In October 2013, I received my Ph.D. 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.

Previously, 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).

I am currently a assitant professor at the Informatics Engineering at the Pontificia Universidad Católica del Peru in Lima, Peru. Further, 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 professor at the Universidad de Ingeniería y Tecnología - UTEC in Peru

I am also part of the Artificial Intelligence team at the Pontificia Universidad Católica del Perú (IA-PUCP team). Moreover, I was a member of the Directive Board of the IEEE Peru Computer Society chapter (from 2015 to 2019).

Finally, I am 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 8th. edition.


Research interest

My research works are focused on Knowledge Extraction from Data from heterogeneous data. I am mainly concentrated on technics for the extraction of complex patterns from data involving spatiotemporal dynamics. These studies should tackle real problems associated with biodiversity, the environment, health issues, among others. Some of my contributions are available on DBLP and Google Scholar

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, among others. In the same context, my team and I proposed the algorithm WinCOPPER, a new Python-implementation to extract sequential patterns under constraints.

Founded research projects

During these last four years, I have participated - as a head or a member of researchers team - in some projects financed by local and/or international organizations. Some of these projects are:

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.

Big data analysis over cellphone usage and consumption to estimate unbanked people indebtedness capacity for financial inclusion

This project aims to extract the unbanked inhabitants' financial health indicators from data related to the use and location reported by cell phones. To attend this aim, we perform big data analytics techniques for the development of evidence-based public policies for traditional and/or digital financial inclusion. This project is still under development.

Feasibility of using geo-referenced photographs in the design of agricultural insurance

This project aims to evaluate the feasibility of using geo-referenced photographs periodically captured by farmers from their cell phones to design low-cost agricultural insurance aimed at small and medium-sized commercial farmers. This project is still under development.

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.

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.

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.

BIrthDAY Consortium

The BirthDAY project aims to provide new efficient decision-making tools for helping agricultural development and biodiversity protection in Peru. More precisely, it aims to develop a new platform for acquiring new data, extract knowledge, and share useful information and knowledge among different actors involved in agriculture or biodiversity domains in Peru.


My trajectory starts in 2004 with some courses in technical schools. The latest ones are:

Teaching courses

Visiting Professor

Thesis advising

Current students

Past students