Success at the ANDI-Challenge

During the last months, I have been participating in the ANDI Challenge, together with my Ph.D. student Óscar Garibo. Since Albert Einstein provided a theoretical foundation for Robert Brown’s observation of the movement of particles within pollen grains suspended in water, significant deviations from the laws of Brownian motion have been uncovered in a variety of animate and inanimate systems, from biology to the stock market. Anomalous diffusion, as it has come to be called, is connected to non-equilibrium phenomena, flows of energy and information, and transport in living systems.

The challenge consists of three main tasks, each of them on 3 Dimensions:

  • Task 1 – Inference of the anomalous diffusion exponent α.
  • Task 2 – Classification of the diffusion model.
  • Task 3 – Segmentation of trajectories.

We got the first position in Task 1 (1D) and the second position in Task 2 (1D). We also get the 3rd position in Task 2 (3d) and the 4th position in Task 2 (2D).

Full professor position at UPV

On November 12th, I got the position of Full Professor at the Dept. of Applied Mathematics of UPV. It has been a long and winding trip of almost 22 years since I started my PhD. I did not think about this when I started. I did not dream of it. I neither consider it as the measure of academic success.

After getting the tenure position in 2009, I did not think about it for some time. However, 8 years ago I simply thought one day: Maybe I can get it, why not? Essentially, it is to keep on working day after day and getting more results. And I started to keep on working even at night or before dawn. Later, three years ago in the lobby of a hotel in Boston, reading the new criteria for becoming a full professor I thought, I absolutely will get it.

Many people have asked me if I am happier or if I have celebrated. Truth be told that happiness only lasted some days, later you return to your daily tasks and almost forget it. Besides, celebrations are very limited in these strange times, so almost anything has changed in my life after it.

Does it worth all the time invested? I honestly do not know. I enjoyed quite a lot during the path, but for the things you meet along the way, not because of the position, and to be focused on the path you missed many things. You can never have it all and you have to decide.

 

 

Investigadores de la UPV trabajan en la lucha contra la COVID-19 a través de la Ciencia de Datos

We Alberto Conejero (Instituto Universitario de Matemática Pura y Aplicada, IUMPA) and Miguel Rebollo (of the Valencian Research Institute for Artificial Intelligence, VRAIN) of UPV are part of the Data Science Working Group in the Fight against COVID-19 , of the Commissioner for the Presidency of the Generalitat Valenciana on Strategy for Artificial Intelligence and Data Sciences against COVID-19. News appeared in UPV, in El Periodic newspaper and in RUVID website.

Data Science Group COVID-19 (Comunitat Valenciana)

Since April 2020, I have been involved in the Data Science Group COVID-19 of the València Region under the supervision of Nuria Oliver. This is a multidisciplinary team of volunteers that work side by side with the General Director of Analysis and Public Policies of the Presidency of the RValencia Region Government. The analysis for COVID-19 is coordinated with the Ministry of Health and the rest of the Councils involved. This working group is led by Nuria Oliver, Commissioner of the Presidency of the Generalitat for the Valencian Strategy for Artificial Intelligence and, especially, for the coordination of data intelligence before the COVID-19 epidemic in the Valencia Region.

They are part of the group of experts from the Jaume I University, the University of Valencia, the Polytechnic University of Valencia, the Miguel Hernández University, the University of Alacant, the CEU Cardenal Herrera University, Fisabio, and Microsoft, with the collaboration of Esri, the INE, the Secretary of State for Artificial Intelligence and the three most important mobile phone companies in the country.

This group is divided into three priority areas with their respective work coordinators: (1) analysis, visualization, and modeling of mobility data, (2) epidemiological models and (3) data science applied to COVID-19. There, I work in epidemiological models with Antonio Falcó, Miguel Rebollo, Miguel A. Lozano, Emilio Sansano, Xavier Barber, and Francisco Escolano.

This is the web page of our data research group http://infocoronavirus.gva.es/es/grup-de-ciencies-de-dades-del-covid-19-de-la-comunitat-valenciana

Paper published in JAMIA: Potential limitations in COVID-19 machine learning due to data source variability: a case study in the nCov2019 dataset

The lack of representative COVID-19 data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, where source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. In this work, we used the publicly available nCov2019 dataset, including patient level data from several countries. We aimed to the discovery and classification of severity subgroups using symptoms and comorbidities.

