Published in IEEE Computer Software and Applications Conference (COMPSAC), 2026
A dual-process cognitive architecture for efficient ML model improvement, published at IEEE COMPSAC 2026.
Recommended citation: Bravo-Rocca, G., et al. (2026). "KC-Agent: A Dual-Process Cognitive Architecture for Efficient ML Model Improvement." IEEE COMPSAC 2026. https://arxiv.org/abs/2608.02351
Published in SN Computer Science (Springer Nature), 2026
Autonomous prompt evolution achieving 99% storage reduction while maintaining 96.9% accuracy in privacy-sensitive healthcare applications.
Recommended citation: Bravo-Rocca, G., et al. (2026). "Adaptive Prompt Evolution for Continual Learning in Diabetic Retinopathy Detection." SN Computer Science. https://link.springer.com/article/10.1007/s42979-026-05036-y
Published in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025
This paper presents an adaptive cognitive architecture for interpretable machine learning monitoring in agent systems.
Recommended citation: Bravo-Rocca, G., et al. (2025). "Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring." International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Detroit, USA. https://dl.acm.org/doi/10.5555/3709347.3743552
Published in International Conference on Computer Vision Theory and Applications (VISAPP), 2025
Novel approach combining experience replay and zero-shot clustering for continual learning in healthcare, shortlisted for Best Student Paper Award.
Recommended citation: Bravo-Rocca, G., et al. (2025). "Experience Replay and Zero-shot Clustering for Continual Learning in Diabetic Retinopathy Detection." VISAPP 2025. Porto, Portugal. https://doi.org/10.5220/0013128600003912
Published in arXiv, 2025
Benchmark of large language models on Peruvian medical exams, including dataset construction and evaluation.
Recommended citation: Bravo-Rocca, G., et al. (2025). "PeruMedQA: Benchmarking Large Language Models (LLMs) on Peruvian Medical Exams - Dataset Construction and Evaluation." arXiv. https://arxiv.org/abs/2509.11517
Published in International Conference on Pattern Recognition (ICPR), 2024
Task-agnostic domain-incremental learning approach using transformer nearest-centroid embeddings for effective domain adaptation without task labels.
Recommended citation: Bravo-Rocca, G., et al. (2024). "TADIL: Task-Agnostic Domain-Incremental Learning through Task-ID Inference using Transformer Nearest-Centroid Embeddings." ICPR 2024. Kolkata, India. https://link.springer.com/chapter/10.1007/978-3-031-78110-0_22
Published in Expert Systems With Applications, 2024
Production-grade MLOps framework for ML workflow management, debugging, and reliability published in top-tier journal.
Recommended citation: Bravo-Rocca, G., et al. (2024). "Scanflow: Multi-graph framework for Machine Learning workflow management, supervision, and debugging." Expert Systems With Applications. Impact Factor: 8.665. https://dl.acm.org/doi/10.1016/j.eswa.2022.117232
Published in IEEE Computer Software and Applications Conference (COMPSAC), 2022
Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation, published at IEEE COMPSAC 2022.
Recommended citation: Bravo-Rocca, G., et al. (2022). "Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation." IEEE COMPSAC 2022. https://doi.org/10.1109/COMPSAC54236.2022.00014
Published in IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2022
Agent-based framework for autonomic management and supervision of ML workflows in Kubernetes clusters, published at IEEE CCGrid 2022.
Recommended citation: Bravo-Rocca, G., et al. (2022). "Scanflow-K8s: Agent-based Framework for Autonomic Management and Supervision of ML Workflows in Kubernetes Clusters." IEEE CCGrid 2022. https://doi.org/10.1109/CCGrid54584.2022.00047