About
I am currently a postdoctoral fellow at the Engineering School of the Pole Universitaire Leonard de Vinci in Paris, France. Also, I am Chief Data Officer CDO at Ping4All, a Luxembourg-based sport-health tech company founded to foster people's physical and mental well-being worldwide. Besides, I am an part-time professor of Informatics Engineering at the Pontificia Universidad Católica del Peru in Lima, Peru, and part of the Artificial Intelligence team at the same university (IA-PUCP team). I am also co-founder of SIMBig, one of the first conferences in Latin America grouping related areas such as Data Science, Big Data, Natural Language Processing, among others. Currently, SIMBig is celebrating its 11th. edition.
Previously, I was a full-time professor (from 2016 to 2021) at the Universidad del Pacífico in Lima, Peru. I was also Vice-dean of the Information engineering program (from 2017 to 2020) at the same university and a member of the Editorial Board of the Universidad del Pacífico publishing house. Also, I was a professor at the Universidad Peruana de Ciencias Aplicadas - UPC in Peru. Moreover, I was a member of the Directive Board of the IEEE Peru Computer Society chapter (from 2015 to 2019).
Education
In October 2013, I received my PhD in Computer Science from the University of Montpellier 2, France, in collaboration with the University of New Caledonia. My thesis was carried out under the supervision of Maguelonne Teisseire, Nazha Selmaoui-Folcher, Sandra Bringay, and Frédéric Flouvat. This work involved the spatiotemporal pattern mining problem from geo-referenced data, specifically related to health and environmental issues.
Also, I received my Master's degree from the University of Montpellier 2 (France) in Computability, Algorithms, and Network Management and Security in June 2010. I obtained my degree in Systems Engineering at Andina University in 2004 (Cusco, Peru).
Research
Research interest
My research focuses on knowledge extraction from heterogeneous data. I am particularly interested in techniques for extracting complex patterns from data with spatio-temporal dynamics. However, my research topics extend to the study of other data mining techniques such as graph mining, text mining, image processing, data privacy, machine learning, among others. My five most recent publications are listed below:
- Alcántara Francia, O. A., Nunez-del-Prado, M., & Alatrista-Salas, H. (2024). Exploring the interpretability of legal terms in tasks of classification of final decisions in administrative procedures. Quality & Quantity, 1-25.
- Galarreta, A. P., Samamé, H., Maehara, Y., Nunez-del-Prado, M., & Alatrista-Salas, H. (2023). Recommender systems using temporal restricted sequential patterns,. Journal of Ambient Intelligence and Humanized Computing 14(12), 15895-15908.
- del Prado Cortez, M. N., Gauthier, V., Roujanski, G., Salas, H. A., & Tariverdi, M. (2023, October). Dynamic Road Network Criticality Computation using Call Detail Records for Enhancing Healthcare Accessibility. In Network Mobility (netmob).
- Trujillano F, Jimenez Garay G, Alatrista-Salas H, Byrne I, Nunez-del-Prado M, Chan K, Manrique E, Johnson E, Apollinaire N, Kouame Kouakou P, Oumbouke WA, Tiono AB, Guelbeogo MW, Lines J, Carrasco-Escobar G, & Fornace K. Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance. Remote Sensing. 15(11):2775. https://doi.org/10.3390/rs15112775
- Galarreta, A. P., Alatrista-Salas, H., & Nunez-del-Prado, M. (2023). Predicting Next Whereabouts Using Deep Learning. In Modeling Decisions for Artificial Intelligence: 20th International Conference, MDAI 2023, Umeå, Sweden, June 19–22, 2023, Proceedings (pp. 214-225). Cham: Springer Nature Switzerland.
I am also interested in the diffusion of areas such as Data Mining, Machine Learning, Big Data, etc. This is reflected in some conferences where I was General Chair or member of the Organization Committee. Some of them are Edunine 2019, CIARP 2016, WRPIAA 2014, NLDB 2014, SIMBig 2014 - 2023, among others. In the same context, my team and I proposed the algorithm WinCOPPER, a new Python-implementation to extract sequential patterns under constraints.
