CV

Paper accepted at MACH journal 2024: "Glacier: Guided Locally Constrained Counterfactual Explanations for Time Series Classification"

Paper accepted at MACH journal 2024: "iJUICE: integer JUstIfied Counterfactual Explanations"

Paper accepted at DAMI journal (ECML/PKDD journal track 2023): "Z-Time: efficient and effective interpretable multivariate time series classification"

Paper accepted at ICDM 2023: "Counterfactual Explanations for Time Series Forecasting"

Paper accepted at IDA 2023: "Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies"

Paper accepted at Discovery Science 2022: "JUICE: JUstIfied Counterfactual Explanations"

Paper accepted at ECML/PKDD 2022: "Finding local groupings of time series"

Paper accepted at ECML/PKDD 2022-DEMO track: "Demonstrator on Counterfactual Explanations for Differentially Private Support Vector Machines"

Paper accepted at CBMS 2022 for: "FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality Prediction"

Paper accepted at AIME 2022 for: "EpidRLearn: Learning intervention strategies for epidemics with Reinforcement Learning"

Best paper award at AIME 2021 for: "Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients"

Paper accepted at the DAMI journal: "SMILE: A feature-based temporal abstraction framework for event-interval sequence classification"

Paper accepted at the journal of Artificial Intelligence in Medicine: "Exploiting Complex Medical Data with Interpretable Deep Learning for Adverse Drug Event Prediction"

Paper accepted at KDD 2020: "Z-Miner: an efficient method for mining frequent arrangements of event intervals"

Paper accepted at ECML/PKDD 2020: "Z-Embedding: a spectral representation of event intervals for efficient clustering and classification"

Paper accepted at ECML/PKDD 2020: "Prediction of Global Navigation Satellite System Positioning Errors with Guarantees"

Paper accepted at CBMS 2020: "A Clustering Framework for Patient Phenotyping with Application to Adverse Drug Events"

Paper accepted at CBMS 2020: "Clinical Predictive Keyboard using Statistical and Neural Language Modeling"

Paper accepted at CBMS 2020: "Mining disproportional frequent arrangements of event intervals for investigating adverse drug events"

Paper accepted at CBMS 2020: "Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models"

Paper accepted at KAIS: "Locally and globally explainable time series tweaking"