prof. dr. ir. Sofie Van Hoecke
- ORCID iD
- 0000-0002-7865-6793
- Bio (via ORCID)
- I graduated from the Engineering Department from the Ghent University in 2003. Following up on my studies in computer science, I achieved a PhD in computer science engineering at the Department of Information Technology at the same university. After being a postdoctoral research engineer at the Department of Information Technology, I started as lecturer ICT and ICT research coordinator at the University College West-Flanders. Since 2013, I joined Ghent University again. Currently, I am associate professor at IDLab, Ghent University-imec and my research focuses on machine learning and hybrid machine learning for predictive maintenance and predictive healthcare.
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- Journal Article
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Acoustic and prosodic speech features reflect physiological stress but not isolated negative affect : a multi-paradigm study on psychosocial stressors
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A novel day-ahead regional and probabilistic wind power forecasting framework using deep CNNs and conformalized regression forests
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Patients with chronic cluster headache may show reduced activity energy expenditure on ambulatory wrist actigraphy recordings during daytime attacks
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Benchmarking whole knowledge graph embedding techniques
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Transfer learning for anomaly detection using bearings' vibration signals
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MinMaxLTTB : leveraging MinMax-preselection to scale LTTB
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Edge anomaly detection framework for AIOps in Cloud and IoT
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Ecologically valid speech collection in behavioral research : the Ghent Semi-spontaneous Speech Paradigm (GSSP)
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Tryp : a dataset of microscopy images of unstained thick blood smears for trypanosome detection
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LDESTS : enabling efficient storage and querying of large volumes of time series data on solid pods
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Comparator model for detecting changes in the ease of breathing of COPD patients
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Tree visualization of patient information for explainability of AI outputs
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Parameter efficient neural networks with singular value decomposed kernels
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Context-aware deep learning with dynamically assembled weight matrices
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Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by design
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From lab to real world : assessing the effectiveness of human activity recognition and optimization through personalization
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Leak localization in water distribution networks using GIS-Enhanced autoencoders
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Generalizable calibrated machine learning models for real-time atrial fibrillation risk prediction in ICU patients
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Pathogen-based target attainment of optimized continuous infusion dosing regimens of piperacillin-tazobactam and meropenem in surgical ICU patients : a prospective single center observational study
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Data analytics for health and connected care : ontology, knowledge graph and applications
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A microservice architecture for leak localization in water distribution networks using hybrid AI
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TALK : tracking activities by linking knowledge
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Real-time estimation and monitoring of COVID-19 aerosol transmission risk in office buildings
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Design of a social chatbot with gamification for user profiling and smoking trigger detection
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Do not sleep on traditional machine learning simple and interpretable techniques are competitive to deep learning for sleep scoring
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Probabilistic leak localization in water distribution networks using a hybrid data-driven and model-based approach
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Powershap : a power-full shapley feature selection method
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Towards knowledge-driven symptom monitoring & trigger detection of primary headache disorders
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Leak localization in water distribution networks by directly fitting the learning parameters of a Gaussian naive Bayes classifier
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The development of an artificial intelligence-based digital pathology for neglected tropical diseases : a platform specific analysis of the World Health Organization diagnostic target product profile for soil-transmitted helminthiasis
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NAOMI platform optimizes communication with relatives of patients
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From self-reporting to monitoring for improved migraine management
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Predicting patient-reported symptom clusters in prostate cancer patients : a machine learning approach
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Plotly-resampler : effective visual analytics for large time series
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Acoustic speech features in social comparison : how stress impacts the way you sound
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Hybrid machine learning for leak localization in the drinking water grid
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Context-aware visualization recommendations reduce decision overload for operators
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A semi-supervised anomaly detection approach detecting mechanical failures
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PowerShap : a power-full Shapley feature selection method
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Assessing the added value of context during stress detection from wearable data
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Hierarchical pattern matching for anomaly detection in time series
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Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients
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Affordable artificial intelligence-based digital pathology for neglected tropical diseases : a proof-of-concept for the detection of soil-transmitted helminths and Schistosoma mansoni eggs in Kato-Katz stool thick smears
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mBrain : towards the continuous follow-up and headache classification of primary headache disorder patients
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Artificial intelligence in infection management in the ICU
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tsflex : flexible time series processing & feature extraction
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An incremental grey-box current regression model for anomaly detection of resistance mash seam welding in steel mills
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A semi-supervised approach with monotonic constraints for improved remaining useful life estimation
