Graph Machine Learning
Representation learning on graphs, graph neural networks, and the theory of relational data.
Independent AI Research & Engineering
Exploring AI with rigor and purpose.
We are an independent two-person research and development collaboration working across machine learning theory, graph learning, model privacy, and practical AI applications.
Graph MLPrivacyResearch
Research interests
Where we focus
Connecting mathematical foundations with careful evaluation and implementation.
Privacy & Reliability
Membership inference, model behavior, rigorous evaluation, and privacy risks in learning systems.
Applied AI Systems
Practical machine learning software, human-centered AI applications, and research prototypes.
Selected work
Research & projects
A selection of publicly available repositories exploring theory and real-world applications.
Research · Graph learning
Graph Membership Inference
Research code and experiments examining membership privacy risks in graph learning.
View on GitHubApplied AI · Accessibility
ASL PyTorch
Experiments and implementation work related to sign language understanding with machine learning.
View on GitHubApplied AI · Education
AR Lecture Assistant
An augmented-reality learning assistant prototype that explores AI-supported classroom experiences.
View on GitHubContact
Let's connect.
Interested in discussing AI research, engineering, or a potential collaboration? Reach us by email.