.- RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education.
.- PICA: A Data-driven Synthesis of Peer Instruction and Continuous Assessment.
.- The ChatGPT and Education Tweets Dataset.
.- A Fair Post-Processing Method based on the MADD Metric for Predictive Student Models.
.- Distractor generation for multiple-choice questions with predictive prompting and large language models.
.- Towards Personalized Educational Materials: Mapping Student Knowledge through Natural Language Processing.
.- A 2-step methodology for XAI in education.
.- Consolidation and Transmission of Multiple xAPI Data Sources from Virtual Learning Environments to Different Learning Record Stores .
.- SoGood 2023 - 8th Workshop on Data Science for Social Good.
.- Efficient and general text classification: An Active Learning approach.
.- Identifying Features of Constructive Journalism in News Articles: An Explainable ML Approach.
.- Anomaly Detection in Pet Behavioral Data.
.- Detecting sexually explicit content in the context of the child sexual abuse materials (CSAM): end-to-end classifiers and region-based networks.
.- PrivateCTGAN: Adapting GAN for Privacy-aware Tabular Data Sharing.
.- Data Science for Fighting Environmental Crime.
.- Fairness Analysis in Causal Models: An Application to Public Procurement.
.- Exploring the Generalizability of Transfer Learning for Camera Trap Animal Image Classification.
.- Towards Hybrid Human-Machine Learning and Decision Making (HLDM).
.- Towards a hybrid human-machine discovery of complex movement patterns.
.- Trustworthy Hybrid Decision Making.
.- Optimizing delegation between human and AI collaborative agents.
.- Exploring the Risks of General-Purpose AI: The Role of Nearsighted Goals and the Brain's Reward Mechanism in Processes of Decision Makings.
.- Towards synergistic human-AI collaboration in hybrid decision-making systems.
.- On the Challenges and Practices of Reinforcement Learning from Real Human Feedback.
.- Conversational XAI: Formalizing its Basic Design Principles.
.- TCuPGAN: A novel framework developed for optimizing human-machine interactions in citizen science.
.- A Crossroads for Hybrid Human-Machine decision-making.
.- Enhancing Fairness, Justice and Accuracy of Hybrid Human AI Decisions by Shifting Epistemological Stances.
.- Interpreting Dynamic Causal Model Policies.
.- Uncertainty meets explainability in machine learning.
.- Relation of Activity and Confidence when Training Deep Neural Networks.
.- Explaining an image classifier with a GAN conditioned by uncertainty.
.- Identifying Trends in Feature Attributions during Training of Neural Networks.
.- Using Stochastic Methods to Setup High Precision Experiments.
.- Designing a Method to Identify Explainability Requirements in Cancer Research.
.- Explainable Learning with Hierarchical Online Deterministic Annealing.
.- Explaining uncertainty in AI for clinical decision support systems.
.- Towards Explainability in Monocular Depth Estimation.
.- Using Part-based Representations for Explainable Deep Reinforcement Learning.
.- Regionally Additive Models: Explainable-by-design models minimizing feature interactions.
.- FALE: Fairness aware ALE plots for auditing bias in subgroups.
.- Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation.
.- Tracing Videos to their Social Network with Robust DCT Analysis.
.- All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection.
.- Improving Tiled Evolutionary Adversarial Attack.
.- Adversarial Magnification to Deceive Deepfake Detection through Super Resolution.
.- DivNoise: A Data Collection for Source Identification on Diverse Camera Sensors.
.- Detecting Face Synthesis Using a Concealed Fusion Model.
.- Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It.
.- Towards a Fine-Grained Threat Model for Video-Based Remote Identity Proofing.
