Petia Radeva

• Full professor at the Department of Mathematics and Computer Science, Faculty of Mathematics and Computer Science, Universitat de Barcelona;
• Icrea Academia;
• Collaborator of the State Agency of Research (Agencia Estatal de Investigación) area TIC (INF), División de Coordinación, Evaluación y Seguimiento Científico Técnico, November 2019.
• Senior Researcher in Computer Vision Center (CVC);
• Senior Researcher in the Institute of Neurosciences, UB;
• Head of “Artificial Intelligence and Biomedical Applications (AIBA)” consolidated research group (www.ub.edu/cvub) 2021 SGR 01094; Member of ELLIS Network, IAPR Fellow.
• Associate editor in Chief of Pattern Recognition journal (Q1, IP=7.196) and
• Associate editor of International Journal of Visual Communication and Image Representation (Q2, IP=3.13), responsible of Special issues of the journal.

Personal Web:http://www.ub.edu/cvub/petiaradeva,

email: petia dot ivanova at ub dot edu, radevap at gmail dot com

Google Scholar Citations, Microsoft Academic Record, LinkedIn, ResearchGate

We often have a postdoc positions, vacant Master and/or PhD Fellowships on Deep learning and applications to real problems! If you are interested, send your CV and Academic transcript to radevap at gmail dot com

Biosketch

Prof. Petia Radeva is a Full professor at the Universitat de Barcelona (UB), Head of the Consolidated Research Group “Artificial Intelligence and Biomedical Applications (AIBA)” at the University of Barcelona. Her main interests are in Machine/Deep learning and Computer Vision and their applications to health. Specific topics of interest: data-centric deep learning, uncertainty modeling, self-supervised learning, continual learning, learning with noisy labeling, multi-modal learning, NeRF, food recognition, food ontology, etc.

She was PI of UB in 7 European, 3 international and more than 25 national projects devoted to applying Computer Vision and Machine learning for real problems like food intake monitoring (e.g. for patients with kidney transplants and for older people).

She is an Associate editor in Chief of Pattern Recognition journal (Q1, IP=8.0).

She is a Research Manager of the State Agency of Research (Agencia Estatal de Investigación, AEI) of the Ministry of Science and Innovation of Spain.

Petia Radeva belongs to the top 2% of the World ranking of scientists with the major impact in the field of TIC according to the citations indicators of the popular ranking of Stanford. Also, she was selected in the first 6% of the ranking of Spanish and foreign most cited female researchers from any field according to the Ranking of CSIC: https://lnkd.in/djx2Yz5p. Moreover, she was awarded the prestigous “Narcis Monturiol” medal in 2024, IAPR Fellow since 2015, ICREA Academia’2015 and ICREA Academia’2022 assigned to the 30 best scientists in Catalonia for her scientific merits, received several international and national awards (“Aurora Pons Porrata” of CIARP, Prize “Antonio Caparrós” for the best technology transfer at UB, etc).

She supervised 24 PhD students and published more than 100 SCI journal publications and in total, >400 international chapters and proceedings, her Google scholar h-index is 54 with >11900 cites.

Currently, member of:

• Institute of Mathematics of the University of Barcelona (IMUB)
• Institute of Neuroscience at the Universitat de Barcelona
• Xarxa d’Innovació de Noves Tecnologies en Salut Mental (TECSAM)
• DataScience@UB
• BARCELONA GRADUATE SCHOOL OF MATHEMATICS (BSGMath)
• IAPR Fellow
• Asociación Española de Reconocimiento de Formas y Análisis de Imágenes (AERFAI)
• IAPR Fellow Committee
• IEETA SAB
• CITIC SAB
• CITIUS SAB

Other positions:

