我深深致力于开源软件，并在15年多的时间里一直在构建专业级工具——可以追溯到 Google Code 时代。我的工作将严格的统计方法与现代软件工程实践相结合，包括版本控制（Git/GitHub）、持续集成、代理 AI、容器技术和敏捷方法。我领导科学软件开发团队交付高性能、可靠且用户友好的工具，这些工具被研究人员和从业者广泛采用。我的大部分工作是用 C++ 构建的，为 R 和 Python 提供包装器，针对高性能计算环境进行优化。在所有项目中，我在设计时都考虑到性能和可用性，确保复杂的方法既可扩展又易于访问。
近年来，我也将 AI 融入工作，推动研发与创新（一些示例见此处）。
重点项目包括：
epiworld
一个用 C++ 编写的高级基于代理的建模框架，专为流行病学建模的快速原型设计而设计。该库可在 R、Python 以及 shiny 包中使用。其最值得注意的应用是对美国近期麻疹爆发的建模。
GitHub 麻疹模拟器
rgexf
创建、读取和写入 ‘GEXF’（图形交换 ‘XML’ 格式）图形文件（用于 ‘Gephi’ 等）。使用 ‘XML’ 包，rgexf 允许读取和写入 GEXF 文件，包括属性、‘GEXF’ 可视化属性（如颜色、大小和位置）、网络动态（节点和边）以及边的权重。用户可以逐元素或通过数据框大量构建/处理图形，通过 ‘gexf-js’（一个 ‘javascript’ 库）在网页浏览器上可视化图形，并与 ‘igraph’ 包交互。
GitHub gexf-js 线上展示
ergmito
使用精确统计量对小型网络的指数随机图模型（ERGMs）进行模拟和估计，如 Vega Yon 等人（2020）所示。与 ‘ergm’ 包不同，‘ergmito’ 避免使用马尔可夫链最大似然估计器（MC-MLE），而是使用最大似然估计器（MLE）来拟合小型网络的 ERGMs。由于对小型网络来说详尽枚举在计算上是可行的，因此这个 R 包利用了这一点，并提供了直接计算似然函数和其他相关函数的工具，这意味着在许多情况下，小型网络的 ERGMs 估计和模拟都可以比基于模拟的算法更快、更准确。
GitHub 论文
以下是我构建或贡献的软件包的详尽列表。您可以在 我的 GitHub 上查看我最近的贡献和正在进行的开源项目
引用数据来自 OpenAlex，下载量来自 CRAN。更新于 2026-10-25。
软件包活跃2026
Build, Import and Export GEXF Graph Files
Vega Yon, G. G., 
Fábrega Lacoa, J., & Kunst, J.
CRAN0.17.0downloads656kstars32被引用6
networksvisualizationdata formats
CRAN•Docs•Repo•DOI
简介
Create, read, and write 'GEXF' (Graph Exchange 'XML' Format) graph files, used in 'Gephi' and others. Using the 'XML' package, rgexf allows reading and writing GEXF files, including attributes, 'GEXF' visual attributes (such as color, size, and position), network dynamics (for both edges and nodes), and edges' weights. Users can build and handle graphs element-by-element or massively through data frames, visualize the graph on a web browser through 'gexf-js' (a 'javascript' library), and interact with the 'igraph' package.
Analysis of Diffusion and Contagion Processes on Networks
Vega Yon, G. G., Olivera Morales, A., & 
Valente, T.
CRAN1.25.0downloads59kstars93
networksdiffusion
CRAN•Docs•Repo•DOI
简介
Empirical statistical analysis, visualization, and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente et al. (2015), Valente (1995), Myers (2000), Iyengar and others (2011), Burt (1987), among others.
Statistical Inference of Annotated Phylogenetic Trees
Vega Yon, G. G.
CRAN0.3-6downloads21kstars6被引用1
phylogeneticsbayesiangenomics
CRAN•Repo•DOI
简介
Implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees, as described in Vega Yon et al. (2021). Focusing on computational efficiency, 'aphylo' makes it possible to estimate pooled phylogenetic models, including thousands (hundreds) of annotations (trees) in the same run. The package also provides tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction), and goodness-of-fit assessment.
