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Teaching

I’m currently giving several subjects in the graduate school focused on the software design and data mining and I’m the diretor of a master of science in Data Mining Applied to Medicine. Finally, I’m the supervissor of several master thesis and one PhD thesis. Next, you can find more information about them.

[-] Master of Science in Data Mining Applieed to Medicine
[-] Software Engineering
[-] Parallel Software
[-] Mathematical Logic
[-] Knowledge-Based System
[-] Supervissor of Masther Thesis (TFC, PFC and TFM)
[-] Supervissor of PhD Students

Master of Science in Data Mining Applieed to Medicine [Top]

This master degree is directed to professionals and workers of medical centers, biotechnologists, doctors or staff of calculation centers of hospitals that fulfill the profile of investigator that needs to improve their knowledge to properly analyze medical data.

More specifically, the program is structured with the objective that the student:
1. Learns the acquisition process and storage of medical data.
2. Knows the legislation and the legal restrictions in medical data processing.
3. Acquires the research dynamic in the medical field and other experimental sciences.
4. Studies mechanisms of data analysis from the statistical and the data mining fields.
5. Is able to design problems of data mining.
6. Is able to understand the results of a methodological process of data analysis.
7. Is able to use software tools in order to make the knowledge extraction process automatic.

MDMM offers full training in KDD methodology

More information is available in the following link and also in the following PDF file.

Software Engineering [Top]

The goal of the subject is twofold. For one hand, it introduces student in one of the most relevant methodologies for the lightweight software development: Extreme Programming (XP). On the other hand, the subject introduces student in the development of .NET applications, and it shows the student how to apply XP in this software approach. More information in the following link.

Software methodologies help to fill the gap between clients and developers

Parallel Software [Top]

The goal of the subject is to train the student in the methodology of parallel software design, familiarizing him with the programming languages used in the present world of parallelism. The focus of the course is based on a practical approach to parallel design, to make it possible for the student to solve the real problems in the market. The design methodology leads us to the study of the algorithms design, the performance analysis, and the construction of programs. Existing tools are described and illustrated using real application examples. More information in the following link.

Thanks to my friend Alex to take perfect notes in class

Mathematical Logic [Top]

The goal of the subject is to introduce the theoretical foundations of the mathematical logic, making emphasis in the techniques of demonstration of theorems. Moreover, the main characteristics of the logical programming are studied in opposition to the imperative programming, studying parallelly the Prolog Language like example.
More information in the following link.

Knowledge-Based Systems [Top]

The goal of the subject is to provide to the student the theorical foundamentals and the practical skills in order to develep knowledge-based systems. At the end of the subject, the student should be able to identify the main issues to represent the knowledge of a domain and also to develop or adapt current engines for solving problems based on reasoning approaches. For example, would you like to develop a car driver for wining the TORCS competition? More information in the following link.

Do you want to be the next Fernando Alonso?

Supervissor of Master Thesis (TFC, PFC or TFM) [Top]

The goal of master thesis is to assess if a student has achieved a set of knowledge in terms of theorical and practical issues. Therefore, the role of the supervissor is to lead the student to achieve the last goal.

I lead master thesis focused on data mining and machine learning problems, which are often in the context of the medical domain. Next, I list some relevant master thesis.

Some examples of finished projects
[-] Clinical knowledge management for the melanoma cancer treatment (PFC, With Honours).
[-] Integration of the SOMCBR framework in the jcolibri2 framwork (PFC, 10).
[-] Development of a notification and prediction system for meteorological alerts for the ‘Servei Meteorlògic de Catalunya’ (PFC, 10).
[-] Adaptation of the retrieval and adaptation steps in the SOMCBR framework for allowing the use of heteronius data (TFC, With Honours).
[-] Parallelization of the retrieval phase of a CBR system based on a clustered case memory (TFC, 10).
[-] Web environment for storing and preprocessing datasets of machine learning problems (TFC, 9).
[-] Support tool for the clinical management of melanoma cancer treatment (TFM, With Honours).
[-] Developing and integration of the clinical records in a hospital sectorial solution (IS-H) in SAP. (TFC, 10)
[-] Visualization of multidimensional data (PFC, With Honours)
[-] Parallelization of clustering algorithms in the IBM PML toolbox (PFC, 10)

In progress
[-] Developing of a virtual poker player
[-] Discovery of consume patterns in a VopIP environment
[-] Developing AS2 servers
[-] Classification of different tissue types in ultrasound images of the liver

New proposals

[See GRSI homepage]

Please, send me an e-mail if you want to get more information about one of them, or if you want to participate in new amazing master thesis projects.

Supervissor of Phd Students [Top]

The goal of PhD is to assess if a student has the enough knwoledge and expertise in a topic in order to perform senior research. I lead PhD students in my researcher lines (see Research section).

[-] Álvaro García-Piquer: Organization of CBR case memory through a evolutionary multiobjective clustering technique.

Please, send me an e-mail if you want to get more information about what is a PhD and what are the skills that it can provide you.