• Crossreader of EISMEA-EIC-PATHFINDER, European Commission, 2022.
• External expert of the Government of Alberta Major Innovation Fund, 2022.
• Secretary of the Advisory board of CITIC, A Coruña, Spain
• Scientific Advisory Board member of IEETA, Portugal, 2022-.
• Member of the Advisory board of ITN “VisuALL”.
• External expert  of the FCT, Portugal, 2022.
• External expert  of the Italian Ministry of University and Research, 2022.
• External expert  of Novo Nordisk, Denmark, 2022.
• External expert  of NCMM, Norway, 2022.
• External expert  of the CORE Multi-Annual Thematic Research Programme, Fonds National de la Recherche Luxembourg (FNR), Luxembourg, 2022.
• External expert  of the European Science Foundation (ESF – www.esf.org), 2022.
• External expert of the Research and Development Office, The Education University of Hong Kong, 2022.
• External expert  of the Cyprus Research and Innovation Foundation, 2022.
• External expert  of the Euskampus Fundazioa, 2022.
• Member of Jurado del Premio Enrique Fuentes Quintana, 2020-2022.
• External expert  of ESF FWO–FRP, France, 2021. 
• External expert  of Junta de Andalucía, 2020-2021.
• External expert  of the Bulgarian National Science Fund, 2018-

Research interests

My research interests are in the fields of:

• Food image recognition by end-to-end learning
• Food intake monitoring by Deep learning
• Domain adaptation and multi-task learning
• Uncertainty modelling
• Life-logging and egocentric vision
• Event detection
• Object discovery
• Video segmentation and analysis
• Image segmentation
• Multi-class classification

Applications of Computer Vision and Machine Learning to Healthcare deserve special interest to me. In particular:

• Applying life-logging to Mild Cognitive Impairment patients.
• Applying life-logging to improve healthy habits of persons.
• Wireless endoscopy for intestine motility disorders diagnosis.
• Registration and retrieval of IVUS pullbacks for pre- post-intervention assessment.

Selected Recent Publications

Talks

Incoming:

• ICMV, 2’24, invited talk

Done:

• Keynote talk on “Data-centric Food Computing” invited to the Metafood Workshop, CVPR’2024.
• Invited talk on “Data-centric Food Computing”, CITIUS, Santiago de Compostela, 15 of July, 2024.
• Keynote talk on: “Inteligencia Artificial Aplicada a la Biomedicina” invited to the CEBUIC’2024, Barcelona, Spain.
• Jornada del Centre Català de la Nutrició de l’Institut d’Estudis Catalans “DELS INICIS A LA CONSOLIDACIÓ DE LA CARRERA INVESTIGADORA”, que tindrà lloc el 18 d’abril, 2024 a Barcelona.
• Invited talk to Congreso Multidisciplinar de Biomedicina (CEBUIC) que estamos organizando desde nuestra universidad del 2 al 4 de julio de 2024, en el campus de ciencias de la salud de Sant Cugat.
• Invitation by Societat Catalana de Física to give a talk on AI and applications, February 2024.

• Keynote lecture: “Data-centred Deep Learning Models for Food Fine-grained recognition”, VISAPP’2024, Rome, Italy, 28 of February, 2024.
• Keynote lecture: “What is common between Self-supervised learning and Food Fine-grained recognition?!” at the Iberoamerican conference on pattern recognition (CIARP) to be held in Coimbra (Portugal) between 27th-30th November 2023.
• Invited speaker “Deep Learning: A Swiss Army Knife or a Threat to Oncologists?” at the Workshop “AI meets Cancer” Research Symposium November 29 – 30, 2023 to be held in Sala d’actes, Vertex building, (UPC) in Barcelona, Spain.
• Keynote talk on the EIT Workshop “Training in Deep Tech: Best practices to build tomorrow’s talent”, https://www.eitdeeptechtalent.eu/news-and-events/events-archive/training-in-deep-tech-best-practices-for-tomorrow-talent/ 23 of November, Casa Milà (La Pedrera), Barcelona, Spain
• Invited talk “Deep learning: fundamentals, challenges and health applications” in Barcelona Supercomputing Center (BSC), 26 of October, 2023.
• Invited participation in the Round table on  “Reptes, bones pràctiques i problemàtiques en l’arribada de la tecnologia a la cura de la salut mental” at the 2a edition of the Technology Exploration Day, of TECSAM Network, 18/10/2023, 8:30-13h, UPF Business School of Management

