After three years of on-line and hybrid conferences, the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) came back to an almost 100% in-person conference, held in Bruges (Belgium) with a great success of attendants and top-quality scientific contributions. IDAL member Prof. José D. Martín-Guerrero participated in the conference with the organization of the special session on Quantum Artificial Intelligence and with the presentation of a tutorial on this topic, on top of being part of the scientific committee, as usual. The special session was organized in collaboration with Prof. Lucas Lamata (Universidad de Sevilla, Spain), and Thomas Villmann (Mittweida University of Applied Sciences, Saxon Institute for Computational Intelligence and Machine Learning, Germany).
Conference of Prof. Sonia Pérez-Díaz
Next July 20, the professor of Mathematics of the UAH Sonia Pérez Díaz will give the lecture “Mathematics and Engineering: a holistic approach”, in the Conference Room of the ETSE-UV (Salón Pelechano). Mrs Sonia Pérez has a long experience teaching mathematics in Engineering, and she is a specialist in algebraic geometry applied to engineering. Algebraic geometry is a branch of mathematics that combines geometry and algebra to study, for example, the solutions of systems of equations or to understand the geometric structure of sets of points that satisfy these equations. In the context of engineering, algebraic geometry provides tools to describe and manipulate geometric shapes using equations, and therefore has multiple applications including the design and representation of curves and surfaces, the analysis of the behavior of curves and surfaces to the analysis of the behavior of curves and surfaces through asymptotics or asymptotes or the modeling of three-dimensional shapes.
Sonia Pérez Díaz is the first full professor in the Dept. of Physics and Mathematics at the University of Alcalá (2022). She received in 2021 the international prize “lnternational Partnership Award for Scientists of Chinese Academy of Sciences (Beijing, China)”, which was awarded for the first time to a woman and for the first time in the area of mathematics. With more than 80 publications and 4 scientific books, her participation in more than 20 competitive research projects and her more than 45 participations as speaker or organizer in national and international congresses and conferences. His main works are framed in the contributions obtained in the field of Algebraic Geometry, Symbolic Computation and, in general, in the foundations, algorithms and applications of algebraic curves and surfaces. The results obtained by Pérez Díaz have laid important foundations for numerous applications in the framework, for example, of computer-aided geometric design.
Dr. Wael El-Deredy gives a talk on Neuroscience
Dr. Wael El-Deredy, Professor of the Universidad de Valparaíso (Chile) gave an interesting talk last December 13th. It covered many different aspects of Neuroscience, from the analysis of brain oscillations and prediction of brain activity based on Markov chains to approaches related to a Bayesian brain, in which decisions (posterior probabilities) are given by the generation of the priors. Dr. El-Deredy gave many details about brain spectra, associated to different areas and tasks, and how they can even be intervened to modify behaviors, enabling patients with certain disorders to carry out activities for which in principle are unable. Happily, Dr. El-Deredy will join IDAL for the next four years as he was awarded with a postdoctoral contract funded by the Valencian Graduate School and Research Network of Artificial Intelligence (ValgrAI, https://valgrai.eu/).
Our dear colleague Oscar J. Pellicer-Valero got his PhD last November 14th, after an outstanding viva of his PhD research entitled “Contributions of biomechanical modeling and machine learning to the automatic registration of Multiparametric Magnetic Resonance and Transrectal Echography for prostate brachytherapy”. Oscar started his PhD in late 2018, and since then, has been working very hard on it, with the result of a remarkable thesis that has attracted interest both from the academic and clinical fields. The PhD thesis was presented as a compendium of five relevant publications corresponding with different parts of his research. Special thanks to Dr. Victor González-Pérez (Valencian Institute of Oncology, IVO) and Dr. Sandra Ortega-Martorell (Liverpool John Moores University, United Kingdom) who were the external examiners that were part of the panel, alongside IDAL member Dr. Yolanda Vives-Gilabert.
We wish Oscar the best of lucks in his post-doctoral career; IDAL will always be his home.
Prof. Enrique Solano visited IDAL from 12th to 14th July. Prof. Solano is a renowned contributor in the field of quantum computing, quantum information and quantum technologies. Some of his publications are globally accepted references in the field. He led research groups in different institutions, like Max Planck Institute for Physics, the University of the Basque Country or Shanghai University. He recently set up a startup company named Kipu Quantum (https://kipu-quantum.com/) with the goal of achieving quantum advantage making use of NISQ (Noisy Intermediate-Scale Quantum) Computing. During his stay, he had scientific discussions about disruptive ideas in the frontiers of Machine Learning and Quantum Computing and gave a presentation on his view to achieve quantum advantage with NISQ approaches.
