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Presentation

General information about PhDs at UPC can be found at the Doctoral School

Goal:

The main goal of the PhD program is to help students to take-up their research in the Cognitive Sciences and/or the Knowledge Engineering related areas. The emphasis in Cognitive Sciences suggests a basic interest in understanding the phenomena associated with Learning mechanisms, Natural Language Understanding, Mind and Intelligence, Perception, etc.

The Ph.D. program in Artificial Intelligence aims to provide the basis for a solid and strong research profile. Students completing the program are typically well qualified for teaching and research positions with colleges and universities as well as with national and international industries and laboratories. The program covers many topics of research related to the design, analysis and use of Artificial Intelligence systems.

Organization:

All Ph.D. programs in the UPC are under the control of the Doctoral School. Additionally, the PhD in Artificial Intelligence is attached to the Computer Science Department. Here you can find additional details about the internal organization.

Duration:

The doctoral program is designed to allow a full-time student entering with a Master of Science in Artificial Intelligence and a degree in Computer Science to complete the degree within three years (five years for part-time). However, it is not uncommon for doctoral programs to take somewhat longer. Extensions must be accepted by the Academic Committee.

Research Topics and Potential Advisors:

Most professors in the program belong to one of the following Research Groups

All the professors involved in the program are experienced researchers. Their list of publications can be found in futur.upc.edu. The impact of their research can be found at google scholar. The current list of professors is:

  • Ulises Cortés
  • Miquel Sànchez
  • Karina Gibert
  • Javier Bejar
  • Mario Martín
  • Javier Vazquez
  • René Alquézar
  • Lluís Belanche
  • Angela Nebot
  • Francisco Múgica
  • Alfredo Vellido
  • Enrique Romero
  • Lluís Padró
  • Horacio Rodríguez
  • Jordi Turmo
  • Javier Larrosa
  • Cecilio Angulo
  • Ricard Gavaldà
  • Marta Arias
  • Fatos Xafa
  • Roberto Nieuwenhuis
  • Albert Rubio
  • Albert Oliveras
  • Emma Rollón
Any other teacher at UPC with research interest on AI can also be an advisor, provided that the Academic Committee accepts it.

Current Research Projects:

Proyectos competitivos activos en los que participa el profesorado:

 

Nombre

Duración

Referencia

Entidad Financiadora

MinD

1/3/2016

H2020-691001

European Commision

CAREGIVERSPRO-MMD

1/1/2016-31/12/2018

H2020-690211

EUROPEAN COMMISSION

RehAdapta

1/1/2015-31/12/2017

TEC2014-56256-C2-2-P

GOBIERNO DE ESPAÑA

DIALCAT

15/10/2016-14/10/2019

COMRDI15-1-0024-13

Generalitat Catalunya

SHAREBOX

1/9/2015-31/8/2019

H2020-680843

EUROPEAN COMMISSION

COIN-GPCR

30/12/2016-29/12/2019

TIN2016-79576-R

GOBIERNO DE ESPAÑA

APCOM

1/1/2015-31/12/2017

TIN2014-57226-P

GOBIERNO DE ESPAÑA

GRAPH-MED

30/12/2016-29/12/2019

TIN2016-77820-C3-3-R

GOBIERNO DE ESPAÑA

CoMMas

1/1/2014-31/12/2017

TIN2013-46181-C2-1-R

GOBIERNO DE ESPAÑA

LoBaSS

01/01/16-31/12/18

TIN2015-69175-C4-3-R

GOBIERNO DE ESPAÑA

Diet4you

01/01/2015-30/06/2019

TIN2014-60557-R

GOBIERNO DE ESPAÑA

 

Acceptance Profile:

The legal requirement to be accepted is having a Master (precise details can be found here)

The ideal background of a candidate is a degree in Computer Science (such as this) and a Master in Artificial Intelligence (such as this). However, students with degrees and masters in related areas such as Engineering, Mathematics, Statistics, etc may be accepted with the requirement of taking selected courses from the Master in Artificial Intelligence.

All candidates must have before being accepted a letter from a teacher in the program agreeing in supervising the PhD. The program coordinator can help students in finding a teacher that best fits their interest.

Accepted students must be able to read technical documents and attend seminars and conferences in English. Candidates must proof having level B1 of English.

