Education
Education Courses 2024/2025 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2023/2024 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2022/2023 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2021/2022 Applied Machine Learning | CS4305TU Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2020/2021 Applied Machine Learning | CS4305TU Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 2019/2020 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 Master projects Ongoing Adaptive Learning on graphs, Elvin Isufi, Alex Jeleniewski (2023/2024) Graph Learning for Multi-Sensor Radar, Elvin Isufi, Radu Gaghi (2023/2024) Graph Neural Networks for Renewable Energy, Elvin Isufi, Rodrigo Revilla Llaca (2023/2024) Hybrid Modelling in Hydrology Using a Neural Ordinary Differential Equations Approach, Riccardo Taormina, Jonathan Schieren (2023/2024) Graph Neural Networks for Predicting Dike-breach floods, Riccardo Taormina, Sergio Bulte (2023/2024) Small Deep Learning Models for Sewer Defect Detection, Riccardo Taormina, Brendan Determan (2023/2024) Improving PIV-based streamflow estimation with Deep Learning, Riccardo Taormina, Max Helmich (2023/2024) GAN-based rainfall nowcasting, Riccardo Taormina, Sven van Os (2023/2024) Optimizing the pump schedule of water distribution systems using a deep learning metamodel, Riccardo Taormina, Nikolaos Mertzanis (2022/2023) Finished GGANet: Algorithm Unrolling for Water Distribution Networks Metamodelling , Riccardo Taormina, Albert Roca Solà (2023/2024) Sparse & Interpretable Graph Attention Networks , Elvin Isufi, Titus Naber (2023/2024) An Experimental Assessment of the Stability of Graph Contrastive Learning , Elvin Isufi, Siert Sebus (2023/2024) Bayesian Contrastive Learning on Topological Structures , Elvin Isufi, Alex Mollers (2023/2024) Assessment of Pump Failures in Rotterdam: A Five-Year Study (2016-2020): A Failure Analysis based on statistical modelling , Riccardo Taormina, Qiwen Zhang (2023/2024) Diverse Explorations of Rainfall Nowcasting with TrajGRU: Mitigating Smoothness and Fading Out Challenges for Longer Lead Times , Riccardo Taormina, Yanghuan Zou (2023/2024) Towards a fully distributed multivariable hydrological deep learning model with graph neural networks , Riccardo Taormina, Peter Nelemans (2023/2024) Characterization of plastic transport in the Saigon River: An analysis of the river stretch that crosses Ho Chi Minh City conducted in the rainy season. , Riccardo Taormina, Francesca Lena (2023/2024) Characterization of plastic transport in the Saigon River: An analysis of the river stretch that crosses Ho Chi Minh City conducted in the rainy season. , Riccardo Taormina, Edoarto Forte (2023/2024) Characterization of plastic transport in the Saigon River: An analysis of the river stretch that crosses Ho Chi Minh City conducted in the rainy season. , Riccardo Taormina, Agatha Zamuner (2023/2024) Prediction of Discharges from Polders to ‘Boezem’ Canals with a Random Forest and an LSTM Model: Improving Inputs of the Decision Support System of the Hoogheemraadschap van Delfland , Riccardo Taormina, Josine van Marrewijk (2023/2024) The Hierarchical Subspace Iteration Method for Computing Vibration Modes of Elastic Objects , Elvin Isufi, Julian van Dijk (2023/2024) A System for Model Diagnosis centered around Human Computation , Elvin Isufi, Ziad Ahmad Saad Soliman Nawar (2023/2024) Automatic feature discovery: A comparative study between filter and wrapper feature selection techniques , Elvin Isufi, Andrei Mân?stireanu (2023/2024) Encoding methods for categorical data: A comparative analysis for linear models, decision trees, and support vector machines , Elvin Isufi, Andrei Udil? (2023/2024) Filtering Knowledge: A Comparative Analysis of Information-Theoretical-Based Feature Selection Methods , Elvin Isufi, Kiril Vasilev (2023/2024) Data-Driven Empirical Analysis of Correlation-Based Feature Selection Techniques , Elvin Isufi, Florena Bu?e (2023/2024) Perceptual losses in precipitation nowcasting , Riccardo Taormina, Diewertje Dekker (2022/2023) Development of an LSTM-based methodology for burst detection in water distribution systems , Riccardo Taormina, Konstantinos Glynis (2022/2023) The role of water vapor observations in satellite-based rainfall information highlighted by a Deep Learning