On 16 June, from 9:00 am in the Assembly Hall of the School of Engineering of the University of Valencia (ETSE-UV), the conference on Data, Information and Knowledge will take place as part of the activities organised by the artificial intelligence research group IDAL and the Pagoda Chair, subsidised by the Regional Ministry of Participation, Transparency, Cooperation and Democratic Quality, to raise awareness of the latest trends among Valencian companies.
From a business point of view, experts from various fields will discuss how to make the transition from data to information and from there to knowledge. Without going any further, the amount of data collected in all areas, whether structured in the form of numbers or in the form of text and images, is growing all the time. However, having data does not mean having information, let alone knowledge.
The talks and round table discussions, given by both researchers and company technicians, will deal with medical, social, technological, public administration, tourism and open data topics, among others. Participants include, among others, the Diputación de Albacete, Valencia City Council, the Ministry of Defence, the University of Valencia, and the companies Zeus, Deepsense, Bosonit, Pangeanic and Ford Valencia. The full programme and access to registration, which is free of charge, can be consulted on the IDAL website (https://idal.uv.es/datos_6/).
The consortium formed by FORD, NUTAI and IDAL-UV has won the project MAPIIA: Advanced Monitoring of Industrial Processes through Artificial Intelligence (Monitorización Avanzada de Procesos Industriales Mediante Inteligencia Artificial) (Exp. INNEST/2021/362).
The Agència Valenciana de la Innovació (AVI), within the program of the action co-financed by the European Union through the Operational Program of the European Regional Development Fund (ERDF) of the Comunitat Valenciana 2014-2020 grants to the consortium formed by FORD, NUTAI and IDAL a subsidy to develop the MAPIIA project. This project of Advanced Monitoring of Industrial Processes through Artificial Intelligence (MAPIIA), framed in the Program of Strategic Projects in Cooperation, deals with the creation of a generic and multiplatform cyber-physical prototype digitization system, capable of monitoring and predicting failures in an industrialized environment through the use of advanced artificial intelligence techniques.
This project will enable the digitization of the critical points of a production line through the acquisition, processing and analysis of digitized data obtained from various types of equipment performing very different manufacturing operations. Through the analysis with Machine/Deep Learning and descriptive statistics techniques, valuable information will be extracted that will help, on the one hand, to make intelligent decisions in terms of failure prediction and, on the other hand, to plan work orders to carry out these maintenance tasks. In this way, the system will be able to help decision making to reduce costs in internal maintenance procedures in industrial plants, as well as to optimize the production process and improve the quality of the final product by predicting failures.
This project advances in the line of industrialization 4.0, which both FORD and NUTAI follow in their business strategy of innovation and development. On the other hand, the third partner, IDAL-Universitat de València, will reinforce the support in the Machine/Deep Learning area.
IDAL members collaborate on a research project on the topic “advanced monitoring of industrial processes using Artificial Intelligence”, financed by the ERDF funds of the Valencian Community. This project is devoted to the creation of a generic, cross-platform, cyber-physical prototype digitization system capable of monitoring and predicting faults in an industrialized environment using advanced artificial intelligence techniques.
The project started on June 2021 and will finish on June 2023.
The paper entitled ‘Single trajectory characterization via machine learning’ co-authored by IDAL member José D. Martín-Guerrero has been selected by the publisher as one the top five published in 2020 according to its quality, interest awakaned in readers, downloads and citations. The paper proposes a Machine Learning approach to accurately characterize single trajectories in diffusion mechanisms. The research was carried out in collaboration with the Research Institute for Photonic Sciences, ICFO.
IDAL member Prof. José D. Martín-Guerrero, and Prof. Dr. Lucas Lamata, from Universidad de Sevilla, are Guest Editors of a special issue in the journal Applied Sciences on Machine Learning and Physics. The deadline is 31st October 2021. We are welcoming original research papers, mini-reviews and perspective articles dealing with aspects in the fuzzy border between Physics and Machine Learning, particularly Quantum Machine Learning, Physics-inspired Machine Learning algorithms and applications of classical (and quantum) Machine Learning for different Physics applications. More info at https://www.mdpi.com/journal/applsci/special_issues/Machine_Learning_Physics.