Gabriel Araujo
Ph.D. Student MIT EECS
Cambridge, Massachusetts, United States
Summary
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Senior🎓
Top SchoolGabriel Araujo is a Ph.D. student in MIT EECS (FutureTech Lab) with eight years of research and applied data science experience focused on the computational limits and societal impacts of deep learning. He has been a research assistant at CSAIL investigating how exponential increases in computing power drive ML progress and its sustainability implications, complementing earlier applied work on legal-document knowledge extraction and community-centered tech projects. Based in Cambridge, he blends rigorous empirical analysis with practical systems and fieldwork, from large-scale computational studies to grassroots innovation with farmers. His background in software engineering and multidisciplinary research allows him to bridge theory, measurement, and real-world deployment, often emphasizing computational efficiency as a lever for more sustainable AI.
8 years of coding experience
Ph.D., Electrical Engineering and Computer Science (EECS), Ph.D., Electrical Engineering and Computer Science (EECS) at Massachusetts Institute of TechnologyBachelor's degree, Computer Software Engineering, Bachelor's degree, Computer Software Engineering at Universidade de Brasília
English
Github Skills (47)
data-quality10
jupyter10
exploratory-data-analysis10
pandas-dataframe10
eda10
big-data-analytics10
jupyter-notebook10
pandas9
data-exploration9
python9
machine-learning9
pandas-profiling9
statistics9
profiling9
data-analysis9
Programming languages (5)
Github contributions (5)
UnBArqDsw/2020.1_G2_TCLDL
Sep 2020 - Dec 2020
Our project aims to develop a web application for the "The Computational Limits of Deep Learning" where will be possible for people/community to have access to the data and the paper's analysis, and also allowing them to continuously contribute with it.
Contributions:1 review, 59 PRs, 59 pushes in 3 months
limitspythondeep-learningweb-applicationmachine-learning
gabrielfilipe7unb/DataScience_Introduction
Apr 2019 - Nov 2019
Data Science Introductions Practices
Contributions:22 PRs, 33 pushes, 15 branches in 7 months
pythonsciencedata-sciencemachine-learningpandas
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