approach , Riccardo Taormina, Fabo Curzi (2022/2023) Predicting fluvial flood arrival times by making use of a deep learning model , Riccardo Taormina, Ron Bruijns (2022/2023) Using YOLOv5 for the Detection of Icebergs in SAR Imagery , Riccardo Taormina, Daan Hulskemper (2022/2023) Assessing the applicability of Transformer-based architectures as rainfall-runoff models , Riccardo Taormina, Kangmin Mao (2022/2023) Simplicial Unrolling Elastic Net for Edge Flow Signal Reconstruction , Elvin Isufi, Chengen Liu (2022/2023) From Clicks to Conscious Choices: Investigating the Effects of Carbon Footprint Data in E-Commerce Recommender Systems , Elvin Isufi, Sneha Lodha (2022/2023) Graph Reqularized Tensor Decomposition for Recommender Systems , Elvin Isufi, Rohan Chandrashekar (2022/2023) Pure Cold Start Recommendation by Learning on Stochastically Expanded Graphs , Elvin Isufi, Simon Dahrs (2022/2023) Nudging Towards Sustainable Choices via Recommender Systems , Elvin Isufi, Raoul Kalisvaart (2022/2023) Deep Learning for Geotechnical Engineering: The Effectiveness of Generative Adversarial Networks in Subsoil Schematization , Riccardo Taormina, Fabian Campos Montero (2022/2023) Quantum to Transport: Modeling Transport Properties of Aqueous Potassium Hydroxide by Machine Learning Molecular Force Fields from Quantum Mechanics , Riccardo Taormina, Jelle Lagerweij (2022/2023) A LSTM-based Generative Adversarial Network for End-use Water Modelling , Riccardo Taormina, Yukun Xie (2022/2023) Operational Streamflow Drought Forecasting for the Rhine River at Lobith Using the LSTM Deep Learning Approach , Riccardo Taormina, Jing Deng (2022/2023) cGANs for multispectral snow extent analysis in the Alps , Riccardo Taormina, Adriaan Keurhorst (2022/2023) The Effect of Climate Variability on the Root Zone Storage Capacity , Riccardo Taormina, Nienke Tempel (2022/2023) GNNs and Beam Dynamics: Investigation into the application of Graph Neural Networks to predict the dynamic behaviour of lattice beams , Riccardo Taormina, Lex Niessen (2022/2023) The impact of an additional phenology model on the performance of conceptual hydrological models , Riccardo Taormina, Casper Pierik (2022/2023) Leak Localization in Water Distribution Networks , Riccardo Taormina, Zixi Meng (2022/2023) Macrolitter in Groyne Fields: Short term variability & the influence of natural processes , Riccardo Taormina, Jakob Grosfeld (2022/2023) Water balance-based approach to improve understanding of Drought Development: by calculating the root storage deficit , Riccardo Taormina, Piet Storm (2022/2023) APDUDS, Riccardo Taormina, Max Lange (2022/2023) Improving APDUDS, Riccardo Taormina, Jip Steiger (2022/2023) Self-Supervised Few Shot Learning: Prototypical Contrastive Learning with Graphs , Elvin Isufi, Ojas Shirekar (2022/2023) Hardware-based implementations in Side-Channel Analysis: A comparison study of DL SCA attacks against HW and SW AES and a novel methodology , Elvin Isufi, Wolf Bubberman (2022/2023) Assessing Global Applicability of a Long Short-Term Memory (LSTM) Neural Network for Rainfall-Runoff Modelling , Riccardo Taormina, Katharina Wilbrand (2021/2022) Short-term Water Demand Forecasting at a District Level Using Deep Learning Techniques , Riccardo Taormina, Diego Mauricio Corredor Mora (2021/2022) Applying deep learning vs machine learning models to reproduce dry spells at point scale from satellite information in a data-scarce region: the case of northern Ghana , Riccardo Taormina, Panagiotis Mavritsakis (2021/2022) Exploration of Deep Learning-based Computer Vision for the detection of floating plastic debris in waterways , Riccardo Taormina, Andé J. Vallendar (2021/2022) Nowcasting heavy precipitation in the Netherlands: a deep learning approach , Riccardo Taormina, Eva van der Kooij (2021/2022) Deep Statistical Solver for Distribution System State Estimation , Elvin Isufi, Benjamin Habib (2021/2022) Do multi-year droughts increase floods? , Riccardo Taormina, Yang Zhao (2021/2022) Automatic Generation of Water Distribution Systems, Riccardo Taormina, Dimitri Tijdeman (2021/2022) Short-term Earthquake Prediction with Deep Neural Networks: Finding the optimal time prior to earthquake strikes to use in predictions , Elvin Isufi, Glenn van den Belt (2021/2022) Improving cell type matching across