Artificial Intelligence

COORDINATOR

Nebot Castells, Maria Angela

CONTACT

Doctoral Unit
ICT North Campus Management and Support Unit
Universitat Politècnica de Catalunya · BarcelonaTech
C. Jordi Girona, 1-3
Building B4 - 003
08034 Barcelona
doctorat.ia@upc.edu
Tel: 93413 78 36

https://artificialintelligence.phd.upc.edu/en/phd

As of today, the doctoral programme in Artificial Intelligence is the only doctoral programme in Catalonia focusing exclusively on artificial intelligence.

• The development of computing and its pervasiveness in all areas of society represent fundamental elements for understanding the socioeconomic progress of the second half of the 20th century. Particularly in recent years, artificial intelligence, due to its multidisciplinary nature, in addition to driving scientific and technological advancement in all fields of science, engineering and many other disciplines, has enabled the efficient and effective deciphering of scientific and social data, which has been critical to shaping our understanding of the world around us, living beings, mankind and society in general. Artificial intelligence is now present in nearly all domains of advanced society. Specifically, the financial, industrial, service, public administration, health care, communications, education and research and innovation sectors cannot be conceived without artificial intelligence playing a critical role in the systems that control them.

• The programme’s sphere of influence is Catalonia. As such it looks to attract Catalan students, though the Department also admits students from other parts of Spain and foreign countries. In Catalonia, and in particular, the metropolitan area surrounding Barcelona, industry and services have developed extensively. The financial, insurance, SME, consulting, education and research sectors here are key to the development of the country as a whole. And, as has already been mentioned, artificial intelligence is necessary in all of these fields. Consequently, educating and training well qualified AI researchers has undoubtedly become a strategic factor for growth.

• The doctoral programme in Artificial Intelligence was the first of its kind in Catalonia (1985), and for many years, it was the only one to exist. Since then, artificial intelligence has seen exponential growth and has been the starting point for many lines of research and products that have made their way to the general public, whether in American, Japan or Europe, where a significant number of Framework Programmes have been dedicated to financing projects that have artificial intelligence as a major element. In Catalonia in particular, the UPC’s doctoral programme in Artificial Intelligence has been vital to the creation of a thriving and growing scientific community. Some of the most important public and private research centres in Europe were founded by research graduates from our programme. Various spin-offs (e.g., ISOCO, 3SCALE, Intelligent Pharma and Sisltech) have been created as the result of one or more doctoral theses. Additionally, the Catalan Association for Artificial Intelligence (ACIA) is one of the most important in Europe.

• The doctoral programme in Artificial Intelligence stands out in Europe thanks to the research quality and output produced by its members, who participate in research projects financed with funds from the EU, Spain or other Spanish organisations and companies. Special mention should be given to the coordination of and participation in research projects involved with the Fifth, Sixth and Seventh Framework Programmes (Share-it, Laboranova, Contract, Agencities.RTD, Alive, Superhub, etc.). At the UPC there are three established groups that have been acclaimed by the Government of Catalonia and another by the university itself. These groups are directly related to the programme, ensuring that it remains dynamic and maintains the scientific standards needed to keep it in such high standing. Additionally, as has been previously mentioned, these groups are very active when it comes to obtaining financing through EU calls, which ensures they have continuous contact with national and European businesses and a high level of internationalisation. Furthermore, other groups at the UPC regularly send students to study in the programme. The same is true with students from other universities, such as the URV and the CSIC’s Artificial Intelligence Research Institute.

• The UPC’s doctoral programme in Artificial Intelligence was given the Quality Award in 2003 (MCD2003-00129), which was renewed in the following years: 2004, 2005, 2006, 2007, 2008 and 2009. Among other recent accolades, it is worth noting that some of the programme’s theses have received awards:

• Two recent doctoral theses presented in the programme were given the Artificial Intelligence Dissertation Award (in 2010 and 2003). This is the only programme in all of Spain that has been given such distinctions. In Europe, there are two other examples: the doctoral programmes in artificial intelligence at the École Polytechnique Fédérale de Lausanne (EPFL) and the J. Stefan Institute in Ljubljana.

• Furthermore, some of the programme’s distinguished former students include five ECCAI Fellows. Ours is one of the programmes that has produced the most Fellows in Europe. They are: Prof. Carlos Sierra (IIIA-CSIC), Enric Plaza (1) (IIIA-CSIC), Vicenç Torra (IIIA-CSIC), Pedro Messeguer (IIIA-CSIC) and Lluís Godó (IIIA-CSIC)

• Another of the programme’s theses was given the Best Thesis Award 2009 by the European Association for Machine Translation.

• Another was given the Joan Lluís Vives Prize 2003, the Barcelona City Research Prize 2003 and the Extraordinary Doctorate Prize by the UPC for the 2003-2004 academic year.

• Another was given the Chihuahua Research Prize 2002, by the state of Chihuahua, Mexico.

The doctoral programme in Artificial Intelligence falls into the field of information and communication technology (ICT), as does the research work carried out in the programme, and this represents one of the primary areas of research at the UPC. The education and training provided in the programme is intended to respond to one of the challenges posed by Catalonia’s 2010-2013 Research and Innovation Plan: Excellent and cutting-edge research and technology (see section 8, page 13). It is also intended to respond to the objectives of area 1—production of scientific and technological knowledge and competencies—of the National Scientific Research, Development and Technological Innovation Plan 2008-2011 (PN I+D+I).
From a technical and scientific point of view, some of the programme’s lines of research contribute to tackling other challenges included in Catalonia’s Research and Innovation Plan:
• Efficient flows of people and goods (sustainable mobility) and of information. The programme covers lines dealing with flows of information related to the accessibility and management of information, particularly in the contexts of algorithmics and programming.
• The new service society with consumer “serviproducts”. The programme incorporates lines of research related to the study and analysis of the structural and algorithmic aspects of social networks and heterogeneous computing networks (sensors, robots, mobile phones, etc.) that could play a crucial role in the development of new methodologies in this field. It also deals with the development of computer graphic technologies and those related to virtual and augmented reality.
• Healthcare and risk prevention. The programme incorporates lines of research related to biocomputing and medical visualisation.
With regard to the PN I+D+I and in line with the objectives of Strategic Action 4, the programme’s lines of research include the following: Telecommunications and the information society, with potential contributions to the following sub-lines:
1. Computing technologies
b) Advanced multi-modal interfaces.
c) Distributed and embedded systems.
d) Software engineering and information management.
e) Intelligent systems.
f) Free and open-source software.
8. Sector-specific applications, services and contents
a) Businesses and particularly SMEs. E-business, in its broadest sense.
b) Healthcare, social welfare and social inclusion, including broadband e-inclusion.
c) Security, in its broadest sense.
d) Transport, in its broadest sense.
Regarding the European Community’s Seventh Framework Programme, from topic 3, Information and Communication Technologies, of the 2011-2012 Work Programme, the doctoral programme’s lines of research pertain to the planning, design and analysis of some of the developmental components of the challenges posed:
• Challenge 1: Pervasive and trusted network and service infrastructures
- tools and platforms for novel Internet application development
- key technological developments in networking, digital media and service infrastructures.
• Challenge 3: alternative paths to components and systems
- multicore computing systems
- embedded systems
- monitoring and control
- cooperating complex systems
• Challenge 4: technologies for digital content and languages
- online access and use of content and services
- reliability of retrieval and use of digital resources
- scaling up data analysis to keep pace with extremely large data volumes
• Challenge 5: ICT for health, ageing well, inclusion and governance. ICT for disease prediction, early diagnosis, prevention, minimally invasive treatment
Artificial intelligence is undoubtedly at the core of the technological and scientific development of other emblematic concepts and challenges, including “smart cities”, “greener technologies” and “living labs”.


General information

Access profile

There cannot be a specific profile for applicants to a programme in a discipline that is so horizontal, interdisciplinary and diverse as artificial intelligence. Areas of research and application range from biology and medicine to computational linguistics, artificial vision and robotic intelligence, to name a few of the extremes.

However, to provide an identifiable base of basic knowledge, applicants’ prior education and training should preferably have provided skills and abilities in research equivalent to those provided by the master’s degree programme in Artificial Intelligence, currently offered by the UPC, or to those provided by specialisations in Advanced Computation and Computer Graphics and Virtual Reality in the master’s degree programme in Innovation and Research in Informatics, which stems from the restructuring of master’s-level studies in ICT at the UPC.

The master’s degree programme in Artificial Intelligence also accepts students from a wide range of other scientific disciplines.