Funded research projects
During these last years, I have taken part either as a leader or as a member of the research team in some projects with local and/or international grants. Some of these projects are:
SmartTTCare: Table tennis as therapeutic activity for your health and wellbeing in cancer remission patients.
Thanks to the practice of table tennis, SmartTTCare aim to provide personalized AI-driven training programs for cancer patients in remission. Utilizing a 5G connection in the Metaverse, our program has a global reach anytime, anywhere. A reward system will motivate patients to keep training, while our technology analytics platform monitors their progress in real-time, offering accurate data to patients, healthcare professionals, and families. This project, funded by the European Spatial Agency - ESA, started in 2023.
[Leader] Fibroscope: Low-cost intelligent microscope for verifying fibre composition in textile products of the South American camelid.
The main objective is to develop a portable system for fibre composition analysis based on computer vision and artificial intelligence to ensure the quality of handmade textile products for commercialization in the national and international markets. This system will be connected to AI-based software that will allow better decision-making on the quality of the analyzed sample. This project started in 2022, and it won first place in Vinculatech, a contest organized by Prociencia. Concytec funds our project.
[Leader] Computational Approaches for the Analysis of Urban Mobility Data
The goal of this project is to analyze urban mobility problems and phenomena that are present in cities around the world. Also, to design data modeling algorithms that help identify patterns in mobility data from big cities. This SticAmSud project starts in 2021, and it is funded by Concytec.
COViD: COntro de Virus Dinámico
The aim of the COViD project is the Peruvian implementation of a digital contact tracer. In this context, we should be capable of estimating the probability of contagion based on infected people and the visualization of such information for policymakers. This project funded by Concytec was finished in February 2021.
Development of a decision support system, using drones, for adaptation to climate change in high-Andean agriculture
This project aims to build a decision support system based on the results of the analysis of heterogeneous data associated with agriculture. Our disposal data contains surveys, meteorological data, hydrological data, and images from multispectral cameras, among others. This project is funded by the local government, precisely by the National Institute of Agrarian Innovation INIA-PNIA.
[Leader] Low cost microscope for smartphones: Technological solution for the detection of diseases in cattle
This project aims to propose a new technology for the early detection of subclinical mastitis in cattle. Our proposal includes the adaptation of a device for capturing images and a microscope to a micro-computer. Also, an algorithm for counting somatic cells was proposed. This project ended in April 2018.
[Leader] Smart shopping: Smart purchase tool
This project aims to construct an algorithm to - smartly - compare products from different stores to propose the best price to clients. The idea behind our proposal is to compare features of the products based on a distance measure. This project ended in September 2017, and intellectual property rights protect our algorithm in Peru.
PEDESTAl: Prediction models for Energy consumption based on big data analytics of population DEnsity and SpaTio-social Activities
The proposed project aims to design and implement prediction models for energy (electricity) consumption relying on human activities classification and mapping over time as well as population density dynamic estimation. Big Data Analytics, Data and Text Mining, Machine Learning, and Social Network tool will be investigated and applied to achieve our goal. This project was funded by Stic-AmSud - Fondecyt.
ANIMITEX project: image analysis based on textual information
With the amount of textual data available on the web, new knowledge extraction domains are provided. Some original methods allow the users to combine different types of data in order to extract relevant information. In this context, the main objectives of the ANIMITEX project is to combines spatial and textual data. This project was funded by CNRS - France.
