2026

VisDocSketcher: Towards Scalable Visual Documentation with Agentic Systems

Luís F. Gomes, Xin Zhou, David Lo, Rui Abreu

Submitted to International Conference on Software Engineering (ICSE) 2026 Under Review

An agentic LLM system that generates high-level visual documentation from source code, paired with AutoSketchEval — a reference-free evaluation framework (inspired by autoencoder reconstruction) that scores diagram quality with no ground truth, reaching AUC > 0.87 across 1,000 Jupyter notebooks.

VisDocSketcher: Towards Scalable Visual Documentation with Agentic Systems

Luís F. Gomes, Xin Zhou, David Lo, Rui Abreu

Submitted to International Conference on Software Engineering (ICSE) 2026 Under Review

An agentic LLM system that generates high-level visual documentation from source code, paired with AutoSketchEval — a reference-free evaluation framework (inspired by autoencoder reconstruction) that scores diagram quality with no ground truth, reaching AUC > 0.87 across 1,000 Jupyter notebooks.

An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks

Xin Zhou, Kisub Kim, Ting Zhang, Martin Weyssow, Luís F. Gomes, Guang Yang, David Lo

International Conference on Automated Software Engineering (ASE) 2026

A study of LLM-as-judge metrics for software engineering tasks, calibrated to bridge the gap with human evaluation across a range of SE benchmarks.

An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks

Xin Zhou, Kisub Kim, Ting Zhang, Martin Weyssow, Luís F. Gomes, Guang Yang, David Lo

International Conference on Automated Software Engineering (ASE) 2026

A study of LLM-as-judge metrics for software engineering tasks, calibrated to bridge the gap with human evaluation across a range of SE benchmarks.

2025

An Exploratory Study of ML Sketches and Visual Code Assistants

Luís F. Gomes, Jonathan Aldrich, Rui Abreu, Vincent Hellendoorn

International Conference on Software Engineering (ICSE) 2025

A VSCode assistant that turns hand-drawn ML workflow sketches into runnable Jupyter notebooks (79% structural accuracy, 49% reduction in coding), with a 19-participant developer study and an automated LLM-as-judge pipeline benchmarking sketch-to-code across GPT-4o, Gemini Pro, and Claude.

An Exploratory Study of ML Sketches and Visual Code Assistants

Luís F. Gomes, Jonathan Aldrich, Rui Abreu, Vincent Hellendoorn

International Conference on Software Engineering (ICSE) 2025

A VSCode assistant that turns hand-drawn ML workflow sketches into runnable Jupyter notebooks (79% structural accuracy, 49% reduction in coding), with a 19-participant developer study and an automated LLM-as-judge pipeline benchmarking sketch-to-code across GPT-4o, Gemini Pro, and Claude.

2023

Transforming Ideas into Code: Visual Sketching for ML Development

Luís F. Gomes

SPLASH — Doctoral Symposium 2023

Doctoral symposium paper outlining a research agenda for visual sketching as an interface for machine learning development.

Transforming Ideas into Code: Visual Sketching for ML Development

Luís F. Gomes

SPLASH — Doctoral Symposium 2023

Doctoral symposium paper outlining a research agenda for visual sketching as an interface for machine learning development.

2021

Distress Detection in Road Pavements Using Neural Networks

Luís F. Gomes, César Analide, Elisabete Freitas

International Conference on Distributed Computing and Artificial Intelligence (DCAI) 2021

Neural network models for detecting distress and defects in road pavement imagery.

Distress Detection in Road Pavements Using Neural Networks

Luís F. Gomes, César Analide, Elisabete Freitas

International Conference on Distributed Computing and Artificial Intelligence (DCAI) 2021

Neural network models for detecting distress and defects in road pavement imagery.