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Germain Garcia-Zanabria

Computer Scientist | Data Scientist | Researcher

UTEC University

I’am Germain Garcia-Zanabria, I received my Ph.D. degree (2017-2021) in Computer Science (Cs) from Sao Paulo University (USP) specifically at ICMC institute, Brazil. I received my Master’s Degree (2014-2016) in Cs at Universidad Católica San Pablo (UCSP), Peru. I conducted my Post-Doctoral research on dropout patterns in Peruvian universities at the Center for Research and Innovation in Computer Science (RICS) of UCSP. I was a visiting researcher (2019) at the Visualization Imaging and Data Analysis Center (VIDA) of New York University (NYU), USA. My areas of interest are data visualization, visual analytics, machine learning, data science, crime analysis, crime prediction, dropout analysis, geo-referenced data, Spatiotemporal analysis, and computer science for social goods.

Interests

Visual Analytics
Visualization of Information
Crime Data Analysis
Visualization for Social Good

Education

PhD in Computer Science, 2021

University of Sao Paulo (USP) - Brazil
MSc in Computer Science, 2016

Universidad Católica San Pablo de Arequipa (UCSP) - PERU
Engr in System Engineering, 2012

Universidad Nacional de San Antonio Abad del Cusco (UNSAAC) - PERU
BSc in System Engineering, 2012

Universidad Nacional de San Antonio Abad del Cusco (UNSAAC) - PERU

Skills

Programming

Python, C++, C#, JS, R, git, LaTeX

Visual Analytics

D3js, Deckgl, Notebook, colab, Power BI, Tableu

Languages

Spanish, English, Portuguese, Quechua

Experience

University Professor - Researcher

UTEC

July 2023 – Present Lima - PERU

Responsibilities include:

Researcher
Professor Data Science Program

University Professor

UNSAAC

June 2022 – September 2022 Cusco - PERU

Responsibilities include:

Research Projects
Business Analytics

POS-Doctoral Researcher - Professor

UCSP

January 2021 – June 2022 Arequipa - PERU

Responsibilities include:

Python for Data Science
Bussiness Analytics
Dropout Data Analysis

Profesional Internship

EGEMSA

September 2012 – January 2014 Cusco - PERU

Profesional internship in Tecnology of Information Group

Projects

Crime Analytics

Visual Data Crime is a research project that aims at creating computational systems to help identify, understand, and predict criminality. The goal is to explore data from space-temporal crime occurrences, safety perception, socioeconomic traits, and amenity features to help specialists and decision-makers deal with criminality.

Dropout Analysis

This project proposes to analyze data from educational environments, with the aim of studying relevant issues, challenges, and opportunities for improvement. Our proposal will focus on three main objectives: (Obj 1) Video Analysis, (Obj 2) Social Network Analysis, and (Obj 3) Socioeconomic and Academic Analysis, described below.

Featured Publications

Germain Garcia-Zanabria, Daniel A. Gutierrez-Pachas, Guillermo Camara-Chavez, Jorge Poco, Erick Gomez-Nieto

July, 2022 Applied Sciences

SDA-Vis - A Visualization System for Student Dropout Analysis Based on Counterfactual Exploration

SDA-Vis system - a set of linked visual resources enabling the exploration of dropout students’ information and their counterfactual explanations.

Germain Garcia-Zanabria, Marcos M Raimundo, Jorge Poco, Marcelo Batista Nery, Claudio T Silva, Sergio Adorno, Luis Gustavo Nonato

September, 2021 IEEE Transactions on Visualization and Computer Graphics

CriPAV - Street-Level Crime Patterns Analysis and Visualization

CriPAV system - Hotspot (b), spatial (a and c), and temporal interactive views (d, e, and f) enabling the exploration of local regions while revealing their criminal patterns over time.

Germain Garcia-Zanabria, Erick Gomez-Nieto, Jaqueline Silveira, Jorge Poco, Marcelo Nery, Sergio Adorno, Luis G. Nonato

November, 2020 In SIBGRAPI

Mirante - A visualization tool for analyzing urban crimes

An overview of the Mirante tool, a set of spatiotemporal visual resources enabling the exploration of crime patterns in a region: (a) Street-level Heatmap, (b) Temporal Evolution View, (c) Temporal Histogram View, (d) Selector toolbox, (e) Address Search Bar, (f) Evolution Animation Controller, and (g) Local/global crime ruler

Germain Garcia-Zanabria, Silveira, Jaqueline, Poco Jorge, Paiva, Afonso, Nery, Marcelo Batista, Silva, Claudio T, Adorno, Sergio, Nonato, Luis Gustavo

October, 2019 IEEE Transactions on Visualization and Computer Graphics

CrimAnalyzer - Understanding Crime Patterns in São Paulo

CrimAnalyzer system - the spatial and temporal interactive views enable the exploration of local regions while revealing their criminal patternsover time.

Recent Publications

Gutierrez-Pachas Daniel A, Germain Garcia-Zanabria, Cuadros-Vargas Ernesto, Camara-Chavez Guillermo, Gomez-Nieto Erick (2023). Supporting Decision-Making Process on Higher Education Dropout by Analyzing Academic, Socioeconomic, and Equity Factors through Machine Learning and Survival Analysis Methods in the Latin American Context. IEEE Transactions on Visualization and Computer Graphics.

PDF Cite DOI

Gerar F. Quispe-Torres, Lauro Enciso-Rodas, Harley Vera-Olivera, Germain Garcia-Zanabria (2022). A Feature-based Trajectory Anomaly Detection. Special Issue of CLEI 2021 best papers (CLEIej).

PDF Cite Slides

Gutierrez-Pachas Daniel A, Germain Garcia-Zanabria, Cuadros-Vargas Alex J, Camara-Chavez Guillermo, Poco Jorge, Gomez-Nieto Erick (2022). How Do Curricular Design Changes Impact Computer Science Programs? - A Case Study at San Pablo Catholic University in Peru. Education Sciences.

PDF Cite Project DOI

Daniel A Gutierrez Pachas, Germain Garcia-Zanabria, Alex J Cuadros-Vargas, Guillermo Camara-Chavez, Jorge Poco, Erick Gomez-Nieto (2021). A comparative study of WHO and WHEN prediction approaches for early identification of university students at dropout risk. In CLEI.

Cite Project DOI

Gerar F. Quispe-Torres, Lauro Enciso-Rodas, Harley Vera-Olivera, Germain Garcia-Zanabria (2021). Trajectory Anomaly Detection based on Similarity Analysis. In CLEI.

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