About Me
Phd student, Thinker, Creative
I am a Phd Student at Ghent University
I was born in Guayaquil, Ecuador on April 10th, 1982. I received my bachelor's degree in Computer Engineering from the Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil-Ecuador, in 2007. In 2012, I got my master degree from a Master's program in Information System Management at the same university.
I am a member of the scientific staff of the Department of Industrial Systems Engineering and Product Design from Ghent University. I got my Ph.D. degree in Computer Science Engineering at Ghent University. My research is in Intelligent Systems and focused on pattern recognition on big data gathered through citizen science applications from smart cities.
Resume
10 Years of Experience
Education
2012
System Information Management
Escuela Superior Politécnica del LitoralThesis: "Designing methodology for data migration between critical applications in the Guayaquil’s town hall".
Advisor: Prof. Lenin Freire
2007
Computer Engineer
Escuela Superior Politécnica del LitoralDesign and implement software and hardware solutions.
Experience
May 2008 - April 2016
Professor
Escuela Superior Politécnica del LitoralUndergraduate course Proffessor. Courses: Programming Fundamentals, Object Oriented Programming, Database Systems I, Web Applications Development, and Data Structures.
Jan 2008 - May 2012
Senior Software Developer
Guayaquil CityhallApplication Developer (Web and Windows) using .NET platform in Guayaquil's town hall.
Abr 2006 - Dic 2007
Revenue Assurance Analyst
CONECEL S.A.Quality controls to SMS billing, identification of unbilled voice events, application development for automation of quality controls.
Data science skills
Coding skills (Python)
Machine Learning/Data Mining
Structured Data (SQL)
Unstructured Data (NoSQL DBs)
Coding Skills
Database developer
Web developer
Windows developer (C#.NET)
Java
Languages
Spanish
Portugues (Brazilian)
English
Dutch (Belgium)
Portfolio
My Best Works
Consultor
Nov 2013- Mar 2014
Inspector of Use Cases National System Public Finance
ESPOLTECH, Guayaquil, EcuadorThe inspection was performed in order to detect and classify the different types of errors in the system requirement’s definition, to correct them and performing the software measurement process.
November 2012
Land Use System development
M.I. Municipalidad de GuayaquilBy this system, citizens can check their property's land use. The system was developed in ASP.NET and deployed at November 2012. Web site.
Research
orcid.org/0000-0002-7878-1471Publications
November 2020
Density-Based Spatial Clustering and Ordering Points Approach for Characterizations of Tourist Behaviour | journal-article
Knowledge about the spots where tourist activity is undertaken, including which segments from the tourist market visit them, is valuable information for tourist service managers. Nowadays, crowdsourced smartphones applications are used as part of tourist surveys looking for knowledge about the tourist in all phases of their journey. However, the representativeness of this type of source, or how to validate the outcomes, are part of the issues that still need to be solved. In this research, a method to discover hotspots using clustering techniques and give to these hotspots a data-driven interpretation is proposed. The representativeness of the dataset and the validation of the results against existing statistics is assessed. The method was evaluated using 124,725 trips, which have been gathered by 1505 devices. The results show that the proposed approach successfully detects hotspots related with the most common activities developed by overnight tourists and repeat visitors in the region under study.Rodríguez-Echeverría, J.; Semanjski, I.; Van Gheluwe, C.; Ochoa, D.; IJben, H.; Gautama, S. Density-Based Spatial Clustering and Ordering Points Approach for Characterizations of Tourist Behaviour. ISPRS Int. J. Geo-Inf. 2020, 9, 686.
November 2018
Efficient Use of Geographical Information Systems for Improving Transport Mode Classification | conference-paper
Comparison between transport mode classifiers is usually performed without considering imbalanced samples in the dataset. This problem makes performance rates, such as accuracy and precision, not enough to report the performance of a classifier because they represent a cut-off point in the classifier performance curve. Our rule-based method proposes to combine both, the network elements associated with the transport mode to identify, and the elements associated with other means of transport. We performed a comparison between our proposed method and another GPS/GIS-based method, by applying a real-world representative dataset with a target class imbalance. We evaluated the performance of both methods with five experiments, using the area under the Receiver Operating Characteristic curve as metric. The results show that the tested methods achieve the same false positive rate. However, our method identifies correctly 84% of the true positive samples, i.e., the highest performance in our test data (data collected in Belgium). The proposed method can be used as a part of the post-processing chain in transport data to perform transport and traffic analytics in smart cities.Rodriguez-Echeverria, J., Gautama, S., Van de Weghe, N., Ochoa, D., & Ortiz-Jaramillo, B. (2018). Efficient Use of Geographical Information Systems for Improving Transport Mode Classification. In DATA ANALYTICS 2018, The Seventh International Conference on Data Analytics (pp. 130–135). Athens, Greece.
