentation, object detection, motion tracking, etc. In the second session we will present some basic image processing operations, leading (if time allows) to looking at approaches used for object classification.


Sergio A Velastin a Marie Skodowska-Curie Postdoctoral Conex Research Professor at the Applied Artificial Intelligence Research group, Department of Computer Science, Universidad Carlos III de Madrid. He got his PhD on Computer Vision at the University of Manchester (UK) and became Professor of Applied Computer Vision at Kingston University London (UK) where he also directed its Digital Imaging Research Centre. Before joining UC3M, he was research professor at the University of Santiago de Chile. His main research interest are on computer vision applied to human monitoring e.g. in the contexts of visual surveillance and Assisted Living.

Music and operations research (Dorien Herremans)

Title: Music and operations research: applications in automatic music generation and dance hit prediction.

Presenter: Dorien Herremans (Queen Mary University)

Date: November 27, 2015

Time: 4:30 pm - 6:30 pm

Organizer: Departamento de Informática – Grupo de Investigación SCALAB

Place: 2.1.C19 Edificio Sabatini (Campus de Leganés)

ECTS: 0.3

The field of operations research offers us powerful optimization and data mining techniques. In this talk we'll explore how these can be useful in the domain of music by looking at two applications: automatic music generation and dance hit prediction.

In the first part of this talk, we'll look at generating music as an optimization problem. In particular, we'll be focusing on music which has a long term structure. A powerful variable neighbourhood search algorithm (VNS) was developed, which is able to generate a range of musical styles based on it's objective function, whilst constraining the music to a structural template. In the first stage of the project, an objective function based on rules from music theory was used to generate counterpoint. In the next stage, a machine learning approach is combined with the VNS in order to generate structured music for the bagana, an Ethiopian lyre. The approach followed in this research allows us to combine the power of machine learning methods with optimization algorithms.

In the second part of this talk, we'll zoom in on the dance hit song problem prediction problem. With annual investments of several billions of dollars worldwide, record companies can benefit tremendously by gaining insight into what actually makes a hit song.  We'll describe how we built a database of dance hit songs from 1985 until 2013, which includes basic musical features, as well as more advanced features that capture a temporal aspect. Different classifiers such as SVM and logistic regression are used to build and test dance hit prediction models. The resulting model has a good performance when predicting whether a song is a “top 10” dance hit versus a lower listed position.

Dorien Herremans is currently a Marie Skodowska-Curie Postdoctoral Fellow at C4DM, Queen Mary University of London. She got her PhD in Operations Research on the topic of Computer Generation and Classification of Music through Operations Research Methods (Compose≡Compute - Generating and Classifying Music through Operations Research Methods). She graduated as a commercial engineer in management information systems at the University of Antwerp in 2005. After that, she worked as a Drupal consultant and was an IT lecturer at the Les Roches University in Bluche, Switzerland. She also worked as a mandaatassistent at the University of Antwerp, in the domain of operations management, supply chain management and operations research (OR). Her current research focuses on applications of OR in the field of music.