Beautiful graph drawing
Vega Yon, G. G., & 
Bischoff, P.
CRAN0.4-0downloads23kstars53
networksvisualization
CRAN•Docs•Repo•DOI
简介
A graph visualization engine that emphasizes aesthetics while providing default parameters that yield out-of-the-box, nice visualizations. The package is built on top of 'The Grid Graphics Package' and works seamlessly with 'igraph' and 'network' objects.
your to-go motif accountant
Vega Yon, G. G.
CRAN0.2.2downloads3.2k
networksstatistical models
CRAN•Docs•Repo•DOI
简介
Provides the 'C++' header-only library 'barry' for use in R packages. 'barry' is a 'C++' template library for counting sufficient statistics on binary arrays and building discrete exponential-family models. It provides tools for sparse arrays, user-defined count statistics, support set constraints, power set generation, and includes modules for Discrete Exponential Family Models (DEFMs) and network statistics. By placing these headers in this package, it offers an efficient distribution system for CRAN, avoiding replication of this code across the sources of other packages. This package follows the same approach as the 'BH' package, which provides 'Boost' headers for R packages.
Estimation and simulation of Multi-binary response models
Vega Yon, G. G.
CRAN0.2.1.0downloads3kstars1
statistical modelsnetworks
CRAN•Docs•Repo•DOI
简介
Multi-binary response models are a class of models that allow for the estimation of multiple binary outcomes simultaneously. This package provides functions to estimate and simulate these models using the Discrete Exponential-Family Models (DEFM) framework, implementing the models described in Vega Yon, Valente, and Pugh (2023). DEFMs include Exponential-Family Random Graph Models (ERGMs), which characterize graphs using sufficient statistics, also the core of DEFMs. Using sufficient statistics, the package describes data through meaningful motifs, such as transitions between different states and the joint distribution of the outcomes.
Fast Agent-Based Epi Models
Meyer, D., 
Pulsipher, A., & Vega Yon, G. G.
CRAN0.14.0.0downloads17kstars14被引用2
epidemiologyagent-based models
CRAN•Docs•Repo•DOI
简介
A flexible framework for Agent-Based Models (ABM), the 'epiworldR' package provides methods for prototyping disease outbreaks and transmission models using a 'C++' backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents' features, providing great complexity for the model dynamics. 'epiworldR' is ideal for simulation studies featuring large populations.
Python Bindings for epiworld
Vega Yon, G. G., & 
Banks, O.
version0.15.0-0
epidemiologyagent-based models
Link•Repo
简介
Python bindings for the 'epiworld' C++ agent-based modeling library. It provides a general framework for modeling disease transmission, including multiple diseases, user-defined policies, feature-dependent transmission, and parallel execution of multiple simulations.
epiworld Agent-Based Models in the Browser via WebAssembly
Vega Yon, G. G.
npm0.18.0-0downloads325
epidemiologyagent-based modelsvisualization
Link•Docs•Repo
简介
Runs the 'epiworld' agent-based epidemic simulation engine in the browser (and Node) by compiling it to WebAssembly. It provides a JavaScript API and a drop-in <epiworld-model> web component, so real epiworld models, such as SIR, SEIR, and measles, can run on any static website with no server.
Analyze Outbreak Models of Multi-Group Populations with Vaccination
Toth, D., 
Wagoner, J., Ray, W., & Vega Yon, G. G.
CRAN0.1.1downloads2.1kstars2
epidemiology
CRAN•Docs•Repo
简介
Models infectious disease dynamics in populations with multiple subgroups having different vaccination rates, transmission characteristics, and contact patterns. Calculates final and intermediate outbreak sizes, forms age-structured contact models with automatic fetching of U.S. census data, and explores vaccination scenarios with an interactive 'shiny' dashboard for a model with two subgroups, as described in Nguyen et al. (2024) and Duong et al. (2026).
Measles Epidemiological Models
Vega Yon, G. G.
