A Numerical Magnetic Resonance Imaging (MRI) Simulation Platform

Quantitative MRI Made Easy with qMRLab: MRI software for data Simulation, analysis and visualization

Data Forge — a modern data stack playground to practice flows and best practices, not just tools. Spark, Trino, Kafka, Iceberg, ClickHouse, Airflow, MinIO, Superset — all wired together locally with Docker Compose.

Generic IoT data simulator. Provides possibility to replay datasets or generates data on fly. Supports various IoT platforms out of the box.

simstudy: Illuminating research methods through data generation

Agent4Edu: Generating Learner Response Data by LLM-based Agents for Intelligent Education Systems (AAAI 2025)

Foundational tools for BCG X's data science packages.

[ECCV 2024] Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging

🧠 Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments.

R Package With Shiny App to Perform and Visualize Clustering of Count Data via Mixtures of Multivariate Poisson-log Normal Model

R Package to Perform Clustering of Three-way Count Data Using Mixtures of Matrix Variate Poisson-log Normal Model With Parameter Estimation via MCMC-EM, Variational Gaussian Approximations, or a Hybrid Approach Combining Both.

Cryptocurrency reddit sentiment analysis application.

Generate simulated illumina sequence reads from a reference sequence

Generate simulated oxford nanopore reads from a reference sequence

A program that simulates answers given by a crowd to multiple choice questions with either a single or multiple answers correct, and writes it to a CSV

Generate synthetic longitudinal correlated data using distributions and correlations from real-world observational data

Software to simulate compendium-wide gene expression data using a VAE.

Simulate data for simple experimental designs using the R package faux (https://github.com/debruine/faux/).

The code simulates the movement of birds between various stations, generating data points for each visit, including the station visited, exact (slightly perturbed) coordinates, and a timestamp. This data is stored in a GeoDataFrame that can be used for spatial analysis and visualization.

This project simulates server performance data (CPU, Memory, Network Traffic) for multiple servers across time intervals and applies K-Nearest Neighbors (KNN) for similarity analysis and prediction.