Output profile

Doctoral candidates who complete a doctoral degree will have acquired the following competencies, which are needed to carry out quality research (Royal Decree 99/2011, of 28 January, which regulates official doctoral studies):

a) A systematic understanding of the field of study and a mastery of the research skills and methods related to the field.
b) An ability to conceive, design or create, put into practice and adopt a substantial process of research or creation.
c) An ability to contribute to pushing back the frontiers of knowledge through original research.
d) A capacity for critical analysis and an ability to assess and summarise new and complex ideas.
e) An ability to communicate with the academic and scientific community and with society in general as regards their fields of knowledge in the manner and languages that are typical of the international scientific community to which they belong.
f) An ability to foster scientific, technological, social, artistic and cultural progress in academic and professional contexts within a knowledge-based society.

The award of a doctoral degree must equip the graduate for work in a variety of settings, especially those requiring creativity and innovation. Doctoral graduates must have at least acquired the personal skills needed to:

a) Develop in contexts in which there is little specific information.
b) Find the key questions that must be answered to solve a complex problem.
c) Design, create, develop and undertake original, innovative projects in their field.
d) Work as part of a team and independently in an international or multidisciplinary context.
e) Integrate knowledge, deal with complexity and make judgements with limited information.
f) Offer criticism on and intellectually defend solutions.

Finally, with respect to competencies, doctoral students must:
a) have acquired advanced knowledge at the frontier of their discipline and demonstrated, in the context of internationally recognised scientific research, a deep, detailed and well-grounded understanding of theoretical and practical issues and scientific methodology in one or more research fields;
b) have made an original and significant contribution to scientific research in their field of expertise that has been recognised as such by the international scientific community;
c) have demonstrated that they are capable of designing a research project that serves as a framework for carrying out a critical analysis and assessment of imprecise situations, in which they are able to apply their contributions, expertise and working method to synthesise new and complex ideas that yield a deeper knowledge of the research context in which they work;
d) have developed sufficient autonomy to set up, manage and lead innovative research teams and projects and scientific collaborations (both national and international) within their subject area, in multidisciplinary contexts and, where appropriate, with a substantial element of knowledge transfer;
e) have demonstrated that they are able to carry out their research activity in a socially responsible manner and with scientific integrity;
f) have demonstrated, within their specific scientific context, that they are able to make cultural, social or technological advances and promote innovation in all areas within a knowledge-based society;
g) have demonstrated that they are able to participate in scientific discussions at the international level in their field of expertise and disseminate the results of their research activity to audiences of all kinds.

Number of places

10

Duration of studies and dedication regime

Duration
The maximum period of study for full-time doctoral studies is four years, counted from the date of first enrolment in the relevant programme until the date on which the doctoral thesis is deposited. The academic committee of the doctoral programme may authorise a doctoral candidate to pursue doctoral studies on a part-time basis. In this case, the maximum period of study is seven years from the date of first enrolment in the programme until the date on which the doctoral thesis is deposited. To calculate these periods, the date of deposit is considered to be the date on which the thesis is made publicly available for review.

If a doctoral candidate has a degree of disability equal to or greater than 33%, the maximum period of study is six years for full-time students and nine years for part-time students.

For full-time doctoral candidates, the minimum period of study is two years, counted from the date of an applicant's admission to the programme until the date on which the doctoral thesis is deposited; for part-time doctoral candidates it is four years.

When there are justified grounds for doing so, and the thesis supervisor and academic tutor have given their authorisation, doctoral candidates may request that the academic committee of their doctoral programme exempt them from the requirement to complete this minimum period of study.

Temporary disability leave and leave for the birth of a child, adoption or fostering for the purposes of adoption, temporary foster care, risk during pregnancy or infant feeding, gender violence and any other situation provided for in current regulations do not count towards these periods. Students who find themselves in any of these circumstances must notify the academic committee of the doctoral programme, which must inform the Doctoral School.

Doctoral candidates may request periods of temporary withdrawal from the programme for up to a total of two years. Requests must be justified and addressed to the academic committee responsible for the programme, which will decide whether or not to grant the candidate's request.

Extension of studies
If a doctoral candidate has not applied to deposit their thesis before the expiry of the deadlines specified in the previous section, the academic committee of the doctoral programme may, at the request of the doctoral candidate, authorise an extension of this deadline of one year under the conditions specified for the doctoral programme in question.

Dismissal from the doctoral programme
A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

  • The doctoral candidate submitting a justified application to withdraw from the programme.
  • The doctoral candidate not having completed their annual enrolment or applied for a temporary interruption.
  • The doctoral candidate not having formalised annual enrolment on the day after the end of the authorisation to temporarily interrupt or withdraw from the programme.
  • The doctoral candidate receiving a negative reassessment after the deadline set by the academic committee of the doctoral programme to remedy the deficiencies that led to a previous negative assessment.
  • The doctoral candidate having been the subject of disciplinary proceedings leading to their suspension or permanent exclusion from the UPC.
  • A refusal to authorise the extensions applied for, in accordance with the provisions of Section 3.3 of these regulations.
  • The doctoral candidate not having submitted the research plan in the period established in Section 8.2 of these regulations.
  • The maximum period of study for the doctoral degree having ended, in accordance with the provisions of Section 3.4 of these regulations.

Dismissal from the programme means that the doctoral candidate cannot continue studying at the UPC and that their academic record will be closed. This notwithstanding, they may apply to the academic committee of the programme for readmission, and the committee must reevaluate the candidate in accordance with the criteria established in the regulations.

A doctoral candidate who has been dismissed due to having exceeded the time limit for completing doctoral studies or due to an unsatisfactory assessment may not be Academic Regulations for Doctoral Studies Universitat Politècnica de Catalunya Page 17 of 33 admitted to the same doctoral programme until at least two years have elapsed from the date of dismissal, as provided for in sections 3.4 and 9.2 of these regulations.

Legal framework

Organization

COORDINATOR:
ACADEMIC COMMISSION OF THE PROGRAM:
STRUCTURAL UNITS:
  • Department of Computer Science (PROMOTORA)
SPECIFIC URL OF THE DOCTORAL PROGRAM:
https://artificialintelligence.phd.upc.edu/en/phd

CONTACT:
Doctoral Unit
ICT North Campus Management and Support Unit
Universitat Politècnica de Catalunya · BarcelonaTech
C. Jordi Girona, 1-3
Building B4 - 003
08034 Barcelona
doctorat.ia@upc.edu
Tel: 93413 78 36

Agreements with other institutions


Access, admission and registration

Access profile

There cannot be a specific profile for applicants to a programme in a discipline that is so horizontal, interdisciplinary and diverse as artificial intelligence. Areas of research and application range from biology and medicine to computational linguistics, artificial vision and robotic intelligence, to name a few of the extremes.

However, to provide an identifiable base of basic knowledge, applicants’ prior education and training should preferably have provided skills and abilities in research equivalent to those provided by the master’s degree programme in Artificial Intelligence, currently offered by the UPC, or to those provided by specialisations in Advanced Computation and Computer Graphics and Virtual Reality in the master’s degree programme in Innovation and Research in Informatics, which stems from the restructuring of master’s-level studies in ICT at the UPC.

The master’s degree programme in Artificial Intelligence also accepts students from a wide range of other scientific disciplines.

Access requirements

As a rule, applicants must hold a Spanish bachelor's degree or equivalent and a Spanish master's degree or equivalent, provided they have completed a minimum of 300 ECTS credits on the two degrees (Royal Decree 43/2015, of 2 February).

Applicants who meet one or more of the following conditions are also eligible for admission:

a) Holders of official Spanish degrees or equivalent Spanish qualifications, provided they have passed 300 ECTS credits in total and they can prove they have reached Level 3 in the Spanish Qualifications Framework for Higher Education.
b) Holders of degrees awarded in foreign education systems in the European Higher Education Area (EHEA), which do not require homologation, who can prove that they have reached Level 7 in the European Qualifications Framework, provided the degree makes the holder eligible for admission to doctoral studies in the country in which it was awarded.
c) Holders of degrees awarded in a country that does not belong to the EHEA, which do not require homologation, on the condition that the University is able to verify that the degree is of a level equivalent to that of official university master's degrees in Spain and that it makes the holder eligible for admission to doctoral studies in the country in which it was awarded.
d) Holders of another doctoral degree.
e) Holders of an official university qualification who, having been awarded a post as a trainee in the entrance examination for specialised medical training, have successfully completed at least two years of training leading to an official degree in a health sciences specialisation.

Note 1: Regulations for access to doctoral studies for individuals with degrees in bachelor's, engineering, or architecture under the system prior to the implementation of the EHEA (CG 47/02 2014).

Note 2: Agreement number 64/2014 of the Governing Council approving the procedure and criteria for assessing the academic requirements for admission to doctoral studies with non-homologated foreign degrees (CG 25/03 2014).