In our work published in JAMIA, we have shown that cases from the two countries with the highest prevalence were divided into separate subgroups with distinct severity manifestations. This variability can reduce the representativeness of training data with respect the model target populations and increase model complexity at risk of overfitting. We conclude that data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.
Our analysis tool developed within BDSLab at UPV can be found at http://covid19sdetool.upv.es/?tab=ncov2019

Grant concession from BBVA fund SARS-CoV-2 and COVID-19

On September 30th, 2020 we have received funding for the project Ciencias de Datos e Inteligencia Artificial contra el COVID-19, IA4COVID19, from Fundación BBVA among more than 150 proposals presented to the call in the category: Big Data e Inteligencia Artificial (“Data-IA-COVID-19”). This proposal has been lead by the data research scientist Nuria Oliver from Ellis Alicante. The initiative, is linked to the Valencian Strategy in Artificial Intelligence.

Our project is a collaborative work that we have developed voluntarily and altruistically since the beginning of the crisis caused by the pandemic, professors from Valencian universities. The research entitled «Data science against Covid-19» brings together the participation of civil society (through a citizen survey), experts from the academic-research environment, and public administration, with the aim of providing information so that the those responsible for public crisis management can make informed decisions based on scientific evidence obtained from data analysis. In particular, I collaborate in the epidemiological models part and as head of the UPV node together with Miguel Rebollo from the VRAIN Institute. The initiative, linked to the Valencian Strategy in Artificial Intelligence through the commissioner of the presidency occupied by the researcher Nuria Oliver.

 

 

Grant funding from CRUE-Santander Fondo Supera CoVID-19

Last July we received funding for the project «Data Sciences against Covid-19» (CD4COVID), from the Supera Covid-19 fund that Banco Santander launched in April, together with CRUE Spanish Universities and the Higher Council for Scientific Research ( CSIC). The fund, endowed with 8.5 million euros to finance programs, projects and support measures, aims to minimize the impact of the crisis generated by the pandemic and focuses on three lines of action: research, impact projects social and strengthening the technological capacity of Spanish universities.

Our project is a collaborative work that we have developed voluntarily and altruistically since the beginning of the crisis caused by the pandemic, professors from Valencian universities. The research entitled «Data science against Covid-19» brings together the participation of civil society (through a citizen survey), experts from the academic-research environment and public administration, with the aim of providing information so that the those responsible for public crisis management can make informed decisions based on scientific evidence obtained from data analysis. In particular, I collaborate in the epidemiological models part and as head of the UPV node together with Miguel Rebollo from the VRAIN Institute. The initiative, linked to the Valencian Strategy in Artificial Intelligence through the commissioner of the presidency occupied by the researcher Nuria Oliver.

MsC in Bioinformatics and Biostatistics

I recently obtained a Msc in Bioinformatics and Biostatitsics from Universitat Oberta de Catalunya and Universitat de Barcelona. My capstone project was entitled «Machine learning methods for characterizing single-particle trajectories with anomalous diffusion» under the supervision of Ferran Reverter Comes.

Machine learning methods for characterizing single-particle trajectories with anomalous diffusion

Single-Particle Tracking (SPT) appears to be a potential approach to studying different dynamic processes in the life sciences with recent advances in light microscopy. The physics of life molecules has an inherent instability due to the heterogeneity of free energy states that different types of molecules can show, far from thermal equilibrium and ranging at different scales, from the nanoscale of a single molecule up to the cellular or even organism level. The classification of trajectories is a relevant topic, not only in the biological field at the molecular level but also at the level of animal and human behavior. Besides, this topic combines physical principles with some degree of uncertainty, which habilitates us for exploring the use of ML techniques.

 

Rankings and Spotify

I have recently presented a contribution in the with Francisco Pedroche on rankings. We have particularized to Spotify. While people around the world stopped, music didn’t: we have shown that during the worst months of the pandemic, the list of the Top-200 hits on Spotify, produced from the streams registered on the popular app, had 18% more songs. The most played songs worldwide, during the months studied, were Dance Monkey (Tones and I), Blinding Lights (The Weeknd), and The Box (Roddy Ricch).

This means that, regardless of whether record companies published new material or not, listeners changed their preferences more often during the pandemic, thus causing an increase in the number of songs that made the lists. Thus, the first quarter of 2019 registered 474 songs on the Top 200 list, whereas in the same period of this year, the number of hits was 557, which represents an 18% increase. This figure reveals a significant increase when compared to the 1% decrease that took place during the same period from 2018 to 2019, or the 9% increase from 2017 to 2018.

Screenshot by Monkey Dance by Tones and I.

Some links to the news on this paper: MUSIC NEWS, TIME24, La Vanguardia, and ABC.

Special Issue «Mathematical and Computational Methods against the COVID-19 Pandemics» in Mathematics (Q1 in JCR)

Mathematics Special Issue CoVID-19

Mathematics can also contribute to the modeling of side problems to the pandemics. We point out some of them, such as data quality analysis, network medicine, healthcare services management, the physical spreading of the virus in the environment, the subsequent impact on the economy, and the social response to confinement government measures.