September 2018
Unsupervised Hierarchical Clustering Approach for Tourism Market Segmentation Based on Crowdsourced Mobile Phone Data | journal-article
Understanding tourism related behavior and traveling patterns is an essential element of transportation system planning and tourism management at tourism destinations. Traditionally, tourism market segmentation is conducted to recognize tourist’s profiles for which personalized services can be provided. Today, the availability of wearable sensors, such as smartphones, holds the potential to tackle data collection problems of paper-based surveys and deliver relevant mobility data in a timely and cost-effective way. In this paper, we develop and implement a hierarchical clustering approach for smartphone geo-localized data to detect meaningful tourism related market segments. For these segments, we provide detailed insights into their characteristics and related mobility behavior. The applicability of the proposed approach is demonstrated on a use case in the Province of Zeeland in the Netherlands. We collected data from 1505 users during five months using the Zeeland app. The proposed approach resulted in two major clusters and four sub-clusters which we were able to interpret based on their spatio-temporal patterns and the recurrence of their visiting patterns to the region.Rodriguez Echeverría, J., Semanjski, I., Gautama, S., Van de Weghe, N., & Ochoa, D. (2018). Unsupervised Hierarchical Clustering Approach for Tourism Market Segmentation Based on Crowdsourced Mobile Phone Data. (E. Lattanzi & V. Freschi, Eds.)Sensors, 18(9).
August 2017
A methodology for train trip identification in mobility campaigns based on smartphones | conference-paper
Nowadays, mobility campaigns use mobile phones as sensors for travel surveys aimed at gathering chronological information, patterns and modes used by citizens. Train trip travel identification is one of the issues present in this new schema. Differentiating train and car trips is challenging because in many cases railways and roads are side by side and their individual travels have similar speed. In this paper, we describe a methodology based on a speed-based filter and geospatial operation using the OSM network to determine possible train trip segments in data gathered in a mobility campaign. We evaluated our method using over 9,683 segments, which have been gathered by 239 devices. The results show that the proposed approach successfully detects 76.14% of the train trip segments labeled by users. This methodology can be used as a post-processing step to classify train segments in big data of smar cities.Rodríguez-Echeverría J., Gautama S. and Ochoa D., "A methodology for train trip identification in mobility campaigns based on smart-phones," 2017 IEEE First Summer School on Smart Cities (S3C), Natal, 2017, pp. 141-144.
October 2016
Linguistic profiles on microblogging platforms to characterize political leaders: the ecuadorian case on twitter | conference-paper
Social interaction on microblogging platforms is becoming a reliable instrument for studying political communication characteristics. Microblogging platforms, such as Twitter, let citizens to engage in the political debate generating well-defined profiles in the platform. Using publicly available tweets it is possible to build a linguistic profile to compare leaders and average citizens. We describe the linguistic analysis of 330,000 tweets collected from 221 Ecuadorian tweeters classified into three different profiles: political leaders, leaders' followers, and average local users. We build a feature vector for each user's tweets using 12 psychological dimensions included in the LIWC (Linguistic Inquiry Word Count) text analysis software and compare users with different profiles using those vectors. Our findings show that the leaders group exhibits a different linguistic profile from the others two groups: around 30% of leader followers are similar to at least one leader while just 19% of average local users are similar to at least one leader. Furthermore, the results of our analysis allows to determine whether local users have some similar characteristics of language uses on social networks of political leaders' followers without relying on critical discourse analysis.Pita, O., Baquerizo, G., Vaca, C., Mendieta, J., Villavicencio, M., & Rodríguez, J. (2016, October). Linguistic profiles on microblogging platforms to characterize political leaders: the ecuadorian case on twitter. In Ecuador Technical Chapters Meeting (ETCM), IEEE (pp. 1-6). IEEE.
Teaching
Undergraduate courses
May 2013 - Feb 2016
Data Structures
Escuela Superior Politécnica del LitoralAveraging 30 students per semester, covering the following topics: data types, data structures: list, stack, queue, map, trees, graph. Developed quizzes, exams, and homework. Checking the syllabus to cover accreditation standards. Coordinated grading and labs with a team of 2 professors.
Oct 2011 - Feb 2016
Web Applications Development
Escuela Superior Politécnica del LitoralAveraging 35 students per semester, covering the following topics: web standards, client-side and server-site programming, web architectures, web services, MVC model, state management, web security. Developed quizzes, exams, and homework. Checking the syllabus to cover accreditation standards.
May 2011 - Sep 2013
Database Systems I
Escuela Superior Politécnica del LitoralAveraging 20 students per semester, covering the following topics: modeling database, normalization, Transact SQL, PL/SQL. Developed quizzes, exams, and homework.
Oct 2010 - Sep 2014
Object Oriented Programming
Escuela Superior Politécnica del LitoralAveraging 60 students per semester, covering the following topics: Java Programming, object-oriented programming, object-oriented analysis and design, user interface design. Developed quizzes, exams, and homework. Checking the syllabus to cover accreditation standards. Coordinated grading and labs with a team of 3 professors.
May 2008 - Sep 2011
Programming Fundamentals
Escuela Superior Politécnica del LitoralAveraging 30 students per semester, covering the following topics: C Programming, structure programming, functions, arrays, libraries, pointers, characters and string, files. Developed quizzes, exams, and homework.
Undergraduate Students Advised
May 20, 2015
Android application that used wi-fi technology to guide students to their classrooms in ESPOL
Escuela Superior Politécnica del LitoralStudents: Carla Hurel, Andrea Caceres. http://www.dspace.espol.edu.ec/xmlui/handle/123456789/30799
Jul 24, 2013
Social web application for labeling fragments of Youtube videos applying the concept of games with a purpose
Escuela Superior Politécnica del LitoralStudents: Carla Salvatierra, Felix Rivas. http://www.dspace.espol.edu.ec/handle/123456789/24733
Contact
Get in Touch
Get in Touch
During my PhD studies I am living in Ghent, Belgium. If you want to contact me, please send a message to the following email addresses.