Legal framework

Admission criteria and merits assessment

Aspiring doctors in Artificial Intelligence should have academic (master’s) and professional backgrounds that show that they have the academic and intellectual capacities and the consistency needed to ensure that they can successfully complete their studies in a timely fashion.

The programme will assess candidates on the following criteria:

 • Academic transcripts for all university degree programmes taken.
 • Publications (if applicable).
 • Research experience (if applicable).
 • CV.
 • Appropriateness of research interests with the programmes lines of research and the applicant’s background.
 • Other merits.

All of those who are admitted to the doctoral programme will be expected to be able to understand technical texts written in English and easily follow courses and conferences in English. Candidates will have to demonstrate that they possess a knowledge of the English language equal to a B1 level as per the Common European Framework of Reference for Languages, both spoken and written, in the timeframes and manners determined by the Academic Committee.

Weighting of criteria:
The Academic Committee of the doctoral programme will be in charge of the process of selecting and admitting candidates. This selection process will be based on a scale that will give priority to the following aspects:

- applicants’ academic transcripts (60%)
- verifiable knowledge of the English language (20%).
- previous experience (20%).

Training complements

The academic committee for the programme may require that doctoral students pass specific bridging courses. In this case, the Committee will monitor the bridging courses and set up appropriate criteria to limit their length.

The courses could involve training in research or transversal education, but in no case will candidates be required to enrol in 60 or more ECTS credits.

Depending on the activities completed by the candidates, the programme’s Academic Committee may propose measures, in addition to those established by current regulations, that would disassociate candidates who do not meet the established requisites.

If necessary, the bridging courses required will be determined by the academic tutors following the recommendations given to each student during the admission process. Recommended courses will be those offered through the joint master’s degree programme in Artificial Intelligence.

Core subjects:

Based on their previous studies, candidates with non-scientific backgrounds will have to pass these courses, in addition to one subject from the following blocks, depending on their chosen line of research.

• Computational Intelligence (CI)
• Computational Vision (CV)
• Intelligent Data Analysis Applications in Business
• Introduction to MultiAgent Systems (IMAS)
• Introduction to Machine Learning (IML)
• Introduction to Natural Language Processing (INLP)
• Planning and Approximate Reasoning (PAR)

Subjects on more specific topics:

For candidates with scientific backgrounds, 1 or 2 blocks of subjects, depending on their chosen line of research.

MultiAgent Systems:
• Multi-Agent Systems Design (MASD)
• Normative and Dynamic Virtual Worlds (NDVW)
• Self-Organising Agent Systems (SOAS)

Human-Computer Interaction:
• Advanced Natural Language Processing (ANLP)
• Cognitive Interaction with Robots (CIR)
• Human-Computer Interaction (HCI)

Advanced Computational Intelligence:
• Advanced Topics in Computational Intelligence (ATCI)
• Complex Networks (CN)
• Intelligent Data Analysis and Data Mining (IDADM)

Knowledge Engineering and Machine Learning:
• Advanced Machine Learning Techniques (AMLT)
• Intelligent Decision Support Systems (IDSS)
• Knowledge Representation and Engineering (KRE)
• Multi-Criteria Decision Support Systems (MCDSS)

Modelling, Reasoning and Problem Solving:
• Constraint Processing and Programming (CPP)
• Logics for Artificial Intelligence (LAI)
• Minds, Brains and Machines (MBM)
• Probabilistic Graphical Models (PGM)

Vision, Perception and Robotics:
• Advanced Artificial Vision (AAV)
• Cooperative Robotics (CR)
• Object Recognition (OR)

Enrolment period for new doctoral students

Students enrolling in the doctoral programme for the first time must do so by the deadline specified in the admission decision.
Unless otherwise expressly indicated, enrolments corresponding to admission decisions issued from the second half of April on must be completed within the ordinary enrolment period for the current academic year.

More information at the registration section for new doctoral students

Enrolment period

Ordinary period for second and successive enrolments: first half of October.

More information at the general registration section

Monitoring and evaluation of the doctoral student

Procedure for the preparation and defense of the research plan

Doctoral candidates must submit a research plan, which will be included in their doctoral student activity report, before the end of the first year. The plan may be improved over the course of the doctoral degree. It must be endorsed by the tutor and the supervisor, and it must include the method that is to be followed and the aims of the research.

At least one of these annual assessments will include a public presentation and defence of the research plan and work done before a committee composed of three doctoral degree holders, which will be conducted in the manner determined by each academic committee. The examination committee awards a Pass or Fail mark. A Pass mark is a prerequisite for continuing on the doctoral programme. Doctoral candidates awarded a Fail mark must submit a new research plan for assessment by the academic committee of the doctoral programme within six months.

The committee assesses the research plan every year, in addition to all of the other activities in the doctoral student activity report. Doctoral candidates who are awarded two consecutive Fail marks for the research plan will be obliged to definitely withdraw from the programme.

If they change the subject of their thesis, they must submit a new research plan.

Formation activities

1. Tutorials (meetings with the supervisor), approximately 288 hours (the exact number and frequency will be defined by the supervisor), mandatory.

2. Artificial Intelligence Seminar, approximately 30 hours (depending on participants’ availability), optional.

3. Theoretical-Scientific Seminar, approximately 30 hours (depending on participants’ availability), optional.

4. Intensive courses, approximately 30 hours (depending on professors’ availability), optional.

5. International scientific meetings (conferences, workshops, schools, etc.), approximately 24 hours, optional.

Procedure for assignment of tutor and thesis director

The academic committee of the doctoral programme assigns a thesis supervisor to each doctoral candidate when they are admitted or enrol for the first time, taking account of the thesis supervision commitment referred to in the admission decision.

The thesis supervisor will ensure that training activities carried out by the doctoral candidate are coherent and suitable, and that the topic of the candidate’s doctoral thesis will have an impact and make a novel contribution to knowledge in the relevant field. The thesis supervisor will also guide the doctoral candidate in planning the thesis and, if necessary, tailoring it to any other projects or activities undertaken. The thesis supervisor will generally be a UPC professor or researcher who holds a doctoral degree and has documented research experience. This includes PhD-holding staff at associated schools (as determined by the Governing Council) and UPC-affiliated research institutes (in accordance with corresponding collaboration and affiliation agreements). When thesis supervisors are UPC staff members, they also act as the doctoral candidate’s tutor.

PhD holders who do not meet these criteria (as a result of their contractual relationship or the nature of the institution to which they are attached) must be approved by the UPC Doctoral School's Standing Committee in order to participate in a doctoral programme as researchers with documented research experience.

The academic committee of the doctoral programme may approve the appointment of a PhD-holding expert who is not a UPC staff member as a candidate’s thesis supervisor. In such cases, the prior authorisation of the UPC Doctoral School's Standing Committee is required. A UPC staff member who holds a doctoral degree and has documented research experience must also be proposed to act as a co-supervisor, or as the doctoral candidate’s tutor if one has not been assigned.

A thesis supervisor may step down from this role if there are justified reasons (recognised as valid by the committee) for doing so. If this occurs, the academic committee of the doctoral programme will assign the doctoral candidate a new thesis supervisor.

Provided there are justified reasons for doing so, and after hearing any relevant input from the doctoral candidate, the academic committee of the doctoral programme may assign a new thesis supervisor at any time during the period of doctoral study.

If there are academic reasons for doing so (an interdisciplinary topic, joint or international programmes, etc.) and the academic committee of the programme gives its approval, an additional thesis supervisor may be assigned. Supervisors and co-supervisors have the same responsibilities and academic recognition.

The maximum number of supervisors of a doctoral thesis is two: a supervisor and a co-supervisor.

For theses carried out under a cotutelle agreement or as part of an Industrial Doctorate, if necessary and if the agreement foresees it this maximum number of supervisors may not apply. This notwithstanding, the maximum number of supervisors belonging to the UPC is two.

More information at the PhD theses section

Permanence

The maximum period of study for full-time doctoral studies is four years, counted from the date of first enrolment in the relevant programme until the date on which the doctoral thesis is deposited. The academic committee of the doctoral programme may authorise a doctoral candidate to pursue doctoral studies on a part-time basis. In this case, the maximum period of study is seven years from the date of first enrolment in the programme until the date on which the doctoral thesis is deposited. To calculate these periods, the date of deposit is considered to be the date on which the thesis is made publicly available for review.

If a doctoral candidate has a degree of disability equal to or greater than 33%, the maximum period of study is six years for full-time students and nine years for part-time students.

