nelsonaloysio.github.io

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Nelson Aloysio R A Passos (1993) is a Brazilian data science specialist and back-end developer, currently based in Portugal.

As a researcher, his main area of interest lies in graph theory and complex network analysis. His last research focused on building a method to map communities in online social networks using text-based classification, applied to the study of temporal data from Twitter.

As a developer, his experience mainly lies in building, scaling and optimizing pipelines for automated information extraction and data visualization, to provide insight and actionable reports for decision and policy making. Slowly gravitating from Python/R towards Julia.

Currently enrolled at research center Sou Ciência–Unifesp[🇧🇷].


Research & development

Ongoing projects

[2021-] Data scientist role at Sou Ciência–Unifesp[🇧🇷].

Supporting development of data-driven research methods for automated information extraction, natural language processing, complex network analysis and graph visualization, aimed at understanding the social perception of public universities and analyzing the relations between higher education, science and technology in Brazil.

Past experience

[2021-2020] Data scientist role at Culture Hack Labs[🇨🇦].

Building pipelines for unsupervised clustering (sklearn/SciPy), natural language processing (NLTK/spaCy) and network analysis (arangoDB/networkX/networKit/igraph), aimed at job orchestration (Celery/Airflow) and CI/CD (docker/k9s/skaffold) automated tasks for cloud deployment (AWS/gcloud).

[2019-2018] Back-end developer role at The Rules Foundation[🇺🇸].

Development of web scraping (bs4/Selenium) and social network data collection, analysis and visualization (Plotly/Pandas/PyPhi/Seaborn) tools for a web analytics dashboard (django/react.js).

[2017-2016] Data analytics consultant role to a presidential election[🇪🇨] campaign staff (undisclosed).

Design and automation of OSINT data crawling/scraping and aggregated analysis routines for crisis control and daily intelligence reports on social media impact among opposing parties running for Ecuadorian presidency.

[2017-2014] R&D role at Laboratory of Internet studies and Cyberculture at Labic–Ufes[🇧🇷].

Data-driven research and back-end development of analytics dashboards for the Brazilian Secretariat for Human Rights (SDH/2015) and the National Institute of Educational Studies and Research (INEP/2017) [BR512017000690-3]. Analysis of social networks and geoepidemiological data on emergent arboviruses (ZKV, DENV, CHIKV) for the United Nations Children’s Fund (UNICEF/2016) and intelligence report on global education using public data for the United Nations’ Education Commission (2017). Additional experience (minor) in data journalism and visual storytelling from working in tandem with journalists and designers in the interim.

Conference papers


Education

[2022-2019] Master in Social Science @ Federal University of Espirito Santo[🇧🇷].

Thesis: Method for classification of communities in temporal networks: mapping the 2013-2018 Brazilian protests on Twitter.

[2020-2018] Graduate in Data Science with Big Data @ Federal Institute of Science and Technology of Espirito Santo[🇧🇷].

Monograph: Cluster analysis using Markov Cluster Algorithm and the Louvain method: a case study of Wikipedia entries. 2020.

[2017-2011] Bachelor in Media Studies Federal University of Espirito Santo[🇧🇷].

Bachelor’s thesis: A tool for data journalism, social network analysis and cyberspace mapping. 2018.


Contact

Also available (rarely) on LinkedIn.