In any case, all the contributions and developments will be beneficial in many ways aside from coping with pandemics. Some potential topics that this Special Issue will cover, but is not limited to, are as follows: Epidemiological dynamics, diffusion modeling, compartmental and SIR type models, human dynamics, agent modeling of structured populations, network medicine, data quality, artificial intelligence and deep learning models, and data analysis of social media

Further information in https://www.mdpi.com/journal/mathematics/special_issues/Mathematics_COVID-19 Your work is welcome!!!

Diario Libre de Rep. Dominicana. Ingenieros dominicanos aportan avances en el estudio de los números primos y el triángulo de Pascal

News appeared in Diario Libre of the Dominican Republic about my joint work with my students Pedro A. Solares Hernández and Fernando A. Manzano, together with Fco. Javier Pérez Benito. In this work, we study divisibility properties of Pascal’s triangle numbers. Link to the article.

Link to the publication in the mathematical journal Mathematics, from MDPI publisher, https://www.mdpi.com/2227-7390/8/2/254 

Modelo matemático para evaluar el impacto energético de los recubrimientos GCover.

En este proyecto, investigadores del Instituto Universitario de Matemática Pura y Aplicada (IUMPA) y de la Escuela Técnica Superior de Arquitectura (ETSA) de la UPV hemos desarrollado un modelo completo para evaluar las prestaciones de uno de los productos de la compañía como aislante térmico en la construcción. La Vanguardia y otros medios se han hecho eco de nuestro trabajo.

20200208 - GCover - La Vanguardia

Podéis leer también la noticia completa también en la página web de la UPV.

J.A. Conejero accreditated as Full Professor

Last may I have received the acreditation as Full Professor from ANECA (Agencia Nacional de Evaluación de la Calidad y Acreditación), deppending from the Spanish Ministry of Education.

It has been a long and winding road since I started my PhD on 1999, and I did not even think about this then. There have been many collaborators and supervised students that have come along with me during these years. I want to thank them for all what I have learned from them and for sharing a little of their time and their life their time with me.

As W. Churchill said: Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning.

CyanoFactory Consortium paper appeared on-line

I have been collaborating in the CyanoFactory project R&D project developed in response to the European Commission FP7-ENERGY-2012-1 call “Future Emerging Technologies” and the need for significant advances in both new science and technologies to convert solar energy into a fuel. The project has been coordinated by P. Linbald from Uppsala. The UPV node has been integrated by J.F. Urchueguía, D. Fuente, M. Siurana, L. Lemus, and myself.

Prototype of a cyanobacteria based fuel factory.

CyanoFactory, Design, construction and demonstration of solar biofuel production using novel (photo)synthetic cell factories, was an example of “purpose-driven” research and development with identified scientific goals and creation of new technologies. The present paper overview highlights significant outcomes of the project. It has appeared in Algal Research.

Wakamola, bot para analizar tus hábitos alimentarios y el de tu red.

El proyecto Wakamola, se trata de un bot que, a través de Telegram, simula una conversación con el usuario sobre su dieta, actividad física, enfermedades, edad, peso, red social, etc. El análisis posterior de dicha información permitirá crear una red de relaciones para estudiar las interacciones de los hábitos de la población en relación a su dieta, actividad física, su entorno y los hábitos su red familiar, laboral y de amistades.

En este proyecto colaboro con Juan M. García Gómez, Sabina Asensio y Vicent Blanes del instituto ITACA de la UPV dentro del proyecto europeo H2020 CrowdHealth.

Más información en https://wakamola.webs.upv.es

Invited Talk at ECTX Conference (Enginnering Computational Technology)

I have been invited to dalivered a talk at The Tenth International Conference on Engineering Computational Technology held in Sitges. In this conference I present some results on algorithmic solutions for managing car-sharing and car-rental companies in order that there was a participatory management with the users. The title of the talk was Iterative algorithms for car rental and car sharing transport management and it was shown within the Special Session Iterative schemes for analyzing nonlinear problems: Numerical and dynamic. The results are part of a joint work with Cristina Jordán and Esther Sanabria-Codesal from Universitat Politècnica de València, too.

 

Talk at European Conference on Iteration Theory (ECIT 2018)

Iteration Theory  is a branch of mathematics and includes topics related to discrete dynamical systems and functional equations. The aim of these theoretical studies is to model, analyze and understand iterative processes, for example systems with discrete time. Such systems arise in many different fields of application: engineering (eg. control theory and electronics), physics, mechanics, economics, biology, ecology, and so on.

20th ECIT follows the sequence of meetings started in Toulouse 1973. The previous one was held on Innsbruck 2016.

I present my recent work entitled Visibility Graphs of Fractional Logistic Time Series, in collaboration withAinara Mira-Iglesias, Cristóbal Rodero-Gómez, and Carlos Lizama.  There we received very interesting feedback from Prof. Mark Edelman.