| 2026 | HCI | Towards a Neurosymbolic Cognitive Digital Twin for Aircraft Pilots: An Ontology-Driven ACT-R Architecture for Procedural Behavior Modeling. | Daril Kengne, Vanessa Mankejeu, Roger Nkambou, Ange Tato |
| 2025 | AIED | Can LLMs Generate Accurate Bayesian Networks to Enhance Knowledge Tracing ? | Ange Tato, Roger Nkambou |
| 2025 | ITS | Leveraging LLMs for Bayesian and Deep Knowledge Tracing in the Logic-Muse Intelligent Tutoring System. | Ange Tato, Roger Nkambou |
| 2023 | AAAI | Learning Logical Reasoning Using an Intelligent Tutoring System: A Hybrid Approach to Student Modeling. | Roger Nkambou, Janie Brisson, Ange Tato, Serge Robert |
| 2023 | AIED | Towards Extracting Adaptation Rules from Neural Networks. | Ange Tato, Roger Nkambou |
| 2023 | EDM | Introduction to Neural Networks and Uses in EDM. | Agathe Merceron, Ange Tato |
| 2023 | FlAIRS | Towards a multi-modal Deep Learning Architecture for User Modeling. | Ange Tato, Roger Nkambou |
| 2023 | ITS | Automatic Execution of the Ontological Piloting Procedures. | Marc-Antoine Courtemanche, Ange Tato, Roger Nkambou |
| 2023 | ITS | Automatic Learning of Piloting Behavior from Flight Data. | Ange Tato, Roger Nkambou, Gabrielle Joyce Nana Tato |
| 2022 | ITS | Ontological Reference Model for Piloting Procedures. | Marc-Antoine Courtemanche, Ange Tato, Roger Nkambou |
| 2022 | ITS | Deep Knowledge Tracing on Skills with Small Datasets. | Ange Tato, Roger Nkambou |
| 2022 | ITS | Towards Adaptive Coaching in Piloting Tasks: Learning Pilots' Behavioral Profiles from Flight Data. | Ange Tato, Roger Nkambou, Gabrielle Joyce Nana Tato |
| 2021 | ITS | Learning Logical Reasoning : Improving the Student Model with a Data Driven Approach. | Roger Nkambou, Janie Brisson, Serge Robert, Ange Tato |
| 2020 | AAAI | Improving First-Order Optimization Algorithms (Student Abstract). | Ange Tato, Roger Nkambou |
| 2020 | AAAI | Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development. | Ange Tato, Roger Nkambou, Aude Dufresne |
| 2019 | FlAIRS | Using EEG Features and Machine Learning to Predict Gifted Children. | Ramla Ghali, Ange Tato, Roger Nkambou |
| 2019 | ICTAI | Some Improvements of Deep Knowledge Tracing. | Ange Tato, Roger Nkambou |
| 2019 | ITS | Towards Predicting Attention and Workload During Math Problem Solving. | Ange Tato, Roger Nkambou, Ramla Ghali |
| 2018 | IJCNN | Semi-Supervised Multimodal Deep Learning Model for Polarity Detection in Arguments. | Ange Tato, Roger Nkambou, Aude Dufresne, Claude Frasson |
| 2017 | AIED | Predicting Learner's Deductive Reasoning Skills Using a Bayesian Network. | Ange Tato, Roger Nkambou, Janie Brisson, Serge Robert |