CRAN0.2.0downloads3kstars5
epidemiologyagent-based models
CRAN•Repo•DOI
简介
A specialized collection of measles epidemiological models built on the 'epiworldR' framework. This package is a spinoff from 'epiworldR' focusing specifically on measles transmission dynamics. It includes models for school settings with quarantine and isolation policies, mixing models with population groups, and risk-based quarantine strategies. The models use Agent-Based Models (ABM) with a fast 'C++' backend from the 'epiworld' library, making it ideal for studying measles outbreaks, vaccination strategies, and intervention policies.
Fast and Effortless Calibration of Agent-Based Models using Machine Learning
Najafzadehkhoei, S., Vega Yon, G. G., & 
Modenesi, B.
CRAN0.1.4downloads1.9kstars1
epidemiologyagent-based modelsmachine learning
CRAN•Docs•Repo•DOI
简介
Provides tools and pre-trained Machine Learning (ML) models for calibration of Agent-Based Models (ABMs) built with the R package 'epiworldR', implementing methods described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025). Users can automatically calibrate ABMs in seconds with pre-trained ML models, effectively focusing on simulation rather than calibration, bridging a gap that allows public health practitioners to run their own ABMs without the advanced technical expertise often required by calibration.
Tools for Studying Imaginary Cognitive Social Structure
Najafzadehkhoei, S., Vega Yon, G. G., & 
Tanaka, K.
CRAN0.1.0downloads2.7kstars1被引用3
networkscognition
CRAN•Docs•Repo•DOI
简介
Tools for measuring and testing imaginary cognitive social structure (CSS) motifs — patterns of false positives and negatives in cognitively perceived social networks relative to the actual network, categorized as partially false, completely false, and mixed false imaginary motifs, as described in Tanaka and Vega Yon (2024).
Publication-Ready Tables and Summaries for Exponential-Family Random Graph Models
Vega Yon, G. G.
CRAN0.1.0downloads709stars3
networksergm
CRAN•Docs•Repo•DOI
简介
Creates publication-ready tables documenting exponential-family random graph models (ERGMs), a class of statistical models for social networks (Robins et al., 2007, <doi:10.1016/j.socnet.2006.08.002>). Tables describe model terms through their definitions, mathematical representations, and graphical representations, and can be generated from ERGM formulas or from models fitted with the 'ergm' package (Hunter et al., 2008, <doi:10.18637/jss.v024.i03>). Resulting tables can be integrated into 'quarto' and 'rmarkdown' documents.
Agent-Based Modeling of Measles in US cities hosting the 2026 FIFA World Cup
Vega Yon, G. G.
epidemiologyagent-based modelsvisualization
Link•Repo
简介
Agent-based measles outbreak simulations across the 11 major U.S. cities hosting the 2026 FIFA World Cup. Built on the 'epiworldR' and 'measles' R packages, and using census-derived age structure and MMR vaccination coverage, the project provides baseline scenario dashboards summarizing simulated outbreak size over time and the probability that outbreaks exceed given case-count thresholds for each host city. With large international crowds expected, the dashboard supports public-health preparedness by helping to understand measles transmission risk around the tournament.
AI-powered Dashboard to Explore the InsighNet community
Vega Yon, G. G.
stars1
text analysis
Link•Repo
简介
An AI-powered dashboard exploring the InsightNet research community: academic profiles and publications for researchers affiliated with InsightNet's centers. A scheduled pipeline collects papers and preprints from ORCID, Europe PMC, PubMed, arXiv, medRxiv/bioRxiv, and Crossref, and daily activity from public web pages, RSS/Atom, Bluesky, and GitHub, normalizing it into a static snapshot. The standalone site includes an AI-assisted expert-finder that answers questions from the collected publications and profiles, citing the underlying record, a browser-side keyword search, and a browsable, filterable publication list, with no runtime server or frontend dependencies.
Dependency-light Exponential Random Graph Model Simulator
Vega Yon, G. G.
npm0.3.0downloads583stars1
networksergmsimulation
Link•Docs•Repo
简介
A small, dependency-light JavaScript simulator for Exponential Random Graph Models (ERGMs), built for teaching and presentations. It simulates from user-specified model parameters and provides an interactive widget for exploring how density, homophily, and reciprocity change network structure in real time.
Interactive ERGM widget for Quarto
Vega Yon, G. G.
version0.3.0-0
networksergmquarto
Link•Repo
简介
A Quarto extension that embeds the 'ergm-js' interactive Exponential Random Graph Model (ERGM) simulator in HTML-based Quarto output, including documents, websites, books, and 'revealjs' decks. It installs with `quarto add` and provides an `ergm-widget` shortcode for interactive network simulation demos.
Epidemiological Cost Calculator
Banks, O., Wang, E., 
Nelson, R., & Vega Yon, G. G.
stars4
epidemiologyhealth economicspolicy
Link•Repo
简介
Evaluating the cost implications of public health interventions requires accessible, transparent, and highly adaptable modeling platforms. This EPidemiological Cost Calculator (EPICC) is a novel, browser-based utility designed to execute arbitrary epidemiological models directly within a web environment, using Python models executed in-browser via 'stlite'. EPICC allows researchers and policymakers to select specific disease models, calibrate parameters to reflect localized settings, and dynamically simulate the economic outcomes of various policy scenarios and intervention points. To ensure methodological rigor, the tool prioritizes transparency by fully documenting all underlying equations and default values, enabling users to appropriately contextualize outputs and limitations. Furthermore, EPICC facilitates seamless reproducibility and stakeholder collaboration; model states are continuously encoded as plain text within the URL for instant sharing, parameter configurations can be exported for longitudinal analysis, and simulation results can be compiled into standardized PDF reports. By integrating robust computational capabilities with user-centric data management, EPICC provides an efficient, accessible framework for translating complex epidemiological data into evidence-based policy decisions.
软件包活跃2025
Exponential Random Graph Models for Small Networks
Vega Yon, G. G., & 
de la Haye, K.
CRAN0.3-2downloads29kstars9被引用45
networksstatistical modelsergm
CRAN•Docs•Repo•DOI
简介
Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics, as shown in Vega Yon et al. (2020). As a difference from the 'ergm' package, 'ergmito' circumvents using a Markov-Chain Maximum Likelihood Estimator (MC-MLE) and instead uses a Maximum Likelihood Estimator (MLE) to fit ERGMs for small networks. As exhaustive enumeration is computationally feasible for small networks, this R package takes advantage of this and provides tools for calculating likelihood functions and other relevant functions directly, meaning that in many cases both estimation and simulation of ERGMs for small networks can be faster and more accurate than simulation-based algorithms.
Shiny interface for epiworldR
Vega Yon, G. G., Meyer, D., & Pulsipher, A.
CRAN0.2.3downloads15kstars3
epidemiologyagent-based modelsvisualization
CRAN•Docs•Repo•DOI
简介
R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR', with support for the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.
WebAssembly Port of epiworld
Banks, O., & Vega Yon, G. G.
version0.0.1
epidemiologyagent-based modelsvisualization
Link•Repo
简介
A web application that ports the 'epiworld' epidemiological agent-based modeling framework to WebAssembly, bringing epiworld simulations to the browser.
A Package for Bayesian Renewal Modeling with JAX and NumPyro
Bayer, D., 
Morris, D. H., Vega Yon, G. G., Martin, T., & Bidari, S.
version0.1.0stars30
epidemiologybayesian
Link•Repo
简介
A flexible tool for simulation and statistical inference of epidemiological models, emphasizing hierarchical multi-signal renewal models. Built on top of the 'numpyro' Python library, 'PyRenew' provides core components for model building. A renewal model estimates new infections from recent past infections using a generation interval, from which it infers the time-varying reproduction number R(t). PyRenew's strength lies in multi-signal integration for pooling information across diverse observed data streams, such as hospital admissions, wastewater concentrations, and emergency department visits, each with distinct observation delays, noise characteristics, and spatial resolutions.