If a doctoral candidate has not applied to deposit their thesis before the expiry of the deadlines specified in the previous section, the academic committee of the doctoral programme may, at the request of the doctoral candidate, authorise an extension of this deadline of one year under the conditions specified for the doctoral programme in question.

Dismissal from the doctoral programme
A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

  • The doctoral candidate submitting a justified application to withdraw from the programme.
  • The doctoral candidate not having completed their annual enrolment or applied for a temporary interruption.
  • The doctoral candidate not having formalised annual enrolment on the day after the end of the authorisation to temporarily interrupt or withdraw from the programme.
  • The doctoral candidate receiving a negative reassessment after the deadline set by the academic committee of the doctoral programme to remedy the deficiencies that led to a previous negative assessment.
  • The doctoral candidate having been the subject of disciplinary proceedings leading to their suspension or permanent exclusion from the UPC.
  • A refusal to authorise the extensions applied for, in accordance with the provisions of Section 3.3 of these regulations.
  • The doctoral candidate not having submitted the research plan in the period established in Section 8.2 of these regulations.
  • The maximum period of study for the doctoral degree having ended, in accordance with the provisions of Section 3.4 of these regulations.

Dismissal from the programme means that the doctoral candidate cannot continue studying at the UPC and that their academic record will be closed. This notwithstanding, they may apply to the academic committee of the programme for readmission, and the committee must reevaluate the candidate in accordance with the criteria established in the regulations.

A doctoral candidate who has been dismissed due to having exceeded the time limit for completing doctoral studies or due to an unsatisfactory assessment may not be Academic Regulations for Doctoral Studies Universitat Politècnica de Catalunya Page 17 of 33 admitted to the same doctoral programme until at least two years have elapsed from the date of dismissal, as provided for in sections 3.4 and 9.2 of these regulations.

Legal framework

Learning resources

Space for grant holders, study rooms, computing equipment and programmes provided by the Computer Science Department, additional resources provided by research groups participating in the programme.

The Academic Committee of the doctoral programme will encourage candidates to participate in mobility programmes on the regional, country, and European levels and in research groups working on projects at the international level, whether via integrated actions or on European projects. Such participation has been and will continue to be one of the major points of internationalisation in the programme.

Doctoral Theses

List of authorized thesis for defense

Last update: 25/05/2024 04:45:20.

List of lodged theses

Last update: 25/05/2024 04:30:28.

List of defended theses by year

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  • MONTES GOMEZ, MARIA DE LAS NIEVES: Value Engineering for Autonomous Agents
    Author: MONTES GOMEZ, MARIA DE LAS NIEVES
    Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
    Department: Department of Computer Science (CS)
    Mode: Article-based thesis
    Reading date: 01/02/2024
    Thesis director: SIERRA GARCIA, CARLOS | OSMAN, NARDINE

    Committee:
         PRESIDENT: CORTÉS GARCÍA, CLAUDIO ULISES
         SECRETARI: LOPEZ SANCHEZ, MAITE
         VOCAL: SEVERINO DE ALMEIDA E PAIVA, ANA MARIA
    Thesis abstract: The topic of this thesis is the engineering of values for autonomous agents. This is realised through the formulation, design and implementation of new functionalities for autonomous agents that enable reasoning in terms of values. In particular, we argue for the role of prescriptive norms as value-promoting mechanisms. Hence, value-driven agents should be able to autonomously determine which regulations (such as obligations, permissions or prohibitions) make the Multiagent System they inhabit better promote some values of interest. We lay the foundations of our work on Schwartz¿s Theory of Basic Human Values to establish a consequential connection between values and norms, considering that norms are aligned with respect to values if the outcomes they incentivise satisfy the goals that capture the meaning of values in a particular context. Another feature of Schwartz¿s theory that has been previously overlooked in the literature is the strong social dimension of values. That is, agents should be able to reason not just in terms of their own, but also of the values of others in their community. This points to Theory of Mind (i.e. the cognitive ability to perceive, interpret and reason about others in terms of their mental states) as an outstanding component of value-based reasoning.This thesis is structured around three main contributions (published in journal papers) plus their integration. The first contribution establishes the normvalue relationship as a consequential one in nature, and proposes a methodology for the automated synthesis and analysis of optimally value-aligned normative systems. The second contribution tackles the limitations of the first, and defines the Action Situation Language to systematically express a wide range of rules that may be implemented in a Multiagent System. This language is complemented by a game engine that automatically interprets interaction descriptions and builds their semantics as Extensive Form Games, which are later analysed with standard game-theoretical tools. This leads to a distribution over game outcomes, which are evaluated in terms of their desirability with respect to values. The third contribution introduces Theory of Mind-related functionalities into an existing Belief-Desire-Intention agent architecture, and combines them with abductive reasoning capabilities.The three contributions are integrated in a novel functionality that enables agents to reason about prescriptive norms in terms of dynamic values. This means that an autonomous agent can, at runtime, switch its value perspective to the one it estimates that another agent has. Such perspective-dependent value-based normative reasoning functionality, with its inherent social orientation, constitutes a novel contribution to the community of values for autonomous agents and paves the way for possible applications such as value-based negotiation over normative systems. In summary, value engineering is a principled and systematic approach to computational ethics, which provides an innovative tool set for integrating ethical values into the design of autonomous agents.

  • ROTKEVICH, MIKHAIL: Revealing the hidden language of DNA
    Author: ROTKEVICH, MIKHAIL
    Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
    Department: Department of Computer Science (CS)
    Mode: Normal
    Reading date: 19/03/2024
    Thesis director: PRZULJ, NATASA

    Committee:
         PRESIDENT: SKUPIN, ALEXANDER
         SECRETARI: VELLIDO ALCACENA, ALFREDO
         VOCAL: GUIGO SERRA, RODERIC
    Thesis abstract: Genomics has revolutionized in recent years due to the rapid advancements in high-throughput sequencing technologies, leading to an explosion of genomic data. This has opened up new opportunities for utilizing natural language processing (NLP) techniques to analyze and extract knowledge from genomic data. However, applying NLP techniques in genomics presents unique challenges due to the differences in genetic data's underlying structure and complexity.State-of-art biological embedding algorithms, such as DNA2VEC, split biological sequences into overlapping sub-sequences of length k, called k-mers, and learn a k-mer-based embedding space. By representing k-mers as continuous vectors, a strong correlation has been observed between the cosine similarity of these embeddings and the global sequence alignment score. This correlation suggests that the k-mer embeddings effectively capture sequence similarities. In other words, if two genes or proteins are embedded closely in the embedding space, they will likely exhibit high sequence similarity.We proposed new embedding methods to go beyond the sequence similarity: untangle 1 (UNT1) and untangle 2 (UNT2). By changing the calculation of the co-occurrences of k-mers in the contextual window, we significantly reduced the correlation to sequence similarity. While capturing fewer semantically similar GO terms, we showed that the novel methods UNT1 and UNT2 provide a broader representation of functional relationships than DNA2VEC.In addition to sequence data, the availability of diverse omics data has witnessed a remarkable surge, with the recognition of its potential to provide complementary insights. In our research, we depart from the conventional use of Singular Value Decomposition (SVD) to represent sequences in a low-dimensional space. Instead, we employ Non-negative Matrix Tri-Factorization (NMTF) to build a directly interpretable biological sequence embedding method. While Singular Value Decomposition (SVD) has successfully produced high-quality embeddings, our choice of NMTF aligns with the goals of explainable AI (XAI) and the need to understand the biological implications of the generated embeddings. NMTF serves as a potent instrument for data fusion, enabling the integration of information from various sources to achieve a deeper knowledge of complex biological systems. By utilizing NMTF, we aim to provide a more comprehensive understanding of the relationships between biological entities, such as k-mer, coding or non-coding regions, and their functional characteristics.We developed a versatile approach for annotating k-mers with genes, which allowed us to investigate the inheritance of annotations across different k-mer lengths. Specifically, we mapped k-mers to genes and vice-versa based on their over-representation in the sequences of the genes. Our study showed that the k-mer clusters are significantly enriched in GO annotations, indicating that the embeddings of k-mers capture functional genome organization.We showed that the same embedding models based on k-mers of DNA not only capture a functional structure of genes, but also effectively distinguish non-coding regions of DNA. We analyzed the non-coding regions of the yeast genome and compared the performance of the models DNA2VEC, UNT1, and UNT2. Our findings suggest that the optimal length of k-mers to classify ncRNAs is shorter than 7. This observation is fundamental since the feasibility of mostly all k-mer-based methods is highly dependent on the volume of the vocabulary increasing exponentially with the k-mer's length.Furthermore, our findings indicate that models utilizing k-mers of length 6 and larger outperform models based on shorter subsequences when predicting chromatin interactions. By emphasizing the importance of longer k-mers, our study provides valuable insights into the potential of utilizing extended sequence motifs to advance our understanding of the structural organization of the genome.