• Invited lecture “AI, Deep learning and Visual recognition” at the Summer School on Data and Algorithms for Science, Technology & Innovation Studies, UB, Spain, 6-8 September 2023.
• Keynote lecture at CCVPR, Oxford University, UK, September 16, 2023.
• Keynote talk at the international conference “Mathematics Days in Sofia”, July 10th – 14th, 2023, the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences, in collaboration with the Union of the Bulgarian Mathematicians and the Faculty of Mathematics and Informatics at the Sofia University.
• Keynote lecture at the 12th International Conference on Pattern Recognition Applications and Methods (ICPRAM) – https://icpram.scitevents.org/, Lisbon, Portugal from 22 of February 2023.
• Keynote speaker for the CVIP 2022 7th IAPR International Conference on Computer Vision and Image Processing (CVIP2022) that will be tentatively organized on November 04-06, 2022 (Friday to Sunday) in Visvesvaraya National Institute of Technology (VNIT) Nagpur. India
• Invited Keynote Presentation at Women in Data Science 28.9.2022, Barcelona.
• Invited Keynote Presentation at S+SSPR Workshop, ICPR 2022, Montreal, Canada Aug. 26-27, 2022
• Invited talk at LatinX in AI Workshop, CVPR 2022, https://www.latinxinai.org/eccv-2022.
• Invited talk at the Summer school organized by the NHL Stenden University,  Leeuwarden, The Netherlands, 15-17 of June, 2022.
• Invited talk at the 12th International Conference on Pattern Recognition Systems (ICPRS) at MINES Saint-Etienne in France from June 7 to June 10, 2022.
• Keynote talk on “Deep Learning Models for Food Image Analysis”, ICRIC-2022 Springer approved fifth International Conference, 17 of May, 2022.
• Invited talk on “Computer vision & Deep learning. ¿Cómo nos pueden ayudar en el diagnóstico de precisión ante las diferentes pruebas diagnósticas?“, Congreso de la Sociedad Española del Transplante (SET), 13 of May, 2022, Malaga, Spain.
• Invited talk on “Addressing the food image challenge as a fine-grained recognition problem”, Decor@ICDE, 9 of May 2022, Kuala Lumpur, Malasia, online.
• Invited talk “Computer Vision and Deep Learning – Applications to Healthcare”, Cicle CERCA, “Dilluns de ciència” a la Residència d’Investigadors, 20.4.2022.
• Invited talk “Machine and Deep Learning – fundamentals and clinical applications” on the Advanced Stem Cell Technologies in Neurology (ITN-ASCTN) Conference, Brussels, Belgium, 4th of April 2022.
• Invited talk “Uncertainty modelling in deep learning. Applications to monitoring of healthy nutrition of people”, training school of VisuAAL ITN MSCA Network, Vienna, 24 of March 2021.
• Jornada SCM IDM 2022, Les matemàtiques de les imatges, “Fonaments de l’Aprenentatge Profund per l’Anàlisi d’imatges: aplicació al reconeixement d’aliments”, 18 of March 2022, online.
• Invited talk “¿Por qué me fascina la inteligencia artificial?”, within the 100tifiques (https://www.donesiciencia.cat/100tifiques/).“100tífiques” is an initiative of the Catalan Foundation for Research and Innovation (FCRI) and the Barcelona Institute of Science and Technology (BIST), in collaboration with the Department of Education of the Generalitat de Catalunya. On February 11, more than 150 simultaneous informative talks were given by more than 180 researchers from the business world and from research centers and universities (“100thes”) in 100 schools in Catalonia, mobilizing more than 15,000 6th and 1st year students of Primary ESO. The aim is to encourage the promotion of scientific and / or entrepreneurial vocations among girls, as well as to strengthen the connection and interaction of scientists and citizens, structuring two-way actions, 22 of February 2022.
• Invited talk to the International Symposium on Artificial Intelligence (ISAI 2022) February 17 – 19, 2022 at Haldia Institute of Technology (https://hithaldia.in/), Haldia-721657, West Bengal, India.
• Invited talk in the winter school of the project DATAETHICS (Leiden University Medical Center) (27 of January 2022), “Health data empowerment and artificial intelligence: ethical dilemmas, advantages and challenges”
• Invited talk on the development programme on “Application of Data Science” hold on December 13 to 17, 2021, School of Computer Science & Engineering (https://scse.xim.edu.in/), XIM University, Bhubaneswar, India.
• Keynote speaker on “Three ways of using uncertainty modeling to help Deep learning: Application to Food recognition”, during the IEEE ICECCO conference, 23-26 of November 2021.
• Invited talk “Machine Learning – fundamentals and applications” on the Summer school: “EXTREME: Modelling, Simulation and Artificial Intelligence in Colloid and Interface Science”, 22nd and 23rd of November, 2021 (online).
• Invited talks on: “Deep learning: Fundamentals and Applications” and “Object detection and segmentation, and Transfer Learning” in the Summer School “AI-Powered IoT for Building Smart Sustainable Signal Processing Applications”, 15^th – 19^th  November  2021 organised by the School of Electronics and Communication Engineering, MIT-WPU, Pune.

• Invited talk “How Food Recognition can leverage Uncertainty Modelling” to the ICCV Workshop “LargeFineFoodAI: Large-Scale Fine-Grained Food AnalysIs”, 16 October 2021.
• Women in Computer Vision, Invited talk to the Workshop Women in Computer Vision, 14 of October, 2021.
• XPatient Congress, «Com la Intel·ligència Artificial pot ajudar a millorar els hàbits nutricionals de les persones»,  28.09.2021, Barcelona, Spain, https://xpatientbcncongress.com/continguts-2021/.
• Invited talk “Shall Food recognition be the next challenge of Deep Learning” by the Asociación Española de Reconocimiento de Formas y Análisis de Imágenes (AERFAI), CEDI 2021,  (congresocedi.es) in Málaga, special session of AERFAI, 23 de Septiembre de 2021.
• Invited talk “Quantifying uncertainty in Deep learning models. Application to Food Recognition” to the Summer school MSCA Menelaos, Coruña, Spain, 22 of September, 2021.
• Invited talk “Puede el Aprendizaje Profundo ayudar a la gente comer más sano?”, to the AI & Big Data, 15 of September 2021, https://aicongress.barcelona/es/.
• Invited talk “Uncertainty Modelling and Deep Learning in Food Analysis” on the Summer school DeepLearn, Gran Canarias, 29 of July 2021.
• Invited talk  “Explainable and interpretable AI for transparentclinical decision making”, on the Summer school Dataethics, 17 of July 2021, Barcelona.
• Invited talk “What is common btw Negative Transfer, Uncertainty and Food Recognition?”, 7 of July, 2021, Delta’2021, (online).
• Invited talk “Why Data Science, Artificial Intelligence, Computer Vision and Deep Learning fascinate me?” on the conference Stanford Women in Data Science in Barcelona, 22 of June, 2021.
• Invited talk “Big Data – is my data the new oil?”, Barcelona 28 of April 2021. https://youtu.be/kdHILUFtaB4
• Invited talk “Computer Vision and Machine Learning at the University of Barcelona (CVML@UB)” at FW: Fòrum d’Intel·ligències Artificials – Deep learning meets Healthcare, Hospital Vall d’Hebron, 15 of April 2021.
• Invited talk “Uncertainty Modelling and Adversarial Networks Applied to Food Image AnalysiS” at ICMV’2020, 3.11.2020.
• Invited lecture on “Food Image Analysis by Deep Learning”  to India, 24.06.2020, as part of the 5 days FDP programme on “Recent Advances of Machine Learning and its Applications” organised by Amity University Kolkata, India.
• Invited lecture “How Deep Learning and Uncertainty Modeling can help people get aware how they eat” on the IV Workshop on Data and Knowledge Engineering (https://disc.cl/wdke), el cual forma parte de la XI Conferencia Internacional Infonor Chile 24.09.2020.(http://www.infonor2020.uda.cl/).
• Invited plenary talk on “Uncertainty ModeLling within an End-to-end Framework for Food Image Analysis”, DeLTA, Paris, France, 8 of July 2020.
• Invited talk on “Uncertainty modeLling for food analysis within end-to-end framework” the Summer school AI-DLDA, 29 of June, 2020, Udine, Italy.
• Invited plenary talk on “Applying Deep Learning for Food Recognition”, ITNT, Samara, Russia, 28 of May 2020.
• Invited plenary talk on “Uncertainty modelling within an End-to-end framework for Food Image Analysis” at Biostec, 13 of March, 2020, Valetta, Malta.
• Invited talk on “Uncertainty modelling within an End-to-end framework for Food Image Analysis” at the University of Groningen, The Netherlands, 13 of February, 2020.
• Invited plenary talk on “Uncertainty Modelling for Improving Food Recognition” at ICMV’2019, 16 of November, 2019, Amsterdam, The Netherlands.
• Invited talk “Uncertainty-Aware Food Recognition by Deep Learning” in the Data Council, Barcelona, Spain, 29 of September 2019.
• Invited inauguration talk on “Deep learning – science, technology or society solution?”, Faculty of Mathematics and Computer Science, Universitat de Barcelona, Spain, 25 of September, 2019.
• Invited talk on “Uncertainty-aware Food image analysis” at the University Kliment Ohridski”, Sofia Bulgaria, 19 of August 2019.
• Invited talk at the Barcelona.ai on “Uncertainty-aware Food image analysis”, 20 of June, 2019, Barcelona, Spain.
• Invited talk on “Uncertainty-aware CNNs. Application to food image analysis” at the University of Otago, New Zealand, 17 of April, 2019.
• Invited plenary talk “Uncertainty-awarefoodanalysisbyDeeplearning” at the Artificial Intelligence International Conference A2IC’2018, Barcelona, Spain, 22.11.2018.
• Open lecture on “Uncertainty-aware CNNs. Application to food image analysis” as a conclusion of the second edition of the Deep Learning for Artificial Intelligence course of Master MET, UPC, 17.12.2018.
• Invited talk on “Deep Learning and Computer Vision” at the Aula Magna, Lima, Peru, 5.11.18.
• Invited talk on “Uncertainty-aware food analysis by Deep learning” at the International Conference on Machine Vision, ICMV’2018, Munich, Germany, 2.10.2018.

• Invited course on “Advanced Computer Vision and Applications” given together with Dr. Jose Massa from INTIA, UNICEN, in CACIC’18, Tandil Argentina, 6-12 of October, 2018.
• Giving lecture on “Deep Learning aplicado al campo biomédico” in SEMINARIOS ABIERTOS DENTRO DEL CURSO DE EXPERTO UNIVERSITARIO DE LA UNIVERSIDAD DE BARCELONA: DATA SCIENCE (CIENCIA DE LOS DATOS): APLICACIONES A LA BIOLOGÍA Y A LA MEDICINA CON PYTHON Y R, 12 of July, 2018, Barcelona.
• Tutorial on “Deep learning and applications to activity recognition in egocentric photostreams“, 9.01.2018, Gran Canarias, Spain.
• Invited talk on “Visual Lifelogging: from egocentric images to neurorehabilitation” 26 of November, 2015, Master Lecture Announcement – EUSES Physiotherapy.
• Invited speaker at the ICMV’2015 Conference on: Deep learning and Lifelogging, 20 of November, 2015.
• Invited speaker at the DIPP’2015 Conference: Digital Presentation and Preservation of Cultural and Scientific Heritage, talk on “Visual Lifelogging in the Era of Outstanding Digitization“, Veliko Tarnovo, Bulgaria, 28 of September, 2015.
• Master thesis of Aniol Lidon on “Semantic and Diverse Summarization of Egocentric Photo Events“, 18 of September, 2015, Barcelona, Spain.
• Talk at CAIP 2015:
  • CAIP 2015 Introduction on Visual Lifelogging I part
  • CAIP 2015 Deep learning II part
  • CAIP 2015 TemporalSegmentation III part
  • CAIP 2015 Social interactions IV part
• Presentation at Bulgarian Academy of Science (BAN), “Object Discovery using CNN Features in Egocentric Videos”, Erasmus, August, 2015.
• Talk on Visual Lifelogging: using non‐medical images for medical purposes at the Universitat Rovira i Virgili, Tarragona, Spain, 29 of Juliol, 2015.
• Talk at CVPR’2015, Workshop on Medical imaging meets Computer Vision at the era of Big Data, Deep Learning and Novel Representations.
• Talk “Life-logging and egocentric vision” at IMEC, Holst Center, Eindhoven, 2015, The Netherlands.
• Talk
  “Visual Lifelogging: using non-medical images for medical purposes” during the

  PC meeting of MICCAI’2015, in Munich, May, 2015.

• Talk at the University of Groningen2014 during my visit to the University of Groningen, The Netherlands, 24th of November, 2014.
• Keynote speaker on “Talk Petia Radeva icmv2014“, of the 7th International Conference on Machine Vision, Milan, Italy, November 19-21, 2014.
• Invited tutorial at the AMDO’2014 conference. Talk: “Lifelogging: what’s it about?“, 18 of July, 2014, Palma de Mallorca, Spain, 1.5 hours.
• Invited talk organized within the European project “Advanced Computing for Innovation (Acommin). Topic: ”Video segmentation: applications to medical imaging and life-logging data”, January 14th 2014, Institute of information and communication technologies, bulgarian academy of sciences, Sofia, Bulgaria, 3 hours.
• Invited talk organized within the European project “Advanced Computing for Innovation (Acommin). Topic: ”Advanced course on Computer Vision”, 24 to 26 July 2013, Institute of information and communication technologies, bulgarian academy of sciences, Sofia, Bulgaria, 14 hours.

Team

PhD students:

• Ahmad Al Maghrabi, co-supervised with Ricardo Marques.
• Umair Haroon, co-supervised with Ricardo Marques.
• Muhammad Usman, , co-supervised with Daniel Ortiz.
• Daniel Vargas, co-supervised with Eduardo Aguilar.
• Martin Menchon, INTIA, UNICEN, Argentina co-supervised with Dr. Jose Massa.
• Federico Gonzalez, University of Ushuaya, Argentina, co-supervised with Dr. Estefania Talavera.
• Omar Dardour, co-supervised with Dr. Mourad Zaied.
• Changhui Hu, co-supervised with Ricardo Marques.
• Jesus Molina Rordiguez, UB.
• Imanol Gonzalez Estepa, UB.
• Javier Ródenas, UB.

PhD. Collaborators and Postdoc supervision:

• Eduardo Andrés Aguilar Torres, UB & Universidad Católica del Norte, Chile
• Ricardo Jorge Rodrigues Sepúlveda Marques, Lecturer, UB.
• Oliver Diaz, Associate professor, UB.
• Simone Balocco, Associate professor, UB.
• Kaisar Kushibar, Postdoc, UB.

• Bhalaji Nagarajan, UB.
• Athanasios Zoumpekas, UB.

External collaborations:

• Josep Maria Canals Coll, Director of Creatio, production and validation center for advanced therapies
• Gloria Menegaz, Associate professor, University of Verona, Italy.
• Jose Massa, Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina.
• Deep Gupta, Associate professor, Visvesvaraya National Institute of Technology, Nagpur, India.
• Estefania Talavera, University of Twente, The Netherlands.
• Maedeh Aghaei, Senior Researcher Lecturer at NHL Stenden, Leeuwarden, Netherlands.
• Mourad Zaied, Associate professor, National Engineering School of Gabes, Tunesia.

Supervised PhD thesis:

26. Bhalaji Nagarajan, “Mastering the Triad of Data, Models and Tasks in Deep Learning for Image Understanding”, 2024, Apto Cum Laude, Universitat de Barcelona, co-supervised with Dr. Eduardo Aguilar.

25. Martin Menchon, “Aprendizaje profundo aplicado a la identificación de rutinas”, Universidad Nacional del Centro de la Provincia de Buenos Aires, 2024, Tandil, Argentina.

24. Giuseppe Pezzano, “Optimization of neural networks for deep learning and applications to CT image segmentation”, 2023, Universitat de Barcelona, co-supervised with Dr. Vicent Ribas.

23. Ahmed Abdo Mahdi, “Brain age estimation”, 2022, University of Verona, Italy, co-supervised with Dr. Gloria Menegaz and Dr. Ilenia Gheno.

22. Marc Bolaños, “Deep multimodal learning for egocentric storytelling and food analysis”, 2021, Universitat de Barcelona.

21. Eduardo Aguilar, “Deep Learning and Uncertainty Modeling in Visual Food Analysis”, 2020, Universitat de Barcelona.

20. Alejandro Cartas, “Recognizing Action and Activities from Egocentric Images”, 2020, Universitat de Barcelona, co-supervised with Mariella Dimiccoli (UPC).

19. Margarida Torre, “Model-Based Segmentation of Images”, 2020, Universitat Autonoma de Barcelona, co-supervised with Fernando Martinez (UPC).

18. Estefania Talavera, “Lifestyle understanding through the analysis of egocentric photo-streams”, 2020, University of Groningen, co-supervised with Prof. Nikolai Petkov.

17. Mostafa Kamal Sarker, “Efficient Deep Learning Models and their Applications to”, 2019, URV, co-supervised with Prof. Domenec Puig.

16. Maedeh Aghaei, 2018, UB, co-supervised with Dr. Mariella Dimiccoli.

15. Felip Miralles, 2016, UB

14. Michal Drozdzal, 2014, UB

13. Marina Alberti, 2013, UB, co-supervised with Dr. Simone Balocco.

12. Francesco Ciompi, 2012, UB, co-supervised with Dr. Oriol Pujol.

11. Pierluigi Casale, 2011, UB, co-supervised with Dr. Oriol Pujol.

10. Sergio Escalera, 2009, UAB, co-supervised with Dr. Oriol Pujol.

9. David Rotger, 2008, UAB.

8. Fernando Vilariño, 2006, UAB.

7. Jaume Amores, 2006, UAB.

6. Ignacio Pulido, 2005, University of Zaragoza, co-supervised with Prof. Francisco Serón.

5. Misael Rosales, 2005, UAB

4. Debora Gil, 2004, UAB

3. Oriol Pujol, 2004, UAB

2. Cristina Cañero, 2003, UAB

1. Ricardo Toledo, 2002, UAB, co-supervised with Prof. Juanjo Villanueva.

Supervised Master and Undergraduate theses:

Ongoing:

• Sergio Rodríguez Llana, Master of Biomedical Data Science, 2024, cosupervised by Emily Diaz and Bhalaji Nagarajan.

Defended:

• Oscar Blazquez, cosupervosed by Ricardo Marques and Bhalaji Nagarajan, 2024, Grade: 10.
•  Adrian Galan Pacheco, TFG, 2024, cosupervised with Ahmad Almuchrabi, Grade: 10, With honors (Matricula de honor).
• María Ruiz Ávila, TFG, 2024, cosupervised by Maya Aghaei, Unversity of Lewarden, The Netherlands, Grade: 9.

• Anxo Pereira, Master of Biomedical Data Science, 2024.
• Marc Ballestero, TFG, UB, cosupervised by Agnes Perez and Roser Sala, 2024, With honors (Matricula de honor).
• Alejandro Argüello, TFM, AI, UPC-UB-URV, co-supervised by Joan Ribaudí Trull, 2024.
• Junjie Li, TFG, 2024, UB.
• Adrià Carrasquilla, TFM, AI, UPC-UB-URV, co-supervised by Maya Aghaei, 2023.
• Nazar Puryi, TFG, UB, 2023, cosupervised by Ricardo Marques, With honors (Matricula de honor).
• Andrey Nuñez, TFM, AI, UPC-UB-URV, cosupervised by Marc Bolaños, 2023.
• Joel Dieguez Vila, TFG, UB, 2023, cosupervised by Ricardo Marques, With honors (Matricula de honor).
• Ridouane Zaim Saikouk, 2023, TFG, UB, cosupervised by Marc Bolaños.
• Riccardo Smeriglio, TFM, co-supervised with Dr. Jordi Abante, 2023.
• Joana Rosell, TFM, co-supervised with Dr. Jordi Abante, 2023.

• Jesus Molina Rordiguez, TFM, UB, 2023, co-supervised with Bhalaji Nagarajan, Grace: 10.
• Imanol Gonzalez Estepa, TFM, UB, 2023, co-supervised with Bhalaji Nagarajan, Grace: 10.
• Pablo Villacorta Benito, TFM, UB, 2023, co-supervised with Javier Rodenas, Grade: 9.5.
• David Dueñas Gaviria, TFM, UB, 2022, co-supervised with Mostafa Kamal, Oxford University, UK, Grade: 9,5.
• Anabel Tingo Gamarra, TFM, UAB, 2021, co-supervised with Ricardo Marques.
• Chenxi Liu, 2020, TFM, co-supervised with Federico Gonzalez.
• Petar Tonchev, 2020, TFM, co-supervised with Javier Rodenas.
• Maria Madalenova, 2020, TFM, co-supervised with Javier Rodenas.
• Jordi Ventura, 2020, TFM, co-supervised with Javier Rodenas.
• Xavier Lopez, 2020, TFM, co-supervised with Javier Rodenas.
• Marc Asenjo, 2020, TFM, co-supervised with Eduardo Aguilar.

• Magi Toneu, 2020, TFM.
• Gerard Marrufat, 2019, TFM, co-supervised with Eduardo Aguilar.
• Carolin, Wuerich, 2019, TFM, co-supervised with Estefania Talavera.
• Santos Bringas, TFM, 2019.
• Emanuel Sanchez, TFM, 2018, co-supervised with Mariella Dimiccoli.
• Montserrat Brufau, TFM, 2018.
• Alex Ferrer, TFM, 2018.
• Markos Gavalas, 2018.
• Maria Leyva, TFM, 2017.
• Pedro Herruzo, TFM, 2017.
• Laura Portell, TFM, 2017.
• Alberto Soto, TFM, 2017.
• Emanuela Mollova, TFM, 2017.
• Chen Zang, BioHealth Master, co-supervised with Laura Igual (UB).
• Marc Bolaños, TFM, UB, 2014.
• Maedeh Aghaei, TFM, UB, 2013, etc.

…

Teaching

Currently, I’m teaching:

Computer Vision, a course for 3rd year students of Computer Science undergraduate study at the University of Barcelona.

Artificial Vision, a Master course for students of graduate study on Artificial Intelligence, UPC-UB-URV.

Advanced Medical Imaging, a Master course for students of graduate study on Biomedical Engineering.

Graduate course on Data science, UB.

Professional Service