DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

Polycrystal generation and meshing

Data Analysis program and framework for materials science data analytics, based on the managing framework SIMPL framework.

To classify trades into buyer- and seller-initiated.

micapipe from the Multimodal imaging and connectome analysis lab (http://mica-mni.github.io) at the Montreal Neurological Institute. Read The Docs documentation below

Microstructure modeling, mesh generation, analysis, and visualization.

MATBOX is an open-source MATLAB toolbox dedicated to microstructure analsyis of porous/heterogeneous materials

Cellular automata code for alloy nucleation and solidification written with Kokkos

Toolbox for particulate microstructure modelling

An Optimized, Easy-to-use, Open-source GPU Solver for Large-scale Inverse Homogenization Problems

visualize financial microstructure 📈 & debug trading bots 🤖

A MATLAB/C++ implementation of solid texture synthesis algorithms for constructing statistically representative 3D microstructure datasets from only 2D data.

MicroSim is a project under the National Supercomputing Mission, Govt of India. The project offers a set of codes that can use high performance computing to simulate microstructure evolution using the Phase Field technique. Follow us on LinkedIn: https://www.linkedin.com/company/microstructure-simulator/

Gray-matter Based Spatial Statistics

Script for the generation of finite-thickness interface elements for polycrystal microstructure modelling

This repo includes the dataset/code of 3D Convolutional Neural Network for material property prediction

A scikit-learn compatible classifier to perform trade classification in Python.

Graded Multiscale Fluid Topology Optimization using Neural Networks

My quant portfolio leverages quantitative finance and data-driven insights to optimize investment strategies. Using advanced models, statistical analysis, and machine learning, I develop systematic trading strategies to capitalize on market inefficiencies and generate alpha.

GAN for synthesizing microstructures based on processing conditions.