Foundational tools for BCG X's data science packages.
[ECCV 2024] Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
🧠 Model-Driven test data generation platform enabling developers to create realistic, scalable, and privacy-compliant test data. Features model-driven data generation, GDPR compliance, and seamless Python integration.
Cryptocurrency reddit sentiment analysis application.
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
Software to simulate compendium-wide gene expression data using a VAE.
A flexible Python framework for generating, fitting, and visualizing noisy nonlinear data. Perfect for educational purposes, algorithm testing, and demonstrating statistical concepts. Includes tools for various noise models, custom function fitting, robust error metrics, and publication-quality visualizations
This repository contains projects and exercises I completed during my "Big Data Architecture" course. It reflects the concepts I’ve learned about data processing using Apache Spark and PySpark.
A sample database with a random data model and automatic reporting. (PL doc)
An application for randomly generating telecommunication payment data.
Code for reproducing my thesis results.
High-performance, multi-stream data ingestion simulator Built for testing real-time pipelines, PB-scale throughput, and stream processing systems like Kafka, Flink, FastAPI, and Iceberg.
Создание синтетического датасета на основе cимуляции свойств физики SEM
Code for JDST 2023 paper: "Simulating Realistic Continuous Glucose Monitor Time Series By Data Augmentation" by L.Gomez, A.Toye, R.Hum and S.Kleinberg
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