  • XENOS, ALEXANDROS: Towards a linearly organized embedding space of biological networks
    Author: XENOS, ALEXANDROS
    Thesis link: http://hdl.handle.net/10803/690743
    Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
    Department: Department of Computer Science (CS)
    Mode: Normal
    Reading date: 02/02/2024
    Thesis director: PRZULJ, NATASA

    Committee:
         PRESIDENT: BORGWARDT, KARSTEN
         SECRETARI: VELLIDO ALCACENA, ALFREDO
         VOCAL: HIGHAM, DESMOND JOHN
    Thesis abstract: The recent technological advances in high-throughput sequencing have yielded vast amounts of large-scale biological omics data that describe different aspects of cellular functioning. These omics data are typically modelled and analyzed as networks. Due to the high dimensionality of biological networks, embeddings are a cornerstone in the analysis of such complex networks. Embedding biological networks is challenging, as it involves capturing both topological (similar wiring patterns) and neighborhood-based similarity of the nodes. However, current network embedding algorithms do not preserve both types of similarity, which limits the information preserved in the embedding space. Moreover, the existing methods for analyzing the embedding space of molecular networks use the vectors of the biological entities as the input for computationally intensive ML models that aid downstream analysis tasks. In contrast, in the field of NLP, they mine the word embedding space directly by doing simple linear operations between the word embedding vectors. In this thesis, following the NLP paradigm, we mine biological knowledge directly from the embedding space, and we identify the properties of a space that make it suitable for linear operations.In network biology, Non-Negative Matrix Tri Factorization (NMTF) is extensively used to embed networks in a low-dimensional space because it is an explainable AI method that also enables the joint representation of different networks in a shared space. We demonstrate the power of the NMTF-based data integration in the context of COVID-19 by applying two integration frameworks to identify COVID-19 related genes and prioritize drugs for repurposing targeting their gene products. Our newly identified genes could not have been identified with either network-medicine or differential expression based approaches that rely on a single type of omic data.Then, to extract new biological knowledge based on linear operations, we introduce two NLP inspired network representations: the Positive Pointwise Mutual Information (PPMI) matrix and the Graphlet Degree Vector (GDV) PPMI matrix. The PPMI matrix captures the neighborhood-based similarities of the nodes based on random walks between adjacent nodes, while the GDV PPMI matrix, the topological ones by using random walks between similarly wired nodes, independent of being adjacent. As a showcase, we represent the nodes of the human PPI network with our GDV PPMI and PPMI matrix and generate the embedding spaces by factorizing these matrices with NMTF. We show that genes embedded close in these spaces have similar biological functions, so we can extract new biomedical knowledge directly by doing linear operations on their embedded vectors. We exploit this property to predict genes participating in protein complexes and to identify cancer-related genes based on the cosine similarities between the vector representations of the genes.We also go beyond embeddings that preserve one type of similarity by introducing novel random-walk based network embeddings that incorporate the graphlets (small, connected and induced subgraphs) into DeepWalk and LINE methods. We use the graphlets that leverage both topological and neighbourhood-based similarity as the context for the random walks. In a graphlet-based random walk, a node can visit any other nodes that simultaneously participate in the given graphlet. We show that in the graphlet-based representations of the networks, more adjacent nodes have the same label (i.e., the nodes are grouped in a more homophilic way) than in the standard random walk representations. Then we factorize these matrices with NMTF and show that the more homophilic the network representation, the more functionally organized is the corresponding embedding space, and thus the downstream analysis tasks are better. Our new graphlet-based methodologies embed networks in linear spaces, alleviating the need for computationally expensive ML methods.

Last update: 25/05/2024 05:00:49.