Teaching
My trajectory starts in 2004 with some courses in technical schools. The latest ones are:
Teaching courses
- Universidad Peruana de Ciencias Aplicadas, Peru
- Machine Learning (master degree,2022 - 2023)
- Pontificia universidad Católica del Perú, Peru
- Infotmation visualization (executive education, 2022 - 2023)
- Introduction to programming for economist (undergraduate degree, 2022 - 2023)
- Aplicaciones de las Ciencias de la Computación (undergraduate degree, 2014 - 2016)
- Web analytics (master degree, 2017 - 2021)
- Information visualization (master degree, 2015 - 2020)
- Text mining (master degree, 2015 - 2020)
- Exploratory data analysis (master degree, 2021 - 2021)
- Universidad de Ingeniería y Tecnología - UTEC, Peru
- Research projects (undergraduate degree, 2021 - 2021)
- Research projects (posgraduate degree, 2021 - 2021)
- Universidad del Pacífico, Peru
- Data engineering (undergraduate degree, 2016 - 2021)
- Data mining (undergraduate degree, 2016 - 2021)
- Web mining (undergraduate degree, 2016 - 2017)
- Storyteelling and data visualization (posgraduate degree, 2021 - 2021)
- Design of business solutions (undergraduate degree, 2019 - 2021)
- Ecole d'informatique EPSI, Montpellier, France
- Data Werehouse and OLAP (undergraduate degree, 2013 - 2014)
- Université de Montpellier 2, France
- Extraction des connaissances à partir des données (master degree, 2012 - 2014)
- Introduction à la fouille de données (master degree, 2015 - now)
- Introduction à l’Algorithmique et la programmation (undergraduate degree, 2010 - 2014)
- Université Paul Valéry, Montpellier, France
- Méthodologie et traitement de données, analyse de données (undergraduate degree, 2011 - 2012)
Visiting Professor
- Université Paul Valéry, Montpellier, France. MIASH Master. Jan-Feb 2020
- Pontificia Universidad Católica del Ecuador - Sede Ambato, Ambato, Ecuador. EIS. Nov, 2016
Thesis advising
Current students
- Ana Paula Galarreta Asian, Ph.D. candidate - PUCP. Spatiotemporal predictions from frequent substructures
- Guillermo Rodríguez-López, Ph.D. candidate, PUCP. Measuring the resilience of social structures based on heterogeneous data.
- Romer Vargas Otiniano, Master student, PUCP. Analysis of the Influence of Social Classes on the Shops Attractiveness.
- Josué Mauricio Salazar, Master student, PUCP. Un nuevo enfoque para la predicción de un tiro penal basada en la estimación de posición del jugador.
Past students
- Hunan Quispe Manotupa, Sui San Ching Donayre, Master student, UPC. Resume here
- Ariana Quispe Porras, Undergraduate student, PUCP. Análisis del turismo en el Perú usando técnicas de graph mining.
- Peter Montalvo García, Master student, PUCP. Resume here
- Hilda Samame Jimenez, Master student, PUCP. Resume here
- Pavel Rojas Bustamante, Master student, PUCP. Resume here
- Julianna Milagros Apumayta Lopez, Master student, PUCP. Resume here
- Kevin Alvarez Mouravskaia, Master student, PUCP. Resume here
- Iván Darío Peñaranda Arenas, Master student, PUCP. Resume here
- Ian Paul Brossard Núñez, Master student, PUCP. Resume here
- Mauro Antonio Leon Payano, Master student, PUCP. Resume here
- José Luis Barturén-Larrea, Master student, PUCP. Resume here
- Oscar Antonio Díaz-Barriga, Master student, PUCP. Resume here
- Natali Flores-Lafosse, Master student, PUCP. Resume here
- Rodrigo Ricardo Maldonado-Cadenillas, undergraduate student, PUCP. Resume here
- Wissame Laddada, "Discovering new spatial relationships using text mining methods". Supervision of Master Research Internship, Université de Montpellier 2.
- Pierre Accorsi, "Spatiotemporal pattern visualization: Three different approaches". Supervision of Master Research Internship, Université de Montpellier 2.
- Mickaël Fabrègue, "Efficient spatiotemporal sequential pattern mining". Supervision of Master Research Internship, Université de Montpellier 2.