| 2026 | GECCO | A Probabilistic L-System Inspired Designer for Neural Architecture Search: A Graph Neural Network Case Study on Node Classification. | Maciej Krzywda, Szymon Lukasik, Amir Hossein Gandomi |
| 2026 | GECCO | SA-DCGP: Surrogate-Assisted Cartesian Genetic Programming with Dynamic Operator Scheduling for Contrastive Graph Clustering. | Maciej Krzywda, Szymon Lukasik, Amir Hossein Gandomi |
| 2026 | GECCO | Surrogate-Assisted Linear Genetic Programming for Evolving Graph Neural Networks for Node Classification. | Maciej Krzywda, Szymon Lukasik, Amir Hossein Gandomi |
| 2026 | GECCO | Self-Evolving Graph Neural Network Design Inspired by Neural Cellular Automata. | Maciej Krzywda, Mariusz Werminski, Szymon Lukasik, Amir Hossein Gandomi |
| 2026 | ICCS | Graph Neural Networks for Misinformation Detection: Performance-Efficiency Trade-Offs. | Soveatin Kuntur, Maciej Krzywda, Anna Wrblewska, Marcin Paprzycki, Maria Ganzha, Szymon Lukasik, Amir H. Gandomi |
| 2025 | CIKM | Graph Neural Network Architecture Search via Hybrid Genetic Algorithm with Parallel Tempering. | Maciej Krzywda |
| 2025 | FedCSIS | Applying Evolutionary Techniques to Enhance Graph Convolutional Networks for Node Classification: Case Studies. | Maciej Krzywda, Szymon Lukasik, Amir H. Gandomi |
| 2025 | GECCO | Linear Genetic Programming for Design Graph Neural Networks for Node Classification. | Maciej Krzywda, Szymon Lukasik, Amir H. Gandomi |
| 2025 | GECCO | Unveiling the Search Space of Simple Contrastive Graph Clustering with Cartesian Genetic Programming. | Maciej Krzywda, Yue Liu, Szymon Lukasik, Amir H. Gandomi |
| 2022 | IJCNN | Graph Neural Networks in Computer Vision - Architectures, Datasets and Common Approaches. | Maciej Krzywda, Szymon Lukasik, Amir H. Gandomi |
| 2021 | KES | Architecture and organization of a Platform for diagnostics, therapy and post-covid complications using AI and mobile monitoring. | Miroslaw Hajder, Piotr Hajder, Tomasz Gil, Maciej Krzywda, Janusz Kolbusz, Mateusz Liput |