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    • CS 4099: ST: Graph Machine Learning
    • CS 4432: Database Systems II
    • CS/DS 541: Deep Learning
    • DS 3010: Data Science III: Computational Methods
  • Publications
    • CLaDMoP: Learning Transferrable Models from Successful Clinical Trials via LLMs
    • Mitigação de Envenenamento de Rótulos em Sistemas de Detecção de DDoS Federados
    • Stop treating `AGI' as the north-star goal of AI research
    • MEXA-CTP: Mode Experts Cross-Attention for Clinical Trial Outcome Prediction
    • Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics
    • Reducing Biases towards Minoritized Populations in Medical Curricular Content via Artificial Intelligence for Fairer Health Outcomes
    • Devil in the Noise: Detecting Advanced Persistent Threats with Backbone Extraction
    • Temporally-aware node embeddings for evolving networks topologies
    • Towards Detecting Cascades of Biased Medical Claims on Twitter
    • Learning building occupants’ indoor environmental quality complaints and dissatisfaction from text-mining Booking.com reviews in the United States
    • Anatomy of Hate Speech Datasets: Composition Analysis and Cross-dataset Classification
    • Bayes and Laplace Versus the World: A New Label Attack Approach in Federated Environments Based on Bayesian Neural Networks
    • Helping Fact-Checkers Identify Fake News Stories Shared through Images on WhatsApp
    • On network backbone extraction for modeling online collective behavior
    • Top-Down Deep Clustering with Multi-Generator GANs
    • DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs
    • Uncovering Coordinated Communities on Twitter During the 2020 U.S. Election
    • Uncovering Discussion Groups on Claims of Election Fraud from Twitter
    • Effects of population mobility on the COVID-19 spread in Brazil
    • On the dynamics of political discussions on Instagram: A network perspective
    • Analysis and Prediction of Users’ Emotional Tone in Reddit Mental Health Communities
    • Encoding Physical Conditioning from Inertial Sensors for Multi-step Heart Rate Estimation
    • Encoding physical conditioning from inertial sensors for multi-step heart rate regression
    • Evaluating the state-of-the-art in mapping research spaces: A Brazilian case study
    • Fairness via AI: Bias Reduction in Medical Information
    • Mixture Variational Autoencoder of Boltzmann Machines for Text Processing
    • Predicting user emotional tone in mental disorder online communities
    • Quão efetivas são Redes Neurais baseadas em Grafos na Detecção de Fraude para Dados em Rede?
    • Sequence-Based Word Embeddings for Effective Text Classification
    • Characterizing (Un)moderated Textual Data in Social Systems
    • Modelos de Previsão do Tom Emocional de Usuários em Comunidades de Saúde Mental no Reddit
    • Unveiling Community Dynamics on Instagram Political Network
    • Supervised Learning for Fake News Detection
    • Aprendizado de Máquina para Previsão do Tempo de Execução de Aplicações Spark
    • Characterizing Directed and Undirected Networks via Multidimensional Walks with Jumps
    • Explainable Machine Learning for Fake News Detection
    • Gray-Box Models for Performance Assessment of Spark Applications
    • Machine Learning for Performance Prediction of Spark Cloud Applications
    • Modeling Dynamic Ideological Behavior in Political Networks
    • SEMPLICe: Um Modelo Sequencial de Proficiência em Comunidades Online para Aprendizado de Idioma
    • Towards Understanding Political Interactions on Instagram
    • Análise de Algoritmos de Clusterização para Experimentos Randomizados em Redes Sociais de Larga Escala
    • Análise das Interações Sociais em Comunidades Online de Aprendizado de Idiomas: um estudo de caso no Reddit
    • Análise de Comunidades de Suporte a Transtornos de Saúde Mental do Reddit
    • Automatic Identification of Best Attributes for Indexing in Data Deduplication
    • Estimation Errors in Network A/B Testing Due to Sample Variance and Model Misspecification
    • Inside the Right-Leaning Echo Chambers: Characterizing Gab, an Unmoderated Social System
    • Modelos de Resposta para Experimentos Randomizados em Redes Sociais de Larga Escala
    • Online Social Networks in Health Care: A Study of Mental Disorders on Reddit
    • Reddit Weight Loss Communities: Do They Have What It Takes for Effective Health Interventions?
    • Selective harvesting over networks
    • An example journal article
    • Targeted Network Recruitment on a Budget
    • An example conference paper
    • Characterizing Branching Processes from Sampled Data
    • On Set Size Distribution Estimation and the Characterization of Large Networks via Sampling
    • Sampling directed graphs with random walks
    • Heterogeneous download times in a homogeneous BitTorrent swarm
    • Assortative Mixing in BitTorrent-Like Networks
    • Formação de clusters em redes P2P por similaridade entre os nós
    • Novas evoluções integradas à ferramenta Tangram-II v3.1
    • Avaliação de um mecanismo de previsão adaptativa de perdas de pacotes com aplicação à transmissão de Voz sobre IP
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Pandas

Oct 26, 2023 · 1 min read
Go to Project Site

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures.

Last updated on Oct 26, 2023
Hugo Wowchemy Markdown
Fabricio Murai
Authors
Fabricio Murai
Assistant Professor of CS, Data Science & AI
PyTorch Oct 26, 2023 →

© 2025 Fabricio Murai. This work is licensed under CC BY NC ND 4.0

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