Louisiana State University
Open-source tools for topology, machine learning, and scientific computing.
Languages: Python, R, C#, LaTeX, Beamer.
Machine Learning & Deep Learning: TensorFlow, PyTorch, PyTorch Geometric, scikit-learn.
Scientific Computing: NumPy, SciPy, NetworkX
Topological Deep Learning Frameworks: TopoModelX, TopoNetX, TopoEmbedX.
ODE solver. Higher Order Splitting Method to solve ODEs.
Statistical tests: ANOVA, A/B test, Bayesian A/B Testing.
I develop Python packages for topological deep learning on graphs, hypergraphs, simplicial complexes, and cellular complexes. Explore the TopoX collection on GitHub.
Higher-order network modeling
Python package for modeling entities and relationships in higher-order networks, including meshes, simplicial complexes, and cell complexes.
View GitHub repository
Learning on topological domains
Python package for efficient deep learning models on topological domains, including simplicial and cell complexes.
View GitHub repository
Topological representation learning
Python package for efficient representation learning on relational systems with topological domains, including social networks and proteins.
View GitHub repository
Scientific computing
Higher-order operator splitting schemes with complex coefficients and applications. Developed in collaboration with Arun Banjara.
View GitHub repository