Jointly infers infection dynamics from wastewater data and epidemiological indicators
Johnson, K., Morris, D., 
Abbott, S., Bernal Zelaya, C., Vega Yon, G. G., Bayer, D., 
Magee, A., & 
Olesen, S.
version0.1.1.99stars34
epidemiologybayesian
Link•Repo
简介
An implementation of a hierarchical semi-mechanistic renewal approach jointly calibrating to multiple wastewater concentration datasets from subsets of a specified population and epidemiological indicators, such as cases or hospital admissions, from the whole population. The framework extends the widely used semi-mechanistic renewal framework 'EpiNow2', using a Bayesian latent variable approach implemented in the probabilistic programming language 'Stan'. The package fits these two data sources and produces estimated and forecasted hospital admissions, estimated and forecasted wastewater concentrations, and global and local R(t) estimates for the subpopulations represented by each wastewater catchment area.
A Lightweight Wrapper for 'Slurm'
Vega Yon, G. G.
CRAN0.5-4downloads38kstars61被引用3
hpcparallel computing
CRAN•Repo•DOI
简介
'Slurm', Simple Linux Utility for Resource Management, is a popular 'Linux'-based software used to schedule jobs in 'HPC' (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to that found in the 'parallel' R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the 'parallel' package.
A friendly MCMC framework
Vega Yon, G. G., & 
Marjoram, P.
CRAN0.5-2downloads36kstars16被引用7
bayesianmcmc
CRAN•Repo•DOI
简介
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing the Metropolis-Hastings algorithm in a modular way, allowing users to specify an automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Among the methods included are Haario (2001) Adaptive Metropolis, Vihola (2012) Robust Adaptive Metropolis, and Thawornwattana et al. (2018) Mirror transition kernels.
库活跃2022
A Flexible and General Agent Based Model Engine
Vega Yon, G. G.
version0.0-1stars10
epidemiologyagent-based modelshpc
Link•Repo
简介
A general framework for epidemiologic simulation implemented as a header-only 'C++' template library. The core principle of 'epiworld' is fast epidemiological prototyping for building complex models quickly: models can have an arbitrary set of states, viruses and tools (e.g., vaccines, mask-wearing) can be designed with arbitrary features, and multiple tools and viruses can coexist in the same simulation. It depends only on the standard library and is capable of over 150 million person-day simulations per second.
Implementing the Felsenstein's Tree Pruning algorithm
Vega Yon, G. G.
version0.0-1stars1
phylogeneticsalgorithms
Link•Repo
简介
A C++ template library implementing Felsenstein's tree-pruning algorithm for efficiently computing likelihood functions on phylogenies. The library reads a tree object as a list of source-target dyads (edges) and allows users to store arbitrary arguments via memory pointers and 'std::function' callbacks invoked with those arguments and the tree structure data. Trees are stored as offspring and parent lists, accessible through a 'TreeIterator' class implementing pre- and post-order traversals for pruning.
Stata Module for Parallel Computing
Vega Yon, G. G., & 
Quistorff, B.
version1.20.0stars136
hpcparallel computing
Link•Repo
简介
A Stata module for parallel computing. By organizing a job into several Stata instances, parallel provides out-of-the-box parallel computing for faster simulations, bootstrapping, reshaping big data, and more, without requiring any knowledge of parallel computing or a Stata/MP license. Depending on the number of available processors, parallel has shown to dramatically speed up computations, sometimes outperforming Stata/MP itself.
Working with Google's 'Public Data Explorer' DSPL Metadata Files
Vega Yon, G. G.
CRAN0.16.1downloads63kstars8
data formats
CRAN•Repo•DOI
简介
Provides a collection of functions to set up 'Google Public Data Explorer' data visualization tool with your own data, building automatically the corresponding DataSet Publishing Language file, or DSPL (XML), metadata file jointly with the CSV files. All zip-up and ready to be published in 'Public Data Explorer'.
Implementation of Artificial Bee Colony (ABC) Optimization
Vega Yon, G. G., & Muñoz, E.
CRAN0.15.0downloads95kstars32
optimization
CRAN•Repo•DOI
简介
An implementation of Karaboga's (2005) Artificial Bee Colony Optimization algorithm. This was developed upon the basic version programmed in C and available at the algorithm's official website.
Out-of-the-box analysis and reporting tools for twitter
Vega Yon, G. G.
version0.16stars38
text analysisnetworks
Link•Repo•DOI
简介
A set of tools to download, process, and analyze tweets, including methods for exporting the outputs through 'D3js'.
没有符合这些筛选条件的项目。
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