species in scRNA-seq data using protein embeddings and transfer learning , Elvin Isufi, Kirti Biharie (2021/2022) Tikhonov and Sobolev regularisers compared to user-based KNN collaborative filtering , Elvin Isufi, Sérénic Monté (2021/2022) Total Variation Regularisation for Item KNN Collaborative Filtering: Performance Analysis , Elvin Isufi, Lars van Blokland (2021/2022) The Performance of Total Variation Regularizer for User Collaborative Filtering , Elvin Isufi, Karolis Mari?nas (2021/2022) Item-Item Collaborative Filtering via Graph Regularization , Elvin Isufi, Melle Jansen (2021/2022) Impact of seismic wave length to detect high-magnitude earthquakes via deep learning , Elvin Isufi, Gancho Georgiev (2021/2022) How long before strike can we predict earthquakes with an LSTM neural network? , Elvin Isufi, Amaury Charlot (2021/2022) Impact of Focal Depth on Short-Term Earthquake Prediction using Deep Learning , Elvin Isufi, Pijus Krisiuk?nas (2021/2022) Predicting Micro-Earthquakes with Deep Neural Networks , Elvin Isufi, Kevin Zhu (2021/2022) Short-term Earthquake Prediction via Recurrent Neural Network Models: Comparison among vanilla RNN, LSTM and Bi-LSTM , Elvin Isufi, Xiangyu Du (2021/2022) Earthquake Prediction: A MLP & SVM Comparison , Elvin Isufi, Daniel van den Akker (2021/2022) Comparing multichannel mixed CNN-RNN to individual models for earthquake prediction , Elvin Isufi, Maikel Houbaer (2021/2022) How does a CNN mixed with LSTM methods compare with the individual one in predicting earthquakes? , Elvin Isufi, Irtaza Hashmi (2021/2022) Parametric design of a grid shell roof over existing buildings?, with a focus on connection design , Elvin Isufi, Fiori Isufi (2021/2022) Investigation of focal epilepsy using graph signal processing , Elvin Isufi, Gaia Zin (2021/2022) Assessing the Capability of Multimodal Variational Auto-Encoders in Combining Information From Biological Layers in Cancer Cells , Elvin Isufi, Bram Pronk (2021/2022) Benchmarking VAE latent features in downstream tasks for cancer related predictions , Elvin Isufi, Boris van Groeningen (2021/2022) The Effect of Different Initialization Methods on VAEs for Modeling Cancer using RNA Genome Expressions , Elvin Isufi, Ivo Kroskinski (2021/2022) Benchmarking the hyper-parameter sensitivity of VAE models for cancer treatment , Elvin Isufi, Armin Korki? (2021/2022) Finding disentangled representations using VAE , Elvin Isufi, Raymond d'Anjou (2021/2022) Creation of new Extra-Tropical Cyclone fields in the North Atlantic with Generative Adversarial Networks , Riccardo Taormina, Filippo Dainelli (2020/2021) Side-channel analysis with graph neural networks , Elvin Isufi, Vasco de Bruijn (2020/2021) Matching streamflow river gauges with hydrologic models , Riccardo Taormina, Mizzi van der Ven (2020/2021) Integrated Neural Network and Finite Element Analysis for constitutive modelling of soil , Riccardo Taormina, Keshav Kashichenula (2020/2021) 3D Road Boundary Mapping of MLS Point Clouds , Riccardo Taormina, Qian Bai (2020/2021) Shallow Cumulus Clouds as Complex Networks , Riccardo Taormina, Pouriya Alinaghi (2020/2021) The variability of the rootzone storage capacity in Austria: An exploration of its controls , Riccardo Taormina, Bart Veenings (2020/2021) Relating groundwater heads to stream discharge by using machine learning techniques: A case study in subcatchment Chaamse Beken , Riccardo Taormina, Valerie Demetriades (2020/2021) Mathematical framework to understand better the behavior of the graphs convolutional neural network to random perturbations, Alejandro Ribeiro, Gao Zhan (2020/2021) Combining frequency information and the unsupervisedW-Net model for wheat head detection , Elvin Isufi, Ivo Chen (2020/2021) Improving the Performance of Object Counting Using Training Images in the Frequency Domain , Elvin Isufi, Dani Rogmans (2020/2021) Using frequency information to improve accuracy of object detectors , Elvin Isufi, Petar Ulev (2020/2021) Injecting prior frequency information in DETR for wheat head detection , Elvin Isufi, Alin Prundeanu (2020/2021) Accelerating Axial-Symmetrical Nebulae Visualization and Reconstruction , Elvin Isufi, Nouri Khalass (2020/2021) Accuracy-Diversity Trade-off in Recommender Systems Via Graph Convolutions , Elvin Isufi, Matteo Pocchiari (2019/2020) Identifