Pablo Mesejo Santiago
CONTACT INFORMATION
Place/Date of Birth: A Coruña (Spain), 26-8-1981 Nationality: Spanish
Address: Office 1.10, Edificio Auxiliar, Escuela Técnica Superior de Ingenierías Informática y de Telecomunicación, Calle Periodista Juan Osorio Bueno, 18014 Granada, Spain
E-mail: [email protected]| [email protected] Telephone: +34 958241000 (ext. 20715)
Skype ID: pmesejo
ORCID: 0000-0001-9955-2101
ResearcherID: K-4589-2014 SCOPUS Author ID 37108185800
Webpage: https://www.ugr.es/~pmesejo/
EDUCATION
• 2013 – PhD in Computer Science at the Department of Information Engineering of the University of Parma (UniPR), Italy.
Marie Curie Researcher within the 7th Framework Program Initial Training Network MIBISOC: Medical Imaging using Bio- Inspired and Soft Computing (GA n. 238819). PhD Thesis: “Automatic Segmentation of Anatomical Structures using Deformable Models and Bio-Inspired/Soft Computing” (https://hal.inria.fr/tel-01363683). Final mark: 10.0/10.0 (Excellent).
PhD Thesis focused on the automatic segmentation of anatomical structures in biomedical images (mainly brain microscopy images, but also CT and brain T1-weighted MRI) using computer vision and artificial intelligence techniques. In particular, the main subject of the dissertation was the segmentation of brain structures by means of deformable models (active shape models, level set method), bio- inspired/soft computing (mainly swarm and evolutionary computation) and machine learning methods (ensemble classifiers).
I was 1 of the 16 researchers selected among more than 100 candidates for the MIBISOC project. Supervisor: Dr. Stefano Cagnoni. PhD committee: Óscar Cordón (University of Granada), Andrea Prati (University of Venice), and Leonardo Bocchi (University of Florence).
• 2010 – Postgraduate Degree in Bioinformatics: Genomics and Structural Biology (750 hours) at the Open University of Catalonia (UOC), Spain. Final Mark: A (Excellent).
The main tackled topics were the following: Fundamentals of Molecular Biology, Computational Genomics, Structural Biology, Functional Genomics and Microarray Data Analysis.
• 2009 – MSc in Computer Science at the University of A Coruña (UDC), Spain. Master Thesis: “Performance Optimization and Analysis of Neuron-glia Connectionist Systems”. Final mark: 10.0/10.0 (Excellent with Honors).
A comparative study between Artificial Neuron-Glia Networks and Artificial Neural Networks (Multi-Layer Perceptron) when solving classification problems was carried out, as well as the design and implementation of an optimization method for glial parameters using cooperative co-evolutionary genetic algorithms.
I obtained 1 of the 3 best marks among 26 computer scientists defending their Master Thesis dissertation in September 2009. Supervisors:
Dr. Ana Belén Porto (UDC) and Oscar Ibañez (European Center for Soft Computing). Master Thesis committee: Ricardo Cao Abad, Vicente Moret Bonillo, Daniel Rivero Cebrián, Xoán Carlos Pardo Pardo, and Francisco Javier Nóvoa de Manuel.
EMPLOYMENT HISTORY
• Since March 2021
Associate Professor at the Department of Computer Science and Artificial Intelligence (DECSAI) of the University of Granada1 (UGR, Spain).
• July 2020 – March 2021 (7.5 months)
Researcher at the SCI2S research group (Soft Computing and Intelligent Information Systems) of the UGR in collaboration with Dr.
Óscar Cordón, Dr. Sergio Damas, and Dr. Manuel Chica. My work is mainly related with the development and application of artificial intelligence techniques for understandable agent-based social simulation of complex marketing systems.
• April 2018 – May 2020 (2 years and 1 month)
Marie Curie Experienced Researcher at the SCI2S research group (Soft Computing and Intelligent Information Systems) of the UGR in collaboration with Dr. Óscar Cordón. Teaching Assistant of Machine Learning, Intelligent Systems Techniques, and Computational Forensics at the Department of Computer Science and Artificial Intelligence. My work is mainly related with the development and application of soft computing and computer vision techniques for comparative radiography in forensic identification. Marie Curie Standard Individual Fellowships, like the one I have, are highly competitive research grants that, in the H2020-MSCA-IF-2016 call, presented a 13.10% success rate. In turn, the UGR is one of the top institutions in computer science and engineering (ranked 1st in Spain and 33rd in the world according to the Academic Ranking of World Universities 2017). Co- founding partner and chief AI officer at Panacea Cooperative Research (an SME focused on finding intelligent solutions to solve unmet biomedical needs,www.panacea-coop.com, commercializing the Skeleton-ID software, www.skeleton-id.com).
• September 2016 – March 2018 (1 year and 7 months)
Starting Researcher Position at the PERCEPTION team (Interpretation and Modeling of Images and Videos) of Inria Grenoble Rhône-Alpes (France)2 in collaboration with Dr. Radu Horaud. My work was mainly related with the ERC Advanced Grant number
1The School of Computer Science of the University of Granada is commonly ranked as one of the top institutions in computer science in the world:
http://www.ugr.university/pages/ugr_news/rankings2016_2017
340113 entitled "Vision and Hearing In Action" (VHIA), and in particular with the integration of deep learning into probabilistic generative models for visual and audio recognition. My closest collaborators during this period were Radu Horaud, Stéphane Lathuilière, Xavier Alameda-Pineda, Benoit Massé and Sylvain Guy.
• September 2014 – August 2016 (2 years)
Postdoctoral researcher at the MISTIS team (Modeling and inference of complex and structured stochastic systems) of Inria Grenoble Rhône-Alpes in collaboration with Dr. Florence Forbes and Dr. Jan M. Warnking, working on the estimation of biophysical parameters from fMRI signals through evolutionary-based optimization to study brain function.
• September 2013 – July 2014 (11 months)
Postdoctoral researcher at the ALCoV team (Advanced Laparoscopy and Computer Vision) of the ISIT lab (Image Sciences for Interventional Techniques, UMR 6284 – CNRS) in the Faculty of Medicine of the University of Auvergne Clermont-Ferrand I (France). I have been working on deformable feature-based image registration and 3D measurement and characterization of neoplasias from endoscopic images under the supervision of Dr. Adrien Bartoli. My work was mainly carried out in collaboration with Adrien Bartoli, Daniel Pizarro, and Toby Collins.
• July 2010 – July 2013 (3 years)
Marie Curie Researcher at the IBISlab (Intelligent Bio-Inspired Systems laboratory) of the University of Parma (Italy) working on biomedical image segmentation under the supervision of Dr. Stefano Cagnoni. Member of the Network Supervisory Board of the MIBISOC Project (Medical Imaging using Bio-Inspired and Soft Computing). Teaching Assistant at the Department of Information Engineering. My closest collaborators during this period were Stefano Cagnoni, Roberto Ugolotti and Youssef S.G. Nashed.
• February 2010 – May 2010 (4 months)
Research Assistant at the ATIS Group (Advances in Telemedicine and Health Informatics) of the University Hospital Complex of A Coruña (Spain) working on software development using Microsoft Office Sharepoint Server 2007.
• May 2006 – December 2007 (1 year and 8 months)
Research Assistantat the RNASA group (Artificial Neural Networks and Adaptive Systems) within a project for the Research Service of the University Hospital Complex of A Coruña working on medical image registration (in particular 2D polyacrylamide gel electrophoresis).
RESEARCH INTERESTS
Machine Learning; Computer Vision; Deep Learning; Biomedical Image Analysis; Computational Intelligence; Artificial Intelligence in Medicine and Biology; Stochastic Optimization; Metaheuristics.
My research career is devoted to analyze and design machine learning, computer vision and computational intelligence methods able to solve, mainly but not exclusively, biomedical image analysis problems. Typical tools I use in my research are stochastic optimization algorithms, deep and shallow neural networks, and ensemble classifiers. Throughout my career I have faced numerous challenging problems, like the automatic segmentation of anatomical structures in biomedical images (PhD at University of Parma, performed with a Marie Curie fellowship), the classification of gastrointestinal lesions from endoscopic videos (postdoc at University of Auvergne Clermont-Ferrand I), the estimation of biophysical parameters from fMRI signals (postdoc at Inria), and the integration of deep learning into probabilistic generative models for visual and audio recognition in human-robot interaction (starting researcher position at Inria), among others.
PUBLICATIONS
SCI-JCR indexed journal papers
Gómez, G., Mesejo, P., and Cordón, Ó., “Cascade of convolutional models for few-shot automatic cephalometric landmarks localization”, submitted to Engineering Applications of Artificial Intelligence (IF2021: 7.802 (Q1), 27th/144 in subject
2Inria is one of the top institutions in computer science (http://archive.sciencewatch.com/inter/ins/08/08octTOP20COM/) and mathematics
category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, 8th/65 in subject category AUTOMATION &
CONTROL SYSTEMS)
Fernández-Moreno, M., Lei, B., Holm, E.A., Mesejo, P., and Moreno-Salinas, R., “Exploring the trade-off between performance and annotation complexity in semantic segmentation”, submitted to Engineering Applications of Artificial Intelligence (IF2021: 7.802 (Q1), 27th/144 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, 8th/65 in subject category AUTOMATION & CONTROL SYSTEMS)
Bi, Y., Xue, B., Mesejo, P., Cagnoni, S., and Zhang, M., “A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, Future Trends and Challenges”, submitted to IEEE Transactions on Evolutionary Computation (IF2021: 16.497 (Q1), 5th/144 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, 2nd/109 in subject category COMPUTER SCIENCE, THEORY & METHODS)
Vargas-Pérez, V.A., Mesejo, P., Chica, M., and Cordón, Ó., “Deep reinforcement learning in agent-based simulations for optimal media planning”, submitted to Information Fusion (IF2021: 17.564 (Q1), 1st/109 in subject category COMPUTER SCIENCE, THEORY & METHODS, and 4th/144 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Venema, J., Peula, D., Irurita, J., and Mesejo, P., “Employing deep learning for sex estimation of adult individuals using 2D images of the humerus”, accepted for publication at Neural Computing and Applications (IF2021: 5.102 (Q1), 45th/189 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Bermejo, E., Fernández-Blanco, E., Mesejo, P., Valsecchi, A., and Ibáñez, Ó., “A deep learning approach for the estimation of subject-to-camera distance in facial photographs”, accepted for publication at Expert Systems with Applications (IF2021:
8.665 (Q1), 21st/144 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, 8th/87 in subject category OPERATIONS RESEARCH & MANAGEMENT SCIENCE, 23rd/276 in subject category ENGINEERING, ELECTRICAL
& ELECTRONIC)
Luengo, J., Moreno, R., Sevillano, I., Charte, D., Peláez, A., Fernández, M., Mesejo, P., and Herrera, F., “A tutorial on the segmentation of metallographic images: taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges”, Information Fusion 78, 232-253, Elsevier, February – 2022 (IF2020: 12.975 (Q1), 1st/110 in subject category COMPUTER SCIENCE, THEORY & METHODS, and 3rd/140 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Bermejo, E., Imaizumi, K., Taniguchi, K., Ogawa, Y., Martos, R., Valsecchi, A., Mesejo, P., and Ibáñez, O., “Automatic landmark annotation in 3D skulls: methodological proposal and reliability study”, Computer Methods and Programs in Biomedicine 210, 106380, Elsevier, October – 2021(IF2020: 5.428 (Q1), 19th/90 in subject category ENGINEERING, BIOMEDICAL, 5th/30 in MEDICAL INFORMATICS, 22nd/112 in COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS, and 13th/110 COMPUTER SCIENCE, THEORY & METHODS)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., and Cordón, Ó., “Deep architectures for the segmentation of frontal sinuses in X-Ray images:
towards an automatic forensic identification system in comparative radiography”, Neurocomputing 456, 575-585, Special Issue on "Hybrid Artificial Intelligent Systems", Elsevier, October – 2021 (IF2020: 5.719 (Q1), 30th/139 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Fernández, R., Estévez, E.J., Irurita, J., and Mesejo, P., “Analysis of the performance of machine learning and deep learning methods for sex estimation of infant individuals from the analysis of 2D images of the ilium”, International Journal of Legal Medicine 135, 2659-2666, Springer, July – 2021 (IF2020: 2.686 (Q1), 4th/17 in subject category MEDICINE, LEGAL) Lathuilière, S., Mesejo, P., Alameda-Pineda, X., and Horaud, R., “A Comprehensive Analysis of Deep Regression”, IEEE
Transactions on Pattern Analysis and Machine Intelligence 42 (9), 2065-2081, IEEE, September – 2020 (IF2020: 16.389 (Q1), 1st/139 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, 2nd/273 in subject category ENGINEERING, ELECTRICAL & ELECTRONIC)
Mesejo, P., Martos, R., Ibáñez, Ó., Novo, J., and Ortega, M., “A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-based Forensic Human Identification”, Applied Sciences 10 (14), 4703, Special Issue "Computer-aided Biomedical Imaging 2020: Advances and Prospects", Multidisciplinary Digital Publishing Institute, July – 2020 (IF2020:
2.679 (Q2), 73rd/160 in subject category PHYSICS, APPLIED; Q2, 38th/90 in subject category ENGINEERING, MULTIDISCIPLINARY; Q3, 101st/178 in subject category CHEMISTRY, MULTIDISCIPLINARY; Q3, 201st/334 in subject category MATERIALS SCIENCES, MULTIDISCIPLINARY)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., “Deep architectures for high-resolution multi-organ chest X-ray image segmentation”, Neural Computing & Applications 32, 15949–15963, Special Issue on "Recent Advances in Deep Learning for Medical Image Processing and Health Informatics", Springer, October – 2019 (IF2019: 5.606 (Q1), 31st/139 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Valsecchi, A., Irurita, J., and Mesejo, P., “Age estimation in forensic anthropology: methodological considerations about the validation studies of prediction models”, International Journal of Legal Medicine 133, 1915–1924, Springer, May – 2019 (IF2019: 2.222 (Q1), 4th/17 in subject category MEDICINE, LEGAL)
Lathuilière, S., Massé, B., Mesejo, P., and Horaud, R., “Neural Network based Reinforcement Learning for Audio-Visual Gaze Control in Human-Robot Interaction”, Pattern Recognition Letters, Special Issue on “Cooperative and Social Robots:
Understanding Human Activities and Intentions”, volume 118, 61-71, Elsevier, February – 2019 (IF2019: 3.255 (Q2), 46th/139 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Mesejo, P., Pizarro, D., Abergel, A., Rouquette, O., Beorchia, S., Poincloux, L., and Bartoli, A., “Computer-Aided Classification of Gastrointestinal Lesions in Regular Colonoscopy”, IEEE Transactions on Medical Imaging 35 (9), 2051-2063, IEEE, September – 2016 (IF2016: 3.942 (Q1), 10th/77 in subject category ENGINEERING, BIOMEDICAL, 17th/127 in category RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING, 4th/26 in subject category IMAGING SCIENCE &
PHOTOGRAPHIC TECHNOLOGY, 36th/262 in subject category ENGINEERING, ELECTRICAL & ELECTRONIC, and 3rd/105 in subject category COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS)
Mesejo, P., Ibáñez, O., Cordón, O., and Cagnoni, S., “A Survey on Image Segmentation using Metaheuristic-based Deformable Models: State of the Art and Critical Analysis”, Applied Soft Computing 44, 1-29, Elsevier, July – 2016 (IF2016: 3.541
(Q1), 21st/133, category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, and 14th/105, category COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS)
Mesejo, P., Saillet, S., David, O., Bénar, C., Warnking, J., and Forbes, F., “A Differential Evolution-based Approach for Fitting a Nonlinear Biophysical Model to fMRI BOLD Data”, IEEE Journal of Selected Topics in Signal Processing 10 (2), 416- 427, IEEE, March – 2016 (IF2016: 5.301 (Q1), 18th/262, category ENGINEERING, ELECTRICAL & ELECTRONIC) Mesejo, P., Valsecchi, A., Marrakchi-Kacem, L., Cagnoni, S., and Damas, S., “Biomedical Image Segmentation using Geometric
Deformable Models and Metaheuristics”, Computerized Medical Imaging and Graphics 43, 167-178, Elsevier, July – 2015 (IF2015: 1.385 (Q3), 51st/76 in subject category BIOMEDICAL ENGINEERING and 93rd/124 in RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING)
Mesejo, P., Ibáñez, O., Fernández-Blanco, E., Cedrón, F., Pazos, A., and Porto-Pazos, A., “Artificial Neuron-Glia Networks Learning Approach Based On Cooperative Coevolution”, International Journal of Neural Systems 25 (4): 1550012, World Scientific, April – 2015 (IF2015: 6.085 (Q1), 2nd/130 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Ugolotti, R.*, Mesejo, P.*, Zongaro, S., Bardoni, B., Berto, G., Bianchi, F., Molineris, I., Giacobini, M., Cagnoni, S., and Di Cunto, F., ”Visual search of neuropil-enriched RNAs from brain in situ hybridization data through the image analysis pipeline Hippo-ATESC”, PLoS ONE 8 (9): e74481.doi:10.1371/journal.pone.0074481, Public Library of Science, September – 2013 (IF2013: 3.534 (Q1), 8th/55 in subject category MULTIDISCIPLINARY SCIENCES) *These authors contributed equally to this work.
Ugolotti, R., Nashed, Y.S.G., Mesejo, P., Ivekovič, S., Mussi, L., and Cagnoni, S., “Particle Swarm Optimization and Differential Evolution for Model-based Object Detection”, Applied Soft Computing 13 (6), 3092-3105, Elsevier, June – 2013 (IF2013:
2.679 (Q1), 20th/121 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Mesejo, P., Ugolotti, R., Di Cunto, F., Giacobini, M., and Cagnoni, S., “Automatic Hippocampus Localization in Histological Images using Differential Evolution-Based Deformable Models”, Pattern Recognition Letters 34 (3), 299-307, Elsevier, February – 2013 (IF2013: 1.062 (Q3), 71st/121 in subject category COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Porto-Pazos, A.B., Veiguela, N., Mesejo, P., Navarrete, M., Alvarellos, A., Ibáñez, O., Pazos, A., and Araque, A., “Artificial Astrocytes Improve Neural Network Performance”, PLoS ONE 6 (4): e19109, Public Library of Science, April – 2011 (IF2011: 4.092 (Q1), 12th/85 in subject category BIOLOGY)
Conference papers
Garzón, I., Mesejo, P., and Giráldez, J., “A methodology for the evaluation of realistic SAT instance generators”, submitted to the 37th AAAI Conference on Artificial Intelligence (AAAI’23) (GGS Rating A++; CORE A++)
Villar, M., Valsecchi, A., and Mesejo, P., "Forensic Human Identification from Facial and Cranial Images using Deep Learning", accepted for oral presentation at the 75th Annual American Association of Forensic Sciences (AAFS) Scientific Conference, Orlando (USA), February 13-18, 2023
Sánchez-Múñoz, C., Mesejo, P. and Damas, S., "Forensic Identification using Craniofacial Superimposition: Estimation of Facial Soft Tissue Depth using Machine Learning Techniques", accepted for oral presentation at the 75th Annual American Association of Forensic Sciences (AAFS) Scientific Conference, Orlando (USA), February 13-18, 2023
Gómez, G., Lathuilière, S., Mesejo, P., and Cordón, Ó., “Custom Structure Preservation in Face Aging”, accepted at the 17th European Conference on Computer Vision (ECCV'22), Tel Aviv (Israel), October 23-27, 2022 (CORE2021 A++, GGS rating A++, acceptance rate ~28%)
Garzón, I., Mesejo, P., and Giráldez, J., "On the performance of deep generative models of realistic SAT instances", 25th International Conference on Theory and Practice of Satisfiability Testing (SAT’22), Haifa (Israel), August 2-5, 2022 (GGS Rating A; CORE A)
Núñez-Molina, C., Mesejo, P., and Fernández-Olivares, J., “A Proposal to Generate Planning Problems with Graph Neural Networks”. ICAPS 2022 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL’22), June 13-24, 2022 (GGS Rating A; CORE A++)
Peula, D., Venema, J., Irurita, J., and Mesejo, P., "Evaluación del uso de técnicas de IA para el diseño de métodos de diagnóstico del perfil biológico en antropología forense: resultados de estimación del sexo de adultos en una muestra de origen mediterráneo", International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'21), November 17-19, 2021
Lathuilière, S., Guy, S., Mesejo, P., and Horaud, R., “Learning Visual Voice Activity Detection with an Automatically Annotated Dataset”, 25th International Conference on Pattern Recognition (ICPR'20), Milan (Italy), January - 2021 (CORE2018 B, GGS rating A-, first round acceptance rate ~30%)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., “A real-coded evolutionary algorithm-based registration approach for forensic identification using the radiographic comparison of frontal sinuses”, 22nd IEEE Congress on Evolutionary Computation (IEEE CEC’20), Glasgow, July-2020 (CORE2018 B, GGS rating A-)
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., Cerezo, A., Pérez, J.M., Alemán, I., and Cordón, Ó., "Automatic segmentation of skeletal structures in X-ray images using deep learning for comparative radiography", accepted for oral presentation at 9th Annual Congress of the International Society of Forensic Radiology and Imaging (ISFRI'20), Albuquerque (USA), May 14- 16, 2020. Cancelled due to COVID-19. 2020 ISFRI Prize
Gómez, Ó., Ibáñez, Ó., Mesejo, P., Valsecchi, A., Cerezo, A., Pérez, J.M., Alemán, I., and Cordón, Ó., "Towards a computer-aided decision support system for comparative radiography", accepted for oral presentation at 9th Annual Congress of the International Society of Forensic Radiology and Imaging (ISFRI'20), Albuquerque (USA), May 14-16, 2020. Cancelled due to COVID-19.
Ibáñez, Ó., Corbal, I., Gómez, I., Gómez, Ó., González, A., Macías, M., Prada, K., Valsecchi, A., and Mesejo, P., "Skeleton-ID:
Artificial Intelligence at the service of Forensic Anthropology", 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Gómez, Ó., Ibáñez, Ó., Mesejo, P., Valsecchi, A., and Cordón, Ó., “Towards a computer-aided decision support system for comparative radiography”, 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Gómez, G., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., "Automatic localization of cephalometric landmarks using convolutional networks", 11th International Scientific Meeting of the Spanish Association of Forensic Anthropology and Odontology (AEAOF'19), Pastrana (Spain), November 8-9, 2019
Irurita, J., Valsecchi, A., Mesejo, P., and Alemán, I., “Improvement of a method for estimating dental age in children through the use of learning algorithms”, 21st Congress of the Spanish Society of Physical Anthropology (SEAF’19), Granada (Spain), June 24-26, 2019
Vladimirova, M., Verbeek, J., Mesejo, P., and Arbel, J., “Bayesian neural network priors at the level of units”, 12th International Conference on Bayesian Nonparametrics (BNP’12), Oxford (UK), June – 2019
Vladimirova, M., Verbeek, J., Mesejo, P., and Arbel, J., “Understanding Priors in Bayesian Neural Networks at the Unit Level”, International Conference on Machine Learning (ICML'19), Long Beach (USA), June - 2019 (CORE2018 A*, GGS rating A++, acceptance rate ~23%)
Fernández, E., Valsecchi, A., Ibáñez, Ó., and Mesejo, P., “Estimating subject-to-camera distance in facial images using Deep Learning”, accepted for a Podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re- organized then as "IACI 2019 Online Symposium"
Gómez, Ó., Mesejo, P., Ibáñez, Ó., Valsecchi, A., and Cordón, Ó., “Automatic segmentation of skeletal structures in x-ray images using deep learning: Towards a computer-aided decision support system for comparative radiography”, accepted for a Podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium"
Urdín, D., Mesejo, P., Ibáñez, Ó., Valsecchi, A., Guyomarc'h, P., and Coqueugniot, H., “Facial Soft Tissue Depth Estimation using Machine Learning Techniques”, accepted for a Podium presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium"
Gómez, G., Mesejo, P., Ibáñez, Ó., and Valsecchi, A., “Automatic Cephalometric Landmarks Localization using Deep Convolutional Neural Networks”, accepted for a Poster presentation at the 18th Biennial Meeting of the International Association of Craniofacial Identification (IACI) July 13-17, 2019 in Baton Rouge, Louisiana, USA. Canceled due to Tropical Storm Threat, and re-organized then as "IACI 2019 Online Symposium"
Massé, B., Lathuilière, S., Mesejo, P., and Horaud, R., “Extended Gaze-Following: Detecting Objects in Videos Beyond the Camera Field of View”, accepted at the 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG'19), Lille (France), May - 2019 (CORE2018 C, GGS rating A-, oral presentation acceptance rate ~20%)
Vladimirova, M., Arbel, J., and Mesejo, P., “Bayesian neural networks become heavier-tailed with depth”, 3rd Bayesian Deep Learning NIPS 2018 Workshop, Montréal (Canada), December - 2018
Vladimirova, M., Arbel, J., and Mesejo, P., “Bayesian neural network priors at the level of units”, 1st Symposium on Advances in Approximate Bayesian Inference, Montréal (Canada), December - 2018
Lathuilière, S., Massé, B., Mesejo, P., and Horaud, R., “Deep Reinforcement Learning for Audio-Visual Gaze Control”, 31st IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'18), 1555-1562, Madrid (Spain), 2018 (CORE2018 A, GGS rating A+,acceptance rate ~47%)
Lathuilière, S., Mesejo, P., Alameda-Pineda, X., and Horaud, R., “DeepGUM: Learning Deep Robust Regression with a Gaussian- Uniform Mixture Model”, 15th European Conference on Computer Vision (ECCV’18), Munich, September - 2018 (CORE2018 A, GGS rating A+,acceptance rate ~25%)
Lathuilière, S., Juge, R., Mesejo, P., Muñoz-Salinas, R., and Horaud, R., "Deep Mixture of Linear Inverse Regressions Applied to Head-Pose Estimation", 28th IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'17), 7149- 7157, Honolulu, 2017 (CORE2017 A, GGS rating A++,acceptance rate ~30%)
Mesejo, P., Saillet, S., David, O., Bénar, C., Warnking, J., and Forbes, F., “Estimating Biophysical Parameters from BOLD Signals through Evolutionary-based Optimization”, 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'15), Part II, 528-535, Munich, 2015 (CORE2015 A, GGS rating A,acceptance rate ~30%) Collins, T., Mesejo, P., and Bartoli, A., “An Analysis of Errors in Graph-based Keypoint Matching and Proposed Solutions”, 13th
European Conference on Computer Vision (ECCV’14), 138-153, Zürich, 2014 (CORE2014 A, GGS rating A+,acceptance rate ~25%)
Valsecchi, A., Mesejo, P., Marrakchi-Kacem, L., Cagnoni, S., and Damas, S., “Automatic Evolutionary Medical Image Segmentation using Deformable Models”, 16th IEEE Congress on Evolutionary Computation (CEC’14), 97-104, Beijing, July-2014 (CORE2014 B, GGS rating A-)
Ugolotti, R., Mesejo, P., Nashed, Y.S.G., and Cagnoni, S., “GPU-based Automatic Configuration of Differential Evolution: a case study”, 16th Portuguese Conference on Artificial Intelligence (EPIA’13), Progress in Artificial Intelligence, Lecture Notes in Computer Science Volume 8154, 114-125, Azores, 2013 (acceptance rate ~25%)
Mesejo, P., Cagnoni, S., Costalunga, A., and Valeriani, D., “Segmentation of Histological Images using a Metaheuristic-based Level Set Approach”, 15th Genetic and Evolutionary Computation Conference companion (GECCO’13), 1455-1462, Amsterdam, July – 2013 (CORE2013 A, GGS rating A)
Ugolotti, R., Nashed, Y.S.G., Mesejo, P., and Cagnoni, S., “Algorithm Configuration using GPU-based Metaheuristics”, 15th Genetic and Evolutionary Computation Conference companion (GECCO’13), 221-222, Amsterdam, July – 2013 (CORE2013 A, GGS rating A)
Mesejo, P. and Cagnoni, S., “An experimental study on the automatic segmentation of in situ hybridization-derived images”, 1st International Conference on Medical Imaging using Bio-Inspired and Soft Computing (MIBISOC’13), 153-160, Brussels, May – 2013
Fernández-Lozano, C., Seoane, J.A., Mesejo, P., Nashed, Y.S.G., Cagnoni, S., and Dorado, J., ''2D-PAGE Texture Classification Using Support Vector Machines and Genetic Algorithms'', 6th International Joint Conference on Biomedical Engineering
Systems and Technologies: International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC’13), 5-14, Barcelona, February – 2013 (full paper acceptance rate ~15%)
Nashed, Y.S.G., Mesejo, P., Ugolotti, R., Dubois-Lacoste, J., Cagnoni, S., “A comparative study of three GPU-based metaheuristics”, 12th International Conference on Parallel Problem Solving from Nature (PPSN’12), 398-407, Taormina, September – 2012 (CORE2012 A, GGS rating A-, acceptance rate ~45%)
Nashed, Y.S.G., Ugolotti, R., Mesejo, P., Cagnoni, S., “libCudaOptimize: an Open Source Library of GPU-based Metaheuristics”, 14th Genetic and Evolutionary Computation Conference companion (GECCO’12), 117-124, Philadelphia, July – 2012 (CORE2012 A, GGS rating A)
Cagnoni, S., Cordón, O., Mesejo, P., Nashed, Y.S.G., Ugolotti, R., “First Results and Future Developments of the MIBISOC Project in the IBISlab of the University of Parma”, 14th Genetic and Evolutionary Computation Conference companion (GECCO’12), 509-516, Philadelphia, July – 2012 (CORE2012 A, GGS rating A)
Mesejo, P., Ugolotti, R., Di Cunto, F., Cagnoni, S., and Giacobini, M., “Automatic Segmentation of Hippocampus in Histological Images of Mouse Brains using Deformable Models and Random Forest”, 25th IEEE International Symposium on Computer- Based Medical Systems (CBMS’12), 1-4, Rome, June – 2012 (GGS rating B, acceptance rate ~50%)
Romero-Porta, F., Mesejo P., Ibáñez O. and Porto-Pazos, A. B., “Optimización mediante Computación Evolutiva de la interacción Neurona-Astrocito en Redes Neurogliales Artificiales”, 8th Congreso Español sobre metaheurísticas, algoritmos evolutivos y bioinspirados (MAEB’12), Albacete, February – 2012
Ugolotti, R., Mesejo, P., Cagnoni, S., Giacobini, M., and Di Cunto, F., “Automatic Hippocampus Localization in Histological Images using PSO-based Deformable Models”, 13th Genetic and Evolutionary Computation Conference companion (GECCO’11), 487-494, Dublin, July – 2011 (CORE2011 A, GGS rating A)
Mesejo, P., Fernández-Blanco, E., Seoane, J. A., Ruiz-Romero, C., Dorado, J., Blanco, F. J., “2D-PAGE image analysis using Evolutionary Computation”, 8th Spanish Symposium on bioinformatics and computational biology, Valencia, 88-91, February – 2008
Book chapters
Martos, R., Ibáñez, Ó., and Mesejo, P., "Artificial Intelligence in Forensic Anthropology: state of the art and Skeleton-ID project", Methodological and Technological Advances in Forensic Science: Application and Case Studies, Edited by Ann H. Ross and Jason Byrd, In Press, 2022
Fernández-Lozano, C., Seoane, J.A., Mesejo, P., Nashed, Y.S.G., Cagnoni, S., and Dorado, J., "Texture Classification of Proteins Using Support Vector Machines and Bio-Inspired Metaheuristics", Biomedical Engineering Systems and Technologies, Communications in Computer and Information Science, 117-130, 2014
Mesejo, P., Fernández-Blanco, E., Martínez Feijóo, D., Blanco, F. J., “2D-PAGE Analysis using Evolutionary Computation”, Encyclopedia of Artificial Intelligence, Idea Group, 1583-1588, ISBN: 978-1-59904-849-9, 2008
Non SCI-JCR indexed journal papers
Gómez, Ó., Mesejo, P., and Ibáñez, Ó., “Automatic segmentation of skeletal structures in x-ray images using deep learning for comparative radiography”, accepted at Forensic Imaging, Elsevier, 2021
Ibáñez, Ó., Martos, R., and Mesejo, P., "Inteligencia Artificial en Antropología Forense: estado del arte, retos y oportunidades", Revista Internacional de Antropología y Odontología Forense / International Journal of Forensic Anthropology and Odontology, Volume 3, Number 2, pages 6-41, July – 2020
Ibáñez, Ó., Alemán, I., Bermejo, E., Corbal, I., Cordón, Ó., Damas, S., Gómez, G., Gómez, I., Gómez, Ó., González, A., Macías, M., Martos, R., Mesejo, P., Panizo, M., Prada, K., and Valsecchi, A., "El proyecto Skeleton-ID: hacia una identificación humana más rápida, objetiva y precisa", Revista Internacional de Antropología y Odontología Forense / International Journal of Forensic Anthropology and Odontology, Volume 3, Number 2, pages 71-88, July – 2020
Mesejo, P., “Soft computing and computer vision for comparative radiography in forensic identification”
,
The Project Repository Journal 5, 12-15, April – 2020Mesejo, P., “Automatic Segmentation of Anatomical Structures using Deformable Models and Bio-Inspired/Soft Computing”, Electronic Letters on Computer Vision and Image Analysis, Volume 13, Number 2, 2014
Seoane, J. A., Mesejo, P., Ruiz-Romero, C., Dorado, J., Pazos, A., Blanco, F. J., “Diagnóstico por imagen en reumatología: de la imagen radiológica a la imagen molecular”, I + S: Informática y Salud, Sociedad Española de Informática y Salud, 62: 9- 17, ISSN: 1579-8070, April – 2007
Teaching training publications
Giráldez, J., Mesejo, P., Segura, J., Fernández, J., and González., A., “Herramientas de gamificación para la enseñanza de técnicas de búsqueda heurística en entornos dinámicos” (“Gamification tools for teaching heuristic search techniques in dynamic environments”), accepted at XXVII Jornadas sobre la Enseñanza Universitaria de la Informática (JENUI 2021).
HONORS, MEMBERSHIPS AND AWARDS:
- ICCV 2017 Outstanding Reviewer Award: http://iccv2017.thecvf.com/files/ICCV_2017_Main_Conference.pdf
- ISFRI 2020 Prize for the paper Gómez et al., "Automatic segmentation of skeletal structures in X-ray images using deep learning for comparative radiography"
- American Academy of Forensic Sciences (AAFS) Associate Member (since 2022). Section: Digital & Multimedia Sciences.
- Marie Curie Individual Fellowship 2016: selected as Marie Curie Experienced Researcher by the European Commission (mark of 99.6 out of 100) for the SKELETON-ID project. Marie Curie Standard Individual Fellowships are highly competitive research grants that, in the H2020-MSCA-IF-2016 call, presented a 13.10% success rate.
- Marie Curie Early Stage Fellow 2010: 1 of the 16 Early Stage Researchers selected among more than 100 applicants to the MIBISOC project (“Medical Imaging using Bio-Inspired and Soft Computing”, MIBISOC ITN GA 238819).
- MSc Thesis evaluated as Excellent with Honors: 1 of the 3 best marks among 26 computer scientists defending their Master Thesis dissertation in September 2009.
- Vice-chair of the IEEE Computational Intelligence Society Task Force on Evolutionary Computer Vision and Image Processing:
https://homepages.ecs.vuw.ac.nz/~alsahahari/ieee-cis-tf-ecvip/(Chair from 2018 to 2021, 4 years)
- Member of the IEEE Computational Intelligence Society Task Force on Evolutionary Deep Learning and Applications: https://yn- sun.github.io/ieeecis_edl.html
- Member of the Andalusian Research Institute DaSCI "Data Science and Computational Intelligence": https://dasci.es/. Chair of the Machine Learning and Image Processing track. Co-organizer of DaSCI seminars and Andalusian lectures.
OTHER CONTRIBUTIONS Official Academic Documents
PhD Thesis: “Automatic Segmentation of Anatomical Structures using Deformable Models and Bio-Inspired/Soft Computing”.
Supervisor: Stefano Cagnoni. Grade: Excellent (10.0/10.0). University of Parma. Finished: July-2013. Defense: March-2014.
Master Thesis: “Optimización y Análisis del Rendimiento de Sistemas Conexionistas NeuroGliales”. Supervisors: Ana Belén Porto Pazos y Óscar Ibáñez Panizo. Grade: Excellent (10.0/10.0). (Spanish: Matrícula de Honor): 1 of the 3 best grades among 26 computer scientists defending their Master Thesis dissertation in September 2009 at the School of Computer Science of the University of A Coruña. Defense: September-2009.
Academic Reviewer and Supervisor Current
PhD Thesis Co-Supervisor (together with Óscar Cordón García): Guillermo Gómez Trenado (“Disruptive approximations to forensic human identification using deep learning”). Becas de Formación de Profesorado Universitario 2019 (2019 FPU Scholarship)
PhD Thesis Co-Supervisor (together with Raúl Moreno Salinas): Marta Fernández Moreno (“Deep learning approaches for image analysis in metallography”). Industrial PhD 2020 – UGR and ArcelorMittal
PhD Thesis Co-Supervisor (together with Julián Luengo): Adrián Peláez Vegas (“Deep learning-based approaches for semantic segmentation in industrial problems”). Industrial PhD 2020 – UGR and ArcelorMittal
PhD Thesis Co-Supervisor (together with Juan Fernández Olivares): Carlos Núñez Molina (“Integrating machine learning and automated planning for goal and actions recommendation”)
PhD Thesis Co-Supervisor (together with Sergio Damas Arroyo): Práxedes Martínez Moreno (“New methods based on Artificial Intelligence for forensic human identification using craniofacial superimposition”)
PhD Thesis Co-Supervisor (together with Óscar Ibáñez Panizo): Javier Venema Rodríguez ("Computer vision and machine learning techniques for the biological profile estimation of dead and living individuals"). Industrial PhD 2022 - UGR and Panacea
MSc Thesis Co-Supervisor (together with Marilyn Bello): Andrés Herrera Espino (“Layer-wise relevance propagation in deep neural networks for instance segmentation”).
MSc Thesis Co-Supervisor (together with Marilyn Bello): Alejandro Alonso Membrilla (“Explainable models for deep reinforcement learning”).
BSc Thesis Co-Supervisor (together with Jesús Giráldez): Laura Sánchez Parra (“Learning graph entropy with graph neural networks”). Double Degree in Mathematics and Computer Science
BSc Thesis Co-Supervisor (together with Guillermo Gómez Trenado and Javier Merí de la Maza): Alejandro Borrego Megías (“Few- shot cephalometric landmark localization”). Double Degree in Mathematics and Computer Science
BSc Thesis Co-Supervisor (together with Guillermo Gómez Trenado and Javier Merí de la Maza): Sergio Quijano Rey (“Age- invariant person re-identification”). Double Degree in Mathematics and Computer Science
BSc Thesis Co-Supervisor (together with Guillermo Gómez Trenado and Javier Merí de la Maza): Carlos Lara Casanova (“Tensor analysis of convolutional neural networks and its application to the estimation of the location of cephalometric landmarks and their visibility”). Double Degree in Mathematics and Computer Science
BSc Thesis Co-Supervisor (together with Jesús Giráldez): Israel Puerta Merino (“Hybridizing heuristic search, automatic planning and constraint satisfaction problems for general video game playing”)
BSc Thesis Co-Supervisor (together with Marilyn Bello): Sergio Fernández Vela (“Explainable AI techniques applied to images for forensic human identification”).
BSc Thesis Co-Supervisor (together with Enrique Bermejo): Jesús Álvarez Fernández (“Automatic segmentation of panoramic dental radiographies using deep learning and explainability techniques”)
BSc Thesis Co-Supervisor (together with Enrique Bermejo): Brian Sena Simons (“Biomedical 3D image quality assessment using machine learning”)
BSc Thesis Co-Supervisor (together with Óscar Cordón): José Antonio López Palenzuela (“Age estimation from dental radiographs using deep learning”).
BSc Thesis Co-Supervisor (together with Marilyn Bello): Pablo García Sánchez (“Explainable AI techniques for multi-view deep neural networks”).
Past
MSc Thesis Co-Supervisor (together with Marilyn Bello): Pablo Costa Contreras ("Explaining Siamese Neural Architectures from Local Perturbations on the Embedding Layer: Methodological Proposal and Experimental Validation on Facial Recognition"). Master in Physics and Mathematics. Defended the 16th of September 2022 at the University of Granada. Final Mark: 10.0/10.0 (with Honors)
MSc Thesis Co-Supervisor (together with Javier Irurita): Javier Venema Rodríguez ("Age estimation in forensic anthropology using deep learning and 3D images of the ribs"). Defended the 14th of September 2022 at the University of Granada. Final Mark:
10.0/10.0 (with Honors)
BSc Thesis Co-Supervisor (together with Enrique Bermejo): Ángel Cabeza Martín ("Generation of 3D facial models from photographs: feasibility study in forensic environments"). Defended the 14th of September 2022 at the University of Granada. Final Mark: 9.6/10.0
BSc Thesis Co-Supervisor (together with Sergio Damas Arroyo): Valentino Lugli ("Automatic classification of morphological criteria for age estimation using 3D scans of the pubic symphysis"). Defended the 13th of September 2022 at the University of Granada. Final Mark: 10.0/10.0 (with Honors)
BSc Thesis Co-Supervisor (together with Andrea Valsecchi): Mario Villar Sanz ("Forensic identification based on face and skull photographies using deep learning"). Defended the 13th of September 2022 at the University of Granada. Final Mark:
9.65/10.0
BSc Thesis Co-Supervisor (together with Jesús Giráldez Crú): Alejandro Palencia Blanco (“The SAT problem: Stochastic local search heuristics using deep learning techniques and analysis of the computational complexity of its proof systems”). Double Degree in Mathematics and Computer Science. Defended the 7th of September 2022 at the University of Granada. Final Mark: 9.41/10.0
MSc Thesis Co-Supervisor (together with Sergio Damas Arroyo): Carlos Sánchez Muñoz (“Forensic human identification by means of craniofacial superimposition: estimation of soft tissue thickness using machine learning techniques”). UGR Scientific Initiation Scholarship. Defended the 21st of July 2022 at the University of Granada. Final Mark: 9.22/10.0
BSc Thesis Co-Supervisor (together with Óscar Cordón García and Óscar Gómez López): Alejandro Manzanares Lemus (“Age estimation from 3D models of the pubic symphysis using deep learning”). Defended the 20th of July 2022 at the University of Granada. Final Mark: 9.65/10.0
MSc Thesis defense panel (Master in Computer Science), together with Sergio Damas Arroyo and Juan Julián Merelo Guervós. 20th of July, 2022. MSc Theses evaluated: 3
BSc Thesis defense panel (BSc in Computer Science), together with Patricia Paderewski Rodríguez and Juan Francisco Valenzuela Valdés. 14th of July, 2022. BSc Theses evaluated: 5
PhD examining board member for the PhD dissertation of Miguel López Pérez entitled "Probabilistic Methods for Image and Signal Classification. Applications to Medicine and Volcanology" (12/07/2022, University of Granada)
MSc Thesis Co-Supervisor (together with Jesús Giráldez Crú): Iván Garzón Segura (“Methodology for the Evaluation of Realistic SAT Instance Generators”). UGR Scientific Initiation Scholarship. Defended the 28th of January 2022 at the University of Granada. Final Mark: 9.3/10.0
BSc Thesis Co-Supervisor (together with Andrea Valsecchi): Pedro Jesús Del Río Rot (“Integration and Analysis of an Automatic Craniofacial Superimposition System for Forensic Human Identification”). Defended the 23rd of November 2021 at the University of Granada. Final Mark: 9.5/10.0
BSc Thesis defense panel (BSc in Computer Science), together with María José Rodríguez Fórtiz and Juan José Ramos Muñoz. 23rd of November, 2021. BSc Theses evaluated: 3
PhD examining board member for the PhD dissertation of David Fuentes Jiménez entitled "Reconstruction of deformable objects from images by means of deep learning" (08/11/2021, University of Alcalá)
MSc Thesis defense panel (Master in Data Science and Computer Engineering), together with Miguel Molina Solana and Miguel García Silvente. 16th of September, 2021. MSc Theses evaluated: 4
BSc Thesis Supervisor: Alejandro Pinel Martínez (“Neural architecture search techniques for the automatic design of convolutional networks. Application to the classification of gastrointestinal lesions”). Defended the 13th of September 2021 at the University of Granada. Final Mark: 9.4/10.0
BSc Thesis defense panel (BSc in Computer Science), together with Francisco Javier Melero Rus and Juan Julián Merelo Guervós.
20th of July, 2021. BSc Theses evaluated: 5
BSc Thesis Co-Supervisor (together with Javier Irurita): Javier Venema Rodríguez (“Biological profile estimation in forensic anthropology using deep learning techniques. Application to sex estimation in adult individuals from images of the humerus bone”). Defended the 21st of July 2021 at the University of Granada. Final Mark: 9.3/10.0
BSc Thesis Co-Supervisor (together with Óscar Cordón García): José María Sánchez Guerrero (“Memetic algorithms for the estimation of biophysical parameters in functional MRI”). Defended the 15th of July 2021 at the University of Granada. Final Mark: 9.5/10.0
PhD examining board member for the PhD dissertation of Anastasiia Safonova entitled "Plant Species Detection in Aerial and Satellite Images using Deep Learning" (30/06/2021, University of Granada)
MSc Thesis Co-Supervisor (together with Inmaculada Alemán Aguilera): Vanessa Velásques Peláez (“Approximation to the use of maxilary sinuses in human forensic identification processes by means of imaging techniques”). Defended the 4th of December 2020 at the University of Granada. Final Mark: 9.7/10.0
BSc Thesis Co-Supervisor (together with Jesús Giráldez Crú): Melani Álvarez Santos (“Deep Learning techniques applied to the resolution of constraint satisfaction problems”). Double Degree in Mathematics and Computer Science. Defended the 18th of September 2020 at the University of Granada. Final Mark: 7.0/10.0
BSc Thesis defense panel (Double Degree in Mathematics and Computer Science), together with Carlos Ureña Almagro and Domingo Barrera Rosillo. 17th of September, 2020. BSc Theses evaluated: 3
BSc Thesis Co-Supervisor (together with Javier Irurita): Raúl Fernández Ortega (“Biological profile estimation in forensic anthropology from osseous images using deep learning”). Defended the 16th of July 2020 at the University of Granada. Final Mark: 9.9/10.0
BSc Thesis Co-Supervisor (together with Jesús Giráldez Crú): Iván Garzón Segura (“Generation of realistic SAT instances using deep learning”). Defended the 16th of July 2020 at the University of Granada. Final Mark: 9.0/10.0
BSc Thesis Supervisor: Jesús Moyano Doña (“Comparative study of methods for the classification of gastrointestinal lesions in endoscopic videos”). Defended the 15th of July 2020 at the University of Granada. Final Mark: 9.6/10.0
BSc Thesis Co-Supervisor (together with Óscar Cordón García): Ángel Rodríguez Hódar (“Comparative study of real-coded metaheuristics for the estimation of biophyisical parameters in fMRI”). Defended the 14th of July 2020 at the University of Granada. Final Mark: 9.0/10.0
MSc Thesis defense panel (Master in Data Science and Computer Engineering), together with Luis M. de Campos and Jesús Garrido.
10th of July, 2020. MSc Theses evaluated: 4
MSc Thesis Co-Supervisor (together with Óscar Cordón García): Guillermo Gómez Trenado (“Image Restauration using Non- Adversarial Networks. Towards a deeper semantic understanding of images”). Defended the 8th of July 2020 at the University of Granada. Final Mark: 9.9/10.0 (with Honors)
MSc Thesis external reviewer and defense panel member. Title: “Deep Robust Regression using Student-t Distribution”. Student:
Álvaro González Jiménez. Supervisors: Dr. Xavier Alameda Pineda & Dr. Stéphane Lathuilière. MoSIG M2. Grenoble Institute of Technology (Grenoble-INP). Defended the 26th of June 2020.
PhD Co-Supervisor (together with Óscar Cordón and Óscar Ibáñez): Óscar David Gómez López ("Soft Computing and Computer Vision for Forensic Identification by means of Comparative Radiography"). Defense date: 17th of January 2020.
Mark: Sobresaliente Cum Laude.
MSc Thesis defense panel (Master in Data Science and Computer Engineering), together with Luis M. de Campos and Jesús Garrido.
30th of January, 2020. MSc Theses evaluated: 3
Industrial supervisor of Mr. Jesús Moyano Doña as intern in Panacea. Project: “Automatic Testing of 3D/2D Web Graphical Environments” (Oct-2019 to Jan-2020)
Research stay supervisor of the visiting scholar Alexsandro Vasconcellos Da Silva. PhD student in Cellular and Molecular Biology at the Pontifical Catholic University of Rio Grande do Sul (Brazil). Subject of the research stay: analysis of facial morphology for forensic facial comparison (Aug-2019 to Dec-2019)
MSc Thesis Co-Supervisor (together with Inmaculada Alemán): Melisa Silva Vega (“Forensic Identification using Medical Images:
Evaluation of techniques for radiological identification using clavicles”). Defended the 19th of September 2019 at the University of Granada. Final Mark: 9.0/10.0
MSc Thesis Co-Supervisor (together with Inmaculada Alemán): José Manuel Pérez Jiménez (“Study of the discriminatory power of frontal sinuses in CTs”). Defended the 19th of September 2019 at the University of Granada. Final Mark: 9.8/10.0 (with Honors)
MSc Thesis Co-Supervisor (together with Inmaculada Alemán): Andrea Cerezo Vallecillo (“Relevance of frontal sinuses in human identification processes by means of imaging techniques”). Defended the 4th of July 2019 at the University of Granada. Final Mark: 10.0/10.0 (with Honors)
BSc Thesis Co-Supervisor (together with Óscar Cordón): Guillermo Gómez Trenado ("Deep Learning and Forensic Anthropology:
revision of the state-of-the-art and application to the localization of cephalometric landmarks"). UGR Scientific Initiation Scholarship. Defended the 25th of June 2019 at the University of Granada. Final Mark: 10.0/10.0 (with Honors)
MSc Thesis Co-Supervisor (together with Xavier Alameda-Pineda): Vadim Sushko (“Gaze Estimation and Gazeable Objects”).
Defended the 25th of June 2019 at ENSIMAG (École nationale supérieure d'informatique et de mathématiques appliquées de Grenoble). Final Mark: 17.5/20
BSc Thesis Supervisor: Sergio Martín de la Higuera ("Automatic recognition of knee prosthetic implants in X-ray images using deep learning "). Defended the 26th of June 2019 at the University of Granada. Final Mark: 9.38/10
BSc Thesis defense panel (BSc in Computer Science), together with Raúl Pérez Rodríguez and Marcelino Cabrera Cuevas. 27th of June, 2019. BSc Theses evaluated: 5
MSc Thesis Co-Supervisor (together with Óscar Ibáñez): David Urdín ("Estimation of the soft tissue thickness in the head for applications in forensic anthropology"). Defended the 24th of September 2018 at the University of Granada. Final Mark:
9.4/10
MSc Thesis Co-Supervisor (together with Óscar Ibáñez): Daniel Muñoz ("Segmentation of facial anatomical regions in photographs using Deep Learning"). Defended the 17th of September 2018 at the University of Granada. Final Mark: 9.2/10
MSc Thesis Co-Supervisor (together with Julyan Arbel): Mariia Vladimirova ("Wide limit of deep Bayesian neural networks ").
Defended the 22nd of June 2018 at ENSIMAG (École nationale supérieure d'informatique et de mathématiques appliquées de Grenoble). Final Mark: 15.5/20
MSc Thesis Co-Supervisor (together with Pedro Javier Herrera Caro): Carlos Otero López ("Automatic Segmentation of X-Ray Images of Knee Prosthetic Implants"). Defended the 2nd of October 2017 at National University of Distance Education (UNED). Final Mark: 8/10.
MSc Thesis Co-Supervisor (together with Radu Horaud): Sylvain Guy ("Visual Voice Activity Detection in the Wild"). Defended the 23rd of June 2017 at ENSIMAG (École nationale supérieure d'informatique et de mathématiques appliquées de Grenoble).