Theses related publications

AUTHOR:DE CASTRO CROS, MARTÍ
Title:DA&AI Supporting tools for gas turbine¿s efficiency improvement: maintenance, operation modes and performance enhancement
Reading date:18/12/2023
Director:ANGULO BAHON, CECILIO
Co-director:VELASCO GARCIA, MANUEL
Mention:No mention
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Effects of gamification in BCI functional rehabilitation
De Castro, M.; Sebastian, M.; Rodriguez, J.; Opisso, E.; Ochoa, M.; Ortner, R.; Guger, C.; Tost, D.
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Publication date: 21/08/2020
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Condition assessment of industrial gas turbine compressor using a drift soft sensor based in autoencoder
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Publication date: 12/04/2021
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Machine-learning-based condition assessment of gas turbine: a review
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Publication date: 21/01/2023
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AUTHOR:ARIAS DUART, ANNA
Title:Assessing biases through mosaic attributions
Reading date:11/12/2023
Director:CORTÉS GARCÍA, CLAUDIO ULISES
Co-director:GARCÍA GASULLA, DARIO
Mention:Menció Doctorat Internacional + Industrial Doctorate Mention (Generalitat)
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The MAMe dataset: On the relevance of high resolution and variable shape image properties
Parés, F.; Arias, A.; García, D.; Campo, G.; Viladrich, N.; Ayguade, E.; Labarta, J.
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Publication date: 08/2022
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Assessing biases through visual contexts
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Electronics (Switzerland), ISSN: 2079-9292 (JCR Impact Factor-2021: 2.69; Quartil: Q3)
Publication date: 07/2023
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Focus! Rating XAI methods and finding biases
31st IEEE International Conference on Fuzzy Systems
Presentation date: 2022
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Focus and bias: will it blend?
24th International Conference of the Catalan Association for Artificial Intelligence
Presentation date: 2022
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A confusion matrix for evaluating feature attribution methods
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
Presentation date: 19/06/2023
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AUTHOR:ZAMBRANA SEGUI, MARIA DEL CARMEN
Title:New data integration methods for drug re-purposing by mining heterogeneous omics data
Reading date:21/11/2023
Tutor/a:LARROSA BONDIA, FRANCISCO JAVIER
Director:PRZULJ, NATASA
Mention:No mention
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Network neighbors of viral targets and differentially expressed genes in COVID-19 are drug target candidates
Zambrana, C.; Xenos, A.; Böttcher, R.; Malod-Dognin , N.; Pržulj, N.
Scientific reports, ISSN: 2045-2322 (JCR Impact Factor-2021: 4.996; Quartil: Q2)
Publication date: 23/09/2021
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Integrated data analysis uncovers new COVID-19 related genes and potential drug re-purposing candidates
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Title: A methodology for the automation of building intelligent process control systems
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Co-director:CUGUERO ESCOFET, MIQUEL ANGEL
Mention:Industrial Doctorate Mention (Generalitat)
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Application of CBR for intelligent process control of a WWTP
Pascual, J.; Cugeró-Escofet, M.A.; Sànchez-Marrè, M.; Aguiló, P.
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Interoperating data-driven and model-driven techniques for the automated development of intelligent environmental decision support systems
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Economic linear parameter varying model predictive control of the aeration system of a wastewater treatment plant
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An interoperable workflow-based framework for the automation of building intelligent process control systems
9th International Congress on Environmental Modelling and Software
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Herramienta basada en minería de datos para la automatización del diseño de sistemas inteligentes en EDAR
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Data mining based tool for the automation of the design of intelligent process control systems in waste water treatment plants
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Optimizing online time-series data imputation through case-based reasoning
24th International Conference of the Catalan Association for Artificial Intelligence
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Ensemble model-based method for time series sensors’ data validation and imputation applied to a real waste water treatment plant
11th International Congress on Environmental Modelling and Software
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Director:ALQUEZAR MANCHO, RENATO
Mention:No mention
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González, A.; Alquezar, R.; Ramírez, A.; González, F.; García, I.
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Title:A framework for the analytical and visual interpretation of complex spatiotemporal dynamics in soccer
Reading date:18/01/2022
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Director:BORNN, LUKE
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Mention:Industrial Doctorate Mention (Generalitat)
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Soccer analytics: Unravelling the complexity of “the beautiful game”
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A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions
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SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Presentation date: 25/02/2021
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Reading date:21/12/2020
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Mention:International Mention
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K nearest neighbour optimal selection in fuzzy inductive reasoning for smart grid applications
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The importance of Robust and Reliable Energy Prediction Models: Next Generation of Smart Meters
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Reading date:10/11/2020
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Mention:No mention
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Visual semantic re-ranker for text spotting
23rd Iberoamerican Congress on Pattern Recognition
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Visual re-ranking with natural language understanding for text spotting
14th Asian Conference on Computer Vision
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Semantic relatedness based re-ranker for text spotting
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Textual visual semantic dataset for text spotting
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Reading date:14/07/2020
Director:BÉJAR ALONSO, JAVIER
Co-director:CORTÉS GARCÍA, CLAUDIO ULISES
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Forecastability measures that describe the complexity of a site for deep learning wind predictions
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27/09/202131/12/2023Estudi de seguretat d'un fàrmacFERRER INTERNACIONAL,S.A.
01/09/202131/08/2024CogNition, emotion/behAvior, fUnctionaliTy and braIn connectivity in recovered COVID-19 patientSFundació La Marató de TV3
01/09/202131/08/2024Implantación de la economía Circular en la Industria de Proceso (CEPI): Métodos y herramientas para la integración circular de sistemas.AGENCIA ESTATAL DE INVESTIGACION
01/09/202131/08/2024artificial Intelligence threat Reporting and Incident response SystemEuropean Commission
31/08/202131/08/2021Software TP2TD: Text processing pipeline for topic-discovery
04/08/202131/12/2024Inteligencia Artificial distribuida para el diagnóstico y tratamiento temprano de enfermedades con gran prevalencia en el envejecimientoMIN DE ECONOMIA Y COMPETITIVIDAD
01/08/202115/03/2024Detectability of humpback and gray whales in satellite imagery off California.The Nature Conservancy
01/06/202131/12/2022CoviD-19 and brain: cognItion And meNtal heAlthAgència de Gestió d'Ajuts Universitaris i de Recerca (Agaur)
01/06/202131/12/2022Realització del projecte de R+D consistent en la millora de funcionalitats de la tecnologia consistent en “Sistema Interoperable basat en tècniques data-driven i model-driven per a l’Automatització deCCB SERVEIS MEDI AMBIENTALS, SA
01/06/202101/03/2023AI for TourismCentre of Innovation for Datatech and Artificial Intelligence
01/04/202131/12/2021dynamiC spEed Limits compliancE for optimiSed Traffic managEmentEUROPEAN INST OF INNOV.& TECHNOL.
01/04/202131/03/2022WalCycData: A data infrastructure for vulnerable road usersEUROPEAN INST OF INNOV.& TECHNOL.
01/02/202131/01/2024Desenvolupament d'un curs digital sobre IA per a la ciutadania en general de difusió massiva en la societat catalanaFUNDACIÓ i2CAT
15/01/202130/09/2021El primero de los objetivos de este proyecto sobre la generación del modelo en forma de gemelo digital se desarrollará a través de la supervisión y asesoramiento del estudio y trabajo desarrollado porT.M.GESTIO SCCL
01/01/202131/12/2024A Collaborative Paradigm for Human Workers and Multi-Robot Teams in Precision Agriculture SystemsCommission of European Communities
01/01/202131/03/2024Towards AI powered manufacturing services, processes, and products in an edge-to-cloud-knowlEdge continuum for humans [in-the-loop]Commission of European Communities
01/01/202131/12/2023Stairway to AI: Ease the Engagement of Low-Tech users to the AI-on-Demand platform through AICommission of European Communities
01/01/202131/12/2022T3.3 Task Force Digitalización vertical (UPC)ATOS SPAIN S.A.
01/01/202131/12/2021ANOMALY FASE 0Agència per la Competitivitat de l'Empresa (ACCIÓ)
01/01/202101/04/2022Llibre blanc sobre la Intel·ligència Artificial aplicada a les indústries culturals i basades en l’experiènciaCentre of Innovation for Data tech and Artificial Intelligence
01/12/202031/12/2021Promoción de una longevidad mental saludable en España y Portugal mediante el desarrollo de una aplicación tecnológica de soporte a la terapia de reminiscencia basada en el patrimonio cultural inmaterialConsejo Superior de Investigaciones Científicas; Fondos FEDER
01/12/202031/10/2021CiutadanIA: Intel·ligència Artificial per a tothomGeneralitat de Catalunya. Departament de la Vicepresidencia i de Politiques Digitals i Territori
19/11/202015/02/2022Promoción de una longevidad mental saludable en España y Portugal mediante el desarrollo de una aplicación tecnológica de soporte a la terapia de reminiscencia basada en el patrimonio cultural inmaterFUNDACIÓN GENERAL CSIC
01/11/202031/12/2022H2020-894116-SYN+AIRSESAR JOINT UNDERTAKING
28/10/202031/12/2021L2-Projectes de desenvolupament i innovació - Realització d'estudis de viabilitat tècnica - ANOMALY - FASE 0Agència per la Competitivitat de l'Empresa (ACCIÓ)
19/10/202018/10/2024CA19122 - European Network For Gender Balance in InformaticsEuropean Cooperation in Science and Technology
15/10/202027/07/2021Detecció d'avaries en sistemes multisensorialsAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/10/202001/12/2020CCT 2020/KG-06: I què hi diuen les dones al Robert? (Que-Robert)Palau Robert
01/09/202031/08/2021Interpretació del topic modelling en dades textualsUniversitat Politècnica de Catalunya
15/08/202031/12/2022Xarxa R+D+I en Tecnologies de la Salut (XarTEC SALUT)AGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
13/08/202013/08/2020Discoursive Process Modeling Empowered with Envolving Process Model Search and Optimization
30/07/202030/12/2020Knowledge Adaptive Recommender for Intelligent NutritionCUBE TECHNOLOGY INNOVATION,S.L.
15/07/202014/02/2021Uso de algoritmos de aprendizaje por refuerzo en problemas de planificaciónITHINKUPC, S.L.
09/07/202015/01/2021PRimera fase del projecte KARIN Desenvolupament del mòdul de distàncies semàntiques pel recomanador d'alimentsCUBE TECHNOLOGY INNOVATION,S.L.
01/07/202031/12/2022Xarxa Fourth Industrial RevolutionAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/07/202031/12/2020Crowdsourced Obtention and Analytics of Data About the Crowding of Public Spaces for the Benefit of Public Transport and Mobility in CitiesEUROPEAN INST OF INNOV.& TECHNOL.
01/07/202031/12/2022Red de Innovación de Nuevas Tecnologías en Salud Mental (TECSAM)Fondos FEDER
30/06/202030/06/2020Model Judge
01/06/202031/05/2023Colaboración robot-humano para el transporte y entrega de mercancíasAGENCIA ESTATAL DE INVESTIGACION
01/06/202030/09/2023Aprendizaje Automático para la Modelización de la Dinámica Molecular de las Proteinas GPCRAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2024Análisis de texto médico para la assistencia a la predicción de diagnosisAGENCIA ESTATAL DE INVESTIGACION
01/04/202031/01/2021Identificació de Necessitats Socials Emergents com a conseqüència de la COVID19 i efecte sobre els Serveis Socials del territoriUniversitat Politècnica de Catalunya
03/03/202031/12/2022Hub d'Innovació PediàtricaFondos FEDER
01/03/202028/02/2026Interactive Machine Learning for Compositional Models of Natural LanguageEuropean Research Council (ERC)
01/03/202031/12/2022Centre de Recerca i Transferència en Salut Mental (CRETSAM)Fondos FEDER
01/03/202028/02/2021Systematization of the acquisition of data throughout Ecuador of the beneficiaries or potential beneficiaries through a digital platform that allows citizens to locate the sites where the physical-rhythmic and recreational activities are carried outCentre de Cooperació per al Desenvolupament , UPC
01/01/202031/12/2020Top Secret RosiesAjuntament de Barcelona
27/12/201927/09/2021Integrated care for frail older adults in the communityINSTITUT DE CULTURA DE BARCELONA
01/11/201901/04/2020Sistemas recomendadores para el desarrollo de una solución de asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial. Proyecto HR2020 de FBLCITHINKUPC, S.L.
01/09/201928/02/2022Artificial Intelligence skills for ICT professionalsCommission of European Communities
01/09/201928/02/2023GAVIUS: from reactive to proactive public administrationsCommission of European Communities
01/06/201931/12/2021Digitalization on Power Generation in the field of Data Analytics and Artificial Intelligence, para la aplicaci´on industrial de t´ecnicas de IA a la producci´on y gesti´on de turbinas de gasSiemens
04/04/201931/10/2020Multiparametric MR approaches for non-invasive Gliobastoma therapy response follow-upCommission of European Communities
01/04/201931/03/2023Future human-machine (AI) Interactlon fon in-car/mobility exoerienceAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/03/201928/02/2020Adquisición de datos para optimizar la oferta de servicios, de promoción de la vida sana, entre los habitantes de zonas desfavorables de GuayaquilCentre de Cooperació per al Desenvolupament , UPC
01/01/201931/12/2021A European AI On Demand Platform and EcosystemCommission of European Communities
01/01/201930/06/2019SEAT-SmarT11: Proyecto de optimización de recursos para ajustes de calidadCàtedra SEAT - UPC
01/01/201930/09/2022Razonamiento Formal para Tecnologías Facilitadoras y EmergentesAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/10/2022Evolving towards DIgital Twins in HealthcareAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2022001-P-001643_Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/01/201901/08/2021Data Science for Gender Gap (DSGG)Pendent per manca de dades
01/01/201931/12/2022INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicineEuropean Commission
01/01/201931/12/2019identificación de perfiles de consumo de servicios sanitarios en el estado de Nueva Gales, AustraliaAustralian National University
01/01/201931/12/2019Analysis of case management in Australia through Clustering Based on Rules and data science approachVisual and Decision Analytics
09/12/201031/08/2026ALEA-SOFTUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona
23/03/201031/08/2026Fundació Salut i Envelliment UABUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona

Teaching staff and research groups

Research projects

START DATEEND DATEACTIVITYFINANCING ENTITY
02/11/202331/12/2024CONTRATO DE PRESTACIÓN DE SERVICIOS ENTRE ANYSOLUTION Y UNIVERSIDAD POLITÉCNICA DE CATALUÑA Proyecto PLANETICANYSOLUTION SL
01/11/202331/08/2025LDCI2027 - CORNETFVV
01/09/202331/08/2026Apoyo a la decisión en oftalmología basado en Machine Learning y aplicado a imágenes multi-modales de la retinaAGENCIA ESTATAL DE INVESTIGACION
01/09/202331/08/2026gion of Reliable syntheTIc health data for Federated leArning in seCure daTa Spaces - UPCAGENCIA ESTATAL DE INVESTIGACION
17/07/202323/07/2025Disseny de les estructures de dades i repositori comú amb mixtura d'estratègia centalitzada federadaImplementació d'iuna capa intel.ligent de dadesPilot a Vall d'AranFUNDACIO TICSALUT
01/06/202331/05/2024Canvi Climàtic i equitat: mapeig de les emissions en funció del nivell de rendaCentre per a la Cooperació al Desenvolupament
08/05/202308/05/2023ROBOT SOCIAL, CECI
01/05/202330/04/2026Federate Learning and mUlti-party computation Techniques for prostatE cancerCommission of European Communities
01/05/202330/04/2026Towards a personalized medicine approach to psychological treatment for psychosisEuropean Commission
29/03/202329/12/2023Reinforcement learning per water managementCETAQUA
21/03/202322/03/2023Patrocini de la jornada d'entrega de premis del programa Top Secret Rosies. Direcció general de Societat Digital (Resolució d'adjudicació EMO-2023-245).GENERALITAT DE CATALUNYA
03/03/202331/12/2026Siemens Energy AI Chair. Energy sustainability for a decarbonized society 5.0SIEMENS GAS AND POWER SAU
01/03/202330/06/2023Estudi de viabilitat tecnològica d’un recomanador personalitzat de vins basat en tècniques d’IAACCIO10
09/02/202301/11/2023Recerca-diagnòstic sobre la Diversitat en la Intel·ligència Artificial a Catalunya. Departament d'Igualtat i Feminisme de la Generalitat (Resolució d’adjudicació IF-2023-39).GENERALITAT DE CATALUNYA
26/01/202326/01/2023Quick sequence detection
01/01/202331/12/2025Xarxa R+D+I en Tecnologies de la Salut (Xartec Salut)AGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/01/202331/12/2025Hacia un enfoque de medicina personalizada para el tratamiento psicológico de la psicosisINSTITUTO DE SALUD CARLOS III
01/01/202331/12/2025Xarxa d’Innovació de Noves Tecnologies en Salut MentalAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/01/202331/12/2025HUB D'INNOVACIÓ PEDIÀTRICAFondo Europeo de Desarrollo Regional
01/01/202331/12/2026Create a Symbiosis where PV and agriculture can have a mutually beneficial relationshipCommission of European Communities
23/12/202231/12/2023ASISTENTE INTELIGENTE PARA LA GESTIÓN DE UNA PLANTA DE TRATAMIENTO DE AGUAS QUE OPTIMICE LA GESTIÓN DE FANGOS ACTIVADOS ENTRE EL CENTRO DE INVESTIGACIÓN EN CIENCIA INTELIGENTE DE DATOS E INTELIGENCIACETAQUA
22/12/202222/12/2025 IA a la transformació digitalFUNDACIÓ i2CAT
01/12/202230/11/2024Aprendizaje automático y sus aplicaciones en la rehabilitación digital para predecir resultados terapéuticos en pacientes con síndrome post COVID19 con deterioro cognitivoAGENCIA ESTATAL DE INVESTIGACION
01/12/202230/11/2024Automatización de procesos de negocio a partir de interacciones humanasAGENCIA ESTATAL DE INVESTIGACION
21/11/202223/02/2023CISCO hará una aportación única a la UPC para ser destinados al programa de generación de talento femenino en Inteligencia Artificial de nombre Top Rosies Talent ycon dedicación especial a la línea dCISCO SYSTEMS (SPAIN) SL
01/11/202201/12/2022Cápsulas inspiracionales programa Apuesta por las TICGeneralitat de Catalunya (GenCat); FUNDACIÓ BARCELONA MOBILE WORLD CAPITAL FOUNDATION
01/09/202231/08/2025Métodos formales escalables para aplicaciones en entornos realesAGENCIA ESTATAL DE INVESTIGACION
01/09/202220/02/2024Programa de generació de talent femení en IAFUNDACIO BARCELONA MOBILE WORLD CAP
12/07/202212/07/2022Software: Conceptual Map automated construction
01/06/202230/06/2022Supervision of the development of the Python version of Gesconda (Gespy)
01/06/202230/06/2023Contrato de colaboración para el desarrollo y aplicación de técnicas de inteligencia artificial para la predicción de la evoluciónBEAWRE DIGITAL, SOCIEDAD LIMITADA
15/05/202231/07/2022Contracte de col.laboració per l’assessorament en la viabilitat de producció i suport en la selecció de fonts de finançaments dels desenvolupaments tècnics associats al projecte ALTERNATIVA ALS RESIDUT.M.GESTIO SCCL
01/05/202230/04/2025Catalonia Digital Innovation (DIH4CAT)European Commission
01/05/202230/04/2025Catalonia Digital Innovation Hub (DIH4CAT)DIRECTORATE-GENERAL FOR COMMUNIC.
23/04/202231/12/2022Donació pel congrés ACAI-2022¿EurAI
23/04/202231/12/2022Donació pel curs ACAI-2022Artificial Intelligence Journal
19/01/202219/01/2022Diseño ROBOT SOCIAL
01/01/202231/12/2022Last mile logistics for autonomous goods deliveryEUROPEAN INST OF INNOV.& TECHNOL.
01/01/202231/12/2022InnovaCity 2.0EUROPEAN INST OF INNOV.& TECHNOL.
01/01/202201/03/2023Top Rosies TalentDIGITAL FUTURE SOCIETY; HP Printing and Computing Solutions, S.L.U .
01/12/202130/11/2024Robots para la asistencia continua y personalizada capaces de explicar-se a si mismosAGENCIA ESTATAL DE INVESTIGACION
01/11/202130/10/2023Life in the AI EraCommission of European Communities
25/10/202130/06/2022PRESTACIÓ DEL SERVEI DE MENTORIA CIENTÍFICA DINS DE L’ADVISORY BOARD DEL REPTE TDA (TECNOLOGIES DIGITALS AVANÇADES) EN CIBERSEGURETATFUNDACIÓ i2CAT
27/09/202131/12/2023Estudi de seguretat d'un fàrmacFERRER INTERNACIONAL,S.A.
01/09/202131/08/2024CogNition, emotion/behAvior, fUnctionaliTy and braIn connectivity in recovered COVID-19 patientSFundació La Marató de TV3
01/09/202131/08/2024Implantación de la economía Circular en la Industria de Proceso (CEPI): Métodos y herramientas para la integración circular de sistemas.AGENCIA ESTATAL DE INVESTIGACION
01/09/202131/08/2024artificial Intelligence threat Reporting and Incident response SystemEuropean Commission
31/08/202131/08/2021Software TP2TD: Text processing pipeline for topic-discovery
04/08/202131/12/2024Inteligencia Artificial distribuida para el diagnóstico y tratamiento temprano de enfermedades con gran prevalencia en el envejecimientoMIN DE ECONOMIA Y COMPETITIVIDAD
01/08/202115/03/2024Detectability of humpback and gray whales in satellite imagery off California.The Nature Conservancy
01/06/202131/12/2022CoviD-19 and brain: cognItion And meNtal heAlthAgència de Gestió d'Ajuts Universitaris i de Recerca (Agaur)
01/06/202131/12/2022Realització del projecte de R+D consistent en la millora de funcionalitats de la tecnologia consistent en “Sistema Interoperable basat en tècniques data-driven i model-driven per a l’Automatització deCCB SERVEIS MEDI AMBIENTALS, SA
01/06/202101/03/2023AI for TourismCentre of Innovation for Datatech and Artificial Intelligence
01/04/202131/12/2021dynamiC spEed Limits compliancE for optimiSed Traffic managEmentEUROPEAN INST OF INNOV.& TECHNOL.
01/04/202131/03/2022WalCycData: A data infrastructure for vulnerable road usersEUROPEAN INST OF INNOV.& TECHNOL.
01/02/202131/01/2024Desenvolupament d'un curs digital sobre IA per a la ciutadania en general de difusió massiva en la societat catalanaFUNDACIÓ i2CAT
15/01/202130/09/2021El primero de los objetivos de este proyecto sobre la generación del modelo en forma de gemelo digital se desarrollará a través de la supervisión y asesoramiento del estudio y trabajo desarrollado porT.M.GESTIO SCCL
