Skip to content
View Audency's full-sized avatar
15 followers · 41 following

Achievements

Achievement: YOLO

Achievements

Achievement: YOLO

Block or report Audency

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Audency/README.md

ORCID LinkedIn Website Gmail LSHTM

About Me

Researcher in Health Data Science at the London School of Hygiene & Tropical Medicine (LSHTM), working on a Wellcome Trust-funded project on predictive modelling for stillbirths and neonatal deaths across Sub-Saharan Africa. Visiting Researcher at PROADI-SUS, Hospital Israelita Albert Einstein (São Paulo). Former Technical Consultant (Epidemiologist & Data Scientist) at PAHO/WHO.

Education: PhD in Public Health – Epidemiology (USP) · MPH (UFBA) · MBA in Data Science & Analytics (USP-Esalq) · MBA in AI & Big Data (ICMC-USP) · BSc Nutrition (Lúrio University)

Research Interests

Maternal & Neonatal Health Machine Learning in Health Predictive Modelling Spatial Epidemiology Big Data in Public Health Health Inequalities Nutrition Epidemiology Federated Learning

Tech Stack

Languages & Statistics

Machine Learning & Deep Learning

Data & Visualization

Tools & Reproducible Research

MLOps & Data Management

Featured Projects

Predictive Modelling & AI in Health

Project Description Stack
🔬 Stillbirths & Neonatal Deaths – SSA Multi-country predictive models using DHS across Sub-Saharan Africa Deep Learning DHS
🌍 Federated Learning – 16 African Countries Privacy-preserving FL with FedProx + DP-SGD on DHS data FedProx DP-SGD Flower
🇧🇷 Federated Learning – Brazil pFedMe + Flower across 5 Brazilian macroregions pFedMe Flower
🔄 Transfer Learning – Africa to Brazil Cross-continent deep learning fine-tuning Transfer Learning Fine-tuning
📊 XGBoost Neonatal Mortality Avoidable neonatal mortality with explainability XGBoost SHAP TRIPOD-AI

Epidemiology & Spatial Analysis

Project Description Stack
🗺️ Municipal Perinatal Clustering Clustering municipalities by perinatal indicators (2012–2023) k-means Markov RF
📉 Maternal Mortality Brazil 2000–2024 Interrupted time-series of maternal mortality trends ITS Joinpoint
🦟 Syphilis Trends – Brazil Temporal trends and spatial patterns of congenital syphilis Spatial Joinpoint
📋 Systematic Review – Neonatal ML SR of ML models for neonatal death & stillbirth prediction Meta-analysis R
🏥 Fetal Weight Estimation with ML ML models for fetal weight prediction ML Regression

GitHub Analytics

  





Affiliations & Research Groups

Institution Role
London School of Hygiene & Tropical Medicine (LSHTM) Researcher in Health Data Science
PROADI-SUS, Hospital Israelita Albert Einstein Visiting Researcher
MARCH Centre, LSHTM Research Group Member
LABDAPS, University of São Paulo Research Group Member
Rede CoVida, Brazil Research Group Member
UFMS – Epi & Applied Mathematics Group Research Group Member

Profile Views

Bridging epidemiology, data science, and global health to generate evidence for policy.

Pinned Loading

  1. Prediction-of-Gestational-Weight-Gain-for-Pregnancy Prediction-of-Gestational-Weight-Gain-for-Pregnancy Public

    Identificação precoce de mulheres com maior risco de ganho de peso excessivo durante a gestação pode permitir intervenções precoces para prevenir complicações e promover um ganho de peso adequado

    Jupyter Notebook 1

  2. Meningitis-DiagnosisML Meningitis-DiagnosisML Public

    A machine learning initiative to improve the diagnostic processes for bacterial meningitis. Utilizing clinical and laboratory data from the SINAN database in São Paulo, this project develops predic…

    Jupyter Notebook

  3. Predict-cervical-cancer- Predict-cervical-cancer- Public

    This study uses machine learning models to predict in-hospital mortality among patients with cervical cancer in this region, aiming to identify key predictive factors that can support the implement…

    Jupyter Notebook

  4. Predictors-of-Low-Birth-Weight-using-Machine-Laerning- Predictors-of-Low-Birth-Weight-using-Machine-Laerning- Public

    Predictors of Low Birth Weight using Machine Laerning

    Jupyter Notebook

  5. maternal-mortality-brazil-2000-2024 maternal-mortality-brazil-2000-2024 Public

    Trends and determinants of maternal mortality in Brazil (2000-2024): interrupted time-series analysis

    HTML

  6. Spatial-Distribution-of-Maternal-and-Child-Health-Indicators-in-Tanzania Spatial-Distribution-of-Maternal-and-Child-Health-Indicators-in-Tanzania Public

    This study analyzes the spatial distribution of four key maternal and child health indicators across Tanzania. Using geospatial analysis and data visualization techniques, we examine regional dispa…

    R