The main research topics covered by the program are:
Agent Oriented Software Engineering.-
The application of software agent technology to develop new services heavily endowed with personalization features in heterogeneous distributed environments such as Internet, has drawn the attention of many researchers in the field of information technology and communications. The reasons can be explained from two aspects. First, from the point of view of modeling (ie considering the effort required to build a computer model that represents the real world), the capacity of multi-agent systems (MAS) to represent the relationships and roles that exist in systems with complex social relationships, such as those to be found in an electronic market or business processes of an enterprise or institution.
From a viewpoint of systems engineering, the characteristics of distribution, communication, modularity and intelligence that agents have, can improve aspects of flexibility (the functionality can be increased by introducing new types of agents in the system to provide new services), scalability (by adding new computing resources in the network, where agents can work), and ruggedness (can be defined as agents that monitor the operation of the system, and failures in the system can be repaired through the reorganization of the agents and their distribution).
This line of research is followed and supported by the Group of Web Intelligent Agents (GWAI). More information about the work, projects and resources can be found on the website GWAI. If you are only interested to access their recent publications you could access HERE.
Artificial Inteligence Techniques in Bioinformatics.-
Bioinformatics studies the application of computer technology to managing and analyzing biological data. The growth of this field in recent years has been outstanding and the trend has not changed. In fact, the demand for new computational techniques that can efficiently handle large amounts of data from new experimental techniques, among which is the massive sequencing of genomes, is growing. In this sense, Artificial Intelligence algorithms that include machine learning techniques, probabilistic models, optimization algorithms, etc. are particularly interesting for the resolution of problems in genomics, proteomics, systems biology, evolution, biological text mining, etc.
In the group's website SING (New Generation Information Systems) you can find additional information on this research, including major software developments brought by the group, the most recent impact publications and most relevant research projects related to the topic.
Application of Optimization and Simulation Algorithms .-
Using advanced heuristic search and optimization on real problems has increased significantly in recent years. As examples include applications in medical, business, industrial or agricultural. The main reason for using these techniques is its easy adaptation and good performance in complex problems and / or size where the classical mechanisms of search optimization and can not be applied. Within this line of research will analyze a number of examples of real applications of the techniques studied during the first course and propose new issues to consider its decision and analyze the results obtained with different techniques. More information can be found on the group page LIA.
Application of techniques for reuse of components in e-Learning environments.-
Under this topic are covered several research Lines:
- e-Learning: here the work is oriented to new trends in education, looking for the way in which students and educators can interact more properly and then the education can be better.
- HCI, Human-Computer Interaction: The work is centered in new Industrial and Educative environments, tools and systems to work more properly; in this field there are a collaborative work with other European Universities and Industries to conquer the proposed goals.
- Information Systems: New trends applied to the use of systems in education, government, industry, commerce in which the web2.0 and future standards are modifing the way things are done. In this field there are an ongoing work jointly with many other Universities in Europe in order to allow new ways of working.
Biomedical signal processing.-
Image analysis plays a fundamental role in modern biomedical sciences at many different scales. Several researchers on the Master have several ongoing projects that use use image analysis and pattern recognition to aide biological and biomedical researchers across a broad spectrum of imaging modalities and technologies.
In particular, the MILE Group maintain a collaborative effort with radiologists for improving radiography images in order to better diagnose cancer. We also have recently initiated a new collaboration with a leading hospital to study histopathology images using machine learning and pattern recogntion to provide better search and and indexing of pathology biopsy images. On a much smaller image scale, we are developing a new software application capable of analyzing multidimensional confocal microscopy images for basic immunology research, whose objective is to understand germinal center formation, as well as B- and T- cell function and behavior.
Computer Graphics, User Interfaces and Multimedia Systems.-
Multimedia Systems: The information content of multimedia systems is enormous. The research groups integrated on the Master have several research projects related to the automatic extraction of information from both video and audio. In particular, several projects related to automatic recognition of human activity in videos, as well as event clustering for the purpose of real-time monitoring for remote health care systems. Also related to human activity, there are ongoing research projects related to content based video retrieval and indexing based upon a query-by-example paradigm with low-level video processing of human actions.
Related to work in image processing of microscopy images, there is on the MILE Group an active collaboration with a leading biology laboratory for tracking and analyzing cells in 3-dimensional videos obtained from two-photon confocal microscopy video sequences. By using state of the art computer graphics, we reconstruct trajectories in 3-dimensions over time.
User Interfaces and Computer Graphics: Taking advantage of the tracking algorithms of the researchers of the Master, there are some ongoing projects related to Augmented Reality ; one of them oabout virtual musical instruments, where the program could interactively track the user's hands and fingers for producing sound in real-time.
Computer Vision .-
Computer vision is a discipline of applied computer science that attempts to obtain, on the basis of digital image processing, semantic knowledge of the contents of an image. Technique is applied in many fields of science. Among the research group participating in the PhD program are projects implemented in the field of biology where you want to extract specific information from images taken with microscopes or other means of acquisition. The techniques employed in the task of computer vision include data preprocessing , segmentation, feature extraction and classification as the ultimate goal. More information can be found on the group page LIA.
Data Mining, and Extraction of Knowledge Info .-
Extraction of Knowledge can be defined as the process of identifying patterns or models valid, novel, potentially useful and ultimately understandable in large collections of data. In particular, data mining can be seen as a step in the overall process of knowledge extraction, which is based on the joint use of machine learning algorithms, statistical analysis, modeling techniques and database technologies to find patterns and establish data relationships so that it is possible to predict future situations. This line is intended to illustrate, from a practical standpoint, the joint use of specific techniques set out in the first year of the biennium in real applications aimed at both predictive tasks (prediction of the occurrence of red tides, prediction of business failure, etc.) as classification tasks (identification of user profiles, identifying causes school failure , etc.).
Natural Language Processing.-
Natural Language Processing (NLP) is an essential part of artificial intelligence which investigates and makes computationally effective mechanisms to facilitate the interaction man / machine communication and enable a much more fluid and less rigid than formal languages. Any NLP system attempts to mimic human linguistic behavior; to do it, the system must be aware both on the structures of language, and also on general knowledge about the universe of discourse. Thus, a person who engages in a dialogue knows not only knows how to combine the words into a sentence, the meanings of them and how they affect the overall meaning of the sentence, but also has a general knowledge of the world that allows him to participate in the conversation. Several researchers into the MILE and GWAI groups works in the use of Natural Language Processing Techniques to solve real problems.
System Development Computer-Aided Diagnosis in Medicine.-
The work in the area of biomedical signal processing involves the development of algorithms and systems for detecting various diseases and maladies, such as sleep apnea and chronic obstructive pulmonary syndrome. Two primary objectives behind these algorithms is to find correlation between a limited set of patient monitoring signals which will act as early warning diagnostic detection systems.
For this, reserchers from the MILE Group have developed algorithms and software libraries for studying heart rate variability using techniques from Fourier and wavelet spectral analysis, non-linear dynamics analysis, and the application of neural networks.