01/01/202131/12/2024A Collaborative Paradigm for Human Workers and Multi-Robot Teams in Precision Agriculture SystemsCommission of European Communities
01/01/202131/03/2024Towards AI powered manufacturing services, processes, and products in an edge-to-cloud-knowlEdge continuum for humans [in-the-loop]Commission of European Communities
01/01/202131/12/2023Stairway to AI: Ease the Engagement of Low-Tech users to the AI-on-Demand platform through AICommission of European Communities
01/01/202131/12/2022T3.3 Task Force Digitalización vertical (UPC)ATOS SPAIN S.A.
01/01/202131/12/2021ANOMALY FASE 0Agència per la Competitivitat de l'Empresa (ACCIÓ)
01/01/202101/04/2022Llibre blanc sobre la Intel·ligència Artificial aplicada a les indústries culturals i basades en l’experiènciaCentre of Innovation for Data tech and Artificial Intelligence
01/12/202031/12/2021Promoción de una longevidad mental saludable en España y Portugal mediante el desarrollo de una aplicación tecnológica de soporte a la terapia de reminiscencia basada en el patrimonio cultural inmaterialConsejo Superior de Investigaciones Científicas; Fondos FEDER
01/12/202031/10/2021CiutadanIA: Intel·ligència Artificial per a tothomGeneralitat de Catalunya. Departament de la Vicepresidencia i de Politiques Digitals i Territori
19/11/202015/02/2022Promoción de una longevidad mental saludable en España y Portugal mediante el desarrollo de una aplicación tecnológica de soporte a la terapia de reminiscencia basada en el patrimonio cultural inmaterFUNDACIÓN GENERAL CSIC
01/11/202031/12/2022H2020-894116-SYN+AIRSESAR JOINT UNDERTAKING
28/10/202031/12/2021L2-Projectes de desenvolupament i innovació - Realització d'estudis de viabilitat tècnica - ANOMALY - FASE 0Agència per la Competitivitat de l'Empresa (ACCIÓ)
19/10/202018/10/2024CA19122 - European Network For Gender Balance in InformaticsEuropean Cooperation in Science and Technology
15/10/202027/07/2021Detecció d'avaries en sistemes multisensorialsAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/10/202001/12/2020CCT 2020/KG-06: I què hi diuen les dones al Robert? (Que-Robert)Palau Robert
01/09/202031/08/2021Interpretació del topic modelling en dades textualsUniversitat Politècnica de Catalunya
15/08/202031/12/2022Xarxa R+D+I en Tecnologies de la Salut (XarTEC SALUT)AGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
13/08/202013/08/2020Discoursive Process Modeling Empowered with Envolving Process Model Search and Optimization
30/07/202030/12/2020Knowledge Adaptive Recommender for Intelligent NutritionCUBE TECHNOLOGY INNOVATION,S.L.
15/07/202014/02/2021Uso de algoritmos de aprendizaje por refuerzo en problemas de planificaciónITHINKUPC, S.L.
09/07/202015/01/2021PRimera fase del projecte KARIN Desenvolupament del mòdul de distàncies semàntiques pel recomanador d'alimentsCUBE TECHNOLOGY INNOVATION,S.L.
01/07/202031/12/2022Xarxa Fourth Industrial RevolutionAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/07/202031/12/2020Crowdsourced Obtention and Analytics of Data About the Crowding of Public Spaces for the Benefit of Public Transport and Mobility in CitiesEUROPEAN INST OF INNOV.& TECHNOL.
01/07/202031/12/2022Red de Innovación de Nuevas Tecnologías en Salud Mental (TECSAM)Fondos FEDER
30/06/202030/06/2020Model Judge
01/06/202031/05/2023Colaboración robot-humano para el transporte y entrega de mercancíasAGENCIA ESTATAL DE INVESTIGACION
01/06/202030/09/2023Aprendizaje Automático para la Modelización de la Dinámica Molecular de las Proteinas GPCRAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2024Análisis de texto médico para la assistencia a la predicción de diagnosisAGENCIA ESTATAL DE INVESTIGACION
01/04/202031/01/2021Identificació de Necessitats Socials Emergents com a conseqüència de la COVID19 i efecte sobre els Serveis Socials del territoriUniversitat Politècnica de Catalunya
03/03/202031/12/2022Hub d'Innovació PediàtricaFondos FEDER
01/03/202028/02/2026Interactive Machine Learning for Compositional Models of Natural LanguageEuropean Research Council (ERC)
01/03/202031/12/2022Centre de Recerca i Transferència en Salut Mental (CRETSAM)Fondos FEDER
01/03/202028/02/2021Systematization of the acquisition of data throughout Ecuador of the beneficiaries or potential beneficiaries through a digital platform that allows citizens to locate the sites where the physical-rhythmic and recreational activities are carried outCentre de Cooperació per al Desenvolupament , UPC
01/01/202031/12/2020Top Secret RosiesAjuntament de Barcelona
27/12/201927/09/2021Integrated care for frail older adults in the communityINSTITUT DE CULTURA DE BARCELONA
01/11/201901/04/2020Sistemas recomendadores para el desarrollo de una solución de asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial. Proyecto HR2020 de FBLCITHINKUPC, S.L.
01/09/201928/02/2022Artificial Intelligence skills for ICT professionalsCommission of European Communities
01/09/201928/02/2023GAVIUS: from reactive to proactive public administrationsCommission of European Communities
01/06/201931/12/2021Digitalization on Power Generation in the field of Data Analytics and Artificial Intelligence, para la aplicaci´on industrial de t´ecnicas de IA a la producci´on y gesti´on de turbinas de gasSiemens
04/04/201931/10/2020Multiparametric MR approaches for non-invasive Gliobastoma therapy response follow-upCommission of European Communities
01/04/201931/03/2023Future human-machine (AI) Interactlon fon in-car/mobility exoerienceAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/03/201928/02/2020Adquisición de datos para optimizar la oferta de servicios, de promoción de la vida sana, entre los habitantes de zonas desfavorables de GuayaquilCentre de Cooperació per al Desenvolupament , UPC
01/01/201931/12/2021A European AI On Demand Platform and EcosystemCommission of European Communities
01/01/201930/06/2019SEAT-SmarT11: Proyecto de optimización de recursos para ajustes de calidadCàtedra SEAT - UPC
01/01/201930/09/2022Razonamiento Formal para Tecnologías Facilitadoras y EmergentesAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/10/2022Evolving towards DIgital Twins in HealthcareAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2022001-P-001643_Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/01/201901/08/2021Data Science for Gender Gap (DSGG)Pendent per manca de dades
01/01/201931/12/2022INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicineEuropean Commission
01/01/201931/12/2019identificación de perfiles de consumo de servicios sanitarios en el estado de Nueva Gales, AustraliaAustralian National University
01/01/201931/12/2019Analysis of case management in Australia through Clustering Based on Rules and data science approachVisual and Decision Analytics
09/12/201031/08/2026ALEA-SOFTUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona
23/03/201031/08/2026Fundació Salut i Envelliment UABUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona

Quality

The Validation, Monitoring, Modification and Accreditation Framework (VSMA Framework) for official degrees ties the quality assurance processes (validation, monitoring, modification and accreditation) carried out over the lifetime of a course to two objectives—the goal of establishing coherent links between these processes, and that of achieving greater efficiency in their management—all with the overarching aim of improving programmes.

Validation

Monitoring

Accreditation

    Registry of Universities, Centers and Degrees (RUCT)

    Indicators