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LanternCode/README.md

Adam Machowczyk

PhD candidate in Computer Science at the University of Leicester, researching graph machine learning, Deep Graph (graph-to-graph) Transformation, benchmarking, and reproducible model evaluation. Thesis submission expected September 2026.

Featured research — edge-dgt-eval

Open-source architecture evaluation framework for graph-to-graph learning, developed as a key contribution of my PhD research.

It enables controlled comparison of non-parametric, feedforward, convolutional, attention-based, and graph-native architectures under shared experimental conditions, across synthetic and real-world graph learning tasks.

Research focus: graph transformation · benchmarking · reproducibility · architecture comparison · relational inductive bias

Selected publications

Academic website · ORCID · LinkedIn

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  1. edge-dgt-eval edge-dgt-eval Public

    An architecture evaluation framework for graph-to-graph edge classification tasks. Supports both dense (image-style) models and GNN encoders under a shared evaluation contract.

    Python

  2. graph-transformation-learning-prototypes graph-transformation-learning-prototypes Public

    Public research prototypes and directional baseline experiments for graph transformation learning, developed alongside my PhD research.

    Python

  3. RAPPAR RAPPAR Public

    Full-stack web application for evaluating and cataloguing rap songs. Built with PHP, JavaScript, and a database-backed architecture.

    PHP

  4. TRBS TRBS Public

    Team simulation project for The Remnants TTRPG. My contributions focused on team coordination, core logic, JavaScript implementation, integration, and debugging.

    JavaScript

  5. RPG-Session-Hub RPG-Session-Hub Public

    Full-stack web application hosting the RPG Session-Hub web application.

    PHP

  6. GLCM-gen-azure GLCM-gen-azure Public

    An Azure Cloud implementation of a simple GLCM matrix generator that supports 0-360 angle operations with a gap of 1-4.

    JavaScript