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Prediction of follower jumps in cam-follower mechanisms : the benefit of using physics-inspired features in recurrent neural networks
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Physics-based neural network models for prediction of cam-follower dynamics beyond nominal operations
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Neural network augmented physics models for systems with partially unknown dynamics : application to slider-crank mechanism
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A complete software stack for IoT time-series analysis that combines semantics and machine learning-lessons learned from the dyversify project
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Event-driven dashboarding and feedback for improved event detection in predictive maintenance applications
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Bayesian convolutional neural networks for remaining useful life prognostics of solenoid valves with uncertainty estimations
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Overly optimistic prediction results on imbalanced data : a case study of flaws and benefits when applying over-sampling
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FLAGS : a methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning
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Anomaly detection and event mining in cold forming manufacturing processes
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Mining recurring patterns in real-valued time series using the radius profile
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Unsupervised anomaly detection for communication networks : an autoencoder approach
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Clinical information extraction for preterm birth risk prediction
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Scalable fleet monitoring and visualization for smart machine maintenance and industrial IoT applications
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Data-driven prognostics of alternating current solenoid valves
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A generalized matrix profile framework with support for contextual series analysis
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A dynamic dashboarding application for fleet monitoring using semantic web of things technologies
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Implications of Z-normalization in the matrix profile
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Smart machine maintenance enabled by a condition monitoring living lab
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Hybrid derivative functions for identification of unknown loads and physical parameters with application on slider-crank mechanism
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Interpretable detection of unstable smart TV usage from power state logs
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Towards diagnosis of rotator cuff tears in 3-D MRI using 3-D convolutional neural networks
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A critical look at studies applying over-sampling on the TPEHGDB dataset
(2019) ARTIFICIAL INTELLIGENCE IN MEDICINE, AIME 2019. In Lecture Notes in Artificial Intelligence 11526. p.355-364 -
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Time-to-birth prediction models and the influence of expert opinions
(2019) ARTIFICIAL INTELLIGENCE IN MEDICINE, AIME 2019. In Lecture Notes in Computer Science 11526. p.286-291 -
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Medinoid : computer-aided diagnosis and localization of glaucoma using deep learning
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A convolutional neural network aided physical model improvement for AC solenoid valves diagnosis
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Eliminating noise in the matrix profile
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Thermal imaging and vibration-based multisensor fault detection for rotating machinery
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Data-driven optimization of energy efficiency and comfort in an apartment
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Computer-aided diagnosis and localization of glaucoma using deep learning
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Web applicable computer-aided diagnosis of glaucoma using deep learning
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Large-scale wearable data reveal digital phenotypes for daily-life stress detection
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Towards adaptive anomaly detection and root cause analysis by automated extraction of knowledge from risk analyses
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A decision support system to follow up and diagnose primary headache patients using semantically enriched data
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Automated assessment of bone age using deep learning and Gaussian process regression
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Automated extraction of rules and knowledge from risk analyses : a ventilation unit demo
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Serious game development and dynamic tailoring through model-driven authoring
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Context-aware stress detection
(2018) p.1-1 -
- Journal Article
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Psychometric data of a questionnaire to measure cyberbullying bystander behavior and its behavioral determinants among adolescents
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Deep learning for infrared thermal image based machine health monitoring
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Extended FTLD pedigree segregating a Belgian GRN-null mutation : neuropathological heterogeneity in one family
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The efficacy of the friendly attac serious digital game to promote prosocial bystander behavior in cyberbullying among young adolescents : a cluster-randomized controlled trial
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A genetic algorithm for interpretable model extraction from decision tree ensembles
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Data-driven imbalance and hard particle detection in rotating machinery using infrared thermal imaging
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The efficacy of the Friendly Attac serious digital game to promote prosocial bystander behavior in cyberbullying among young adolescents : a cluster-randomized controlled trial
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Extensible multi-domain generation of Virtual Worlds using blackboards
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The pragmatic proof : hypermedia API composition and execution
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The Friendly ATTAC game: an intervention aimed at the promotion of positive bystander behavior in cyberbullying among adolescents: examining the role of player experience and player behavior
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The efficacy of a serious game aimed at the promotion of positive bystander behavior in cyberbullying among adolescents: examining the role of player experience and player behavior
(2016) -
The Friendly ATTAC game: an intervention aimed at adolescent bystander behavior in cyberbullying
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GENESIM : genetic extraction of a single, interpretable model
(2016) p.1-6 -
The efficacy of a serious game aimed at the promotion of positive bystander behavior in cyberbullying among adolescents: examining the role of player experience and player behavior
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Data-driven multivariate power curve modeling of offshore wind turbines