All admission requests from candidates that satisfy the legal requirements will be evaluated by the academic committee. The committee will make its decision based on the following items and weights:

  • Academic background (60%)
  • English level (20%)
  • Previous research experience (20%)

Full details on acceptance requirements and procedure can be found here.

Complementary Courses:

If the background of the candidate requires it, the committee may accept with the requirement of taking selected courses from the Master in Artificial Intelligence. As an orientation, we consider three types of candidate background:

  • If the candidate has a Master in AI or Intelligent Systems, no additional course will be required
  • If the candidate has a Master in  in Computer Science, Electric Engineering, Software Engineering or similars, all the mandatory courses from the Master will be required except for those already taken.
  • If the candidate has a degree or Master in Telecommunications, Mathematics, Estatistics or similars all the mandatory courses will be required.
Depending on the topic of the Thesis and the specific knowledge required, additional Master courses may be required.
The Master mandatory courses are:
  • Computational Intelligence
  • Computer Vision
  • Introduction to Natural Language Technology
  • Introduction to Multiagent systems
  • Introduction to Machine Learning
  • Planning and Approximate Reasoning

Training Activities:

Besides the frequent meetings that students have with their advisors, there are two other times of training activities:

  • Transversal courses and seminars are organized by the Doctorate School. They include courses and seminars about Information skills, research methodology, communication skills, innovation, creativity, etc.
  • Specific courses and seminars from the research group where the Thesis takes place. They include seminars from visiting professors, join seminars with the Master on AI, research schools organized by research associations, etc. Advisors will give advise to their PhD students about different opportunities and possible grants to cover the cost of attending these schools.

Evaluation:

All students must submit a yearly report on their progress that will be evaluated by the Academic Committee. Besides, in their second year students must present orally their thesis project to an ad-hoc committee. Finally, the thesis can only be defended after an anonymous review. Details about all these evaluations can be found here, here and here.

 

Internatioalization:

In our program we believe that students must go beyond our department to meet other researchers at an international level. We recommend our students to visit research groups related to their work for at least 3 months. The thesis advisor will provide advise about the best time to do these visits and the best destinations.

The Doctorate School informs regularly about mobility opportunities.

Miscellaneous:

 

  • Number of entry places per academic year: 10
  • Facilities: All students have access to a working desk, internet acess, shared desktop computer, printer, library, basic software (e-mail account, programming environment, data analysis sofware, ...).
  • The calendar of administrative topics (e.g. enrollment, extension request, yearly report submission,...) is updated every year and can be found here.
  • Our program, like every PhD program at UPC, follows a strict system of internal quality control and transparency. Details can be found here.

Facts and Figures:

 


2013/014 2014/2015 2015/2016 2016/2017
ACCÉS I MATRÍCULA



Oferta de places 10 10 10 10
Estudiants matriculats de nou ingrés
2 14 3
Nombre total d'estudiants matriculats
38 38 27
estudiants estrangers matriculats


16
estudiants amb beca



estudiants provinents d'altres universitats
22 23 19





RESULTATS ACADÈMICS



Nombre total de tesis llegides 3 5 8 2
tesis amb qualificació de cum laude (núm) 1 4 5 1
doctors amb menció internacional (núm) 2 3 2 1
Percentatge d'abandonament del programa
11.99% 15.79% 15.79%
Nombre de resultats científics de les tesis doctorals 33 49 99 11
Nombre de tesis llegides a temps complet 2 5 8 2
Nombre de tesis llegides a temps parcial 1 0 0 0
Duració mitjana de tesis a temps complet 6 4.6 7 5.6
Duració mitjana de tesis a temps parcial 7.5 0 0 0
Nombre de tesis llegides amb membre tribunal extranger 2 4 6 1





PERSONAL DOCENT INVESTIGADOR



sexennis vius dels directors de tesis llegides 3 3 6 1
Nombres de directors/codirectors UPC de tesis defensades 3 4 7 7
External jury members
3 0 1
INDICADORS DE SATISFACCIÓ



Satisfacció dels doctorands amb els estudis
% 3.89/5
Satisfacció dels professors amb el programa



INSERCIÓ LABORAL



Taxa d'adequació de la feina als estudis
% 65.00%
Taxa d'ocupació
% 96.00%