Final evaluation: 17.5/20
PhD examining board member for the PhD dissertation of Sebastián Bronte entitled "Real Time Sequential Non Rigid Structure from Motion Using a Single Camera" (11/07/2017 at the University of Alcalá)
Reviewer for the PhD dissertation entitled: “Automatic body communication extraction through markerless motion capture” (PhD candidate: Alvaro Marcos Ramiro. PhD student at the Electronics Department of University of Alcala, under the supervision of Marta Marron Romera, Daniel Pizarro-Perez, and Daniel Gatica Perez. Defense date: June 17th, 2014)
Reviewer for the PhD dissertation entitled: “Correction of Errors in Time of Flight Cameras” (PhD candidate: David Jimenez Cabello. PhD student at the Electronics Department of University of Alcala, under the supervision of Daniel Pizarro-Perez and Manuel Mazo-Quintas. Defense date: February 13th, 2015)
Technology Transfer
- Co-founding partner and chief AI officer of Panacea Cooperative Research (an SME focused on finding intelligent solutions to solve unmet biomedical needs): http://www.panacea-coop.com/index.php/es/ Panacea is a UGR spin-off and member of the Data Science and Computational Intelligence Innovation Hub (DaSCII Hub). It was founded in August 2017, and started its economic activity in the second trimester of 2018. Main commercialized product: Skeleton-ID (https://skeleton-id.com/).
- Patent of invention: "Procedimiento de identificación de imágenes óseas". Inventors: Óscar David Gómez López; Óscar Ibáñez Panizo; Pablo Mesejo Santiago; Óscar Cordón García; Sergio Damas Arroyo; Andrea Valsecchi. Universidad de Granada.
Application No.: P201831303. Application date: 29/12/2018. Priority Country: Spain, USA (No. 17/418,878) and Europe (No. 19856455.1). Owning Institution: University of Granada. Exploitation rights: Panacea Cooperative Research S. Coop.
Web: https://patentscope.wipo.int/search/es/detail.jsf?docId=ES297287223&_fid=WO202013630
- Patent of invention: "Sistema de análisis de imágenes para la comparación facial forense". Inventors: Rubén Martos Fernández;
Óscar Ibáñez Panizo; Andrea Valsecchi; Pablo Mesejo Santiago; Alexsandro Vasconcellos da Silva; Fernando Navarro Merino; Inmaculada Alemán Aguilera; Óscar Cordón García; Sergio Damas Arroyo. Universidad de Granada & Panacea Cooperative Research. Nº of application: P202030191. Country of inscription: Spain, Andalusia. Registration Date:
06/03/2020. Priority Country: Spain and Europe (Nº 21764501.9). PCT number application: PCT/ES2021/070162. PCT application date: 05/03/2021. PCT submission number: PCT/ES2021/070162. PCT submission date: 05/03/2021.
International application number: WO 2021/176126. Owning Institutions: Panacea Cooperative Research S. Coop. (50%), University of Granada (50%).
Web:
https://patentscope.wipo.int/search/ar/detail.jsf;jsessionid=02B1D0460862DA7305AD24A59B9C3BAA.wapp2nA?docId=W O2021176126&_cid=P20-KTLUIW-14894-12
- Patent of invention: "Procedimiento de identificación forense mediante comparación automática de modelo 3D del cráneo y fotografía(s) de la cara". Inventors: Óscar Ibáñez Panizo; Andrea Valsecchi; Enrique Bermejo Nievas; Rubén Martos Fernández; Pablo Mesejo Santiago; Práxedes Martínez Moreno; Guillermo Gómez Trenado; Óscar Cordón García; Sergio Damas Arroyo; Rosario Guerra Martí; Inmaculada Alemán Aguilera. Universidad de Granada & Panacea Cooperative Research. Nº of application: P202130618. Country of inscription: Spain, Andalusia. Registration Date: 02/07/2021. Priority Country: Spain. Owning Institutions: Panacea Cooperative Research S. Coop. (50%), University of Granada (50%).
- BOLD model FIT software protected by the French Software Protection Agency (APP), 20/07/2016. ID number:
IDDN.FR.001.300022.000.S.P.2016.000.31230
- CAPRE (Computer-Aided Polyp Recognition) software protected by the French Software Protection Agency (APP), 25/08/2015.
ID number: IDDN.FR.001.350029.000.S.P.2015.000.31230
- 7 software packages developed by me and my colleagues can be found at https://github.com/Stephlat/DeepRegression (Deep Regression for Computer Vision), https://team.inria.fr/perception/research/dmlir/ (Deep Mixture of Linear Inverse Regressions), https://hal.inria.fr/hal-01221115v2 (fMRI BOLD Data Model Parameter Estimation), https://hal.inria.fr/hal- 01221316/file/CODES.zip (Hybrid Level Set Segmentation Framework), https://github.com/tobycollins/GAIM (Graph-based Affine Invariant Matching), http://ibislab.ce.unipr.it/project.php?invioID=13 (Hippocampus Localization in Brain Histological Images), and http://ibislab.ce.unipr.it/software/libcudaoptimize/doxygen/ (Bio-Inspired Global Optimization Toolbox).
Posters, Seminars and Invited Talks
Invited Talk "Deep Learning meets Forensic Anthropology: applications, challenges and future trends", Andalusian Research Institute in Artificial Intelligence (DaSCI), DaSCI monthly lectures, 20th of December 2022
Invited Talk "Biological Profile Estimation using Deep Learning Techniques", Panacea Cooperative Research, 13th and 15th of December 2022
Informational Talk (together with Guillermo Gómez) “Machines that learn by themselves”, European Researchers’ Night, Granada, 30-September-2022
Invited Talk "Computer vision and machine learning applications (mainly) in the field of biomedical image analysis", University College London, Molecular Bionics Group, 18-October-2021
Informational Talk (together with Guillermo Gómez) “Machines that learn by themselves”, European Researchers’ Night, Granada, 24-September-2021
Informational Talk (together with Guillermo Gómez) “Machines that learn by themselves. The example of deep neural networks for image analysis”, European Researchers’ Night, https://www.youtube.com/watch?v=glUC3rnyZYs, Granada, 27-November- 2020
Informational Talk “Deep Learning. Successes (and limitations) of the last revolution (and hype) in artificial intelligence”, Week of Science, Colegio Internacional de Granada, Dílar, 6-March-2020
Dissemination Activity for Kids (together with Rubén Martos) “Discovering our bones”, VII Jornadas de la Ciencia, CEIP Fuentenueva, Granada, 31-January-2020
Invited Poster Presentation “Skeleton-ID: Soft Computing and Computer Vision for Comparative Radiography in Forensic Identification”, MSCA AI cluster, Brussels, 10/11-December-2019
Informational Talk “Deep Learning. Successes (and limitations) of the last revolution (and hype) in artificial intelligence”, Week of Science, Granada, 13-November-2019
Informational Talk “Forensic Identification” (together with Andrea Valsecchi), Week of Science, Granada, 13-November-2019 Informational Talk “Deep Learning. Successes (and limitations) of the last revolution (and hype) in artificial intelligence”, European
Researchers’ Night, Granada, 27-September-2019
Informational Talk “Deep Learning. Successes (and limitations) of the last revolution (and hype) in artificial intelligence”, Week of Science, Granada, 15-November-2018
Informational Talk “Forensic Identification” (together with Andrea Valsecchi and Sergio Damas), Week of Science, Granada, 15- November-2018
Conference Poster: “Estimating biophysical parameters from BOLD signals through evolutionary-based optimization”, 18th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'15), Munich, 6- October-2015
Invited Talk "Metaheuristics for model-based object segmentation", Laboratoire Jean Kuntzmann, Grenoble, 26-March-2015 Invited Talk "Evolutionary-based Optimization of Nonlinear Models for fMRI Data", Grenoble Institute of Neurosciences, La
Tronche, 23-February-2015
Seminar “Computer-aided Decision Support Systems for Endoscopy in Gastroenterology: Current and Future Works”, University Hospital Estaing, Clermont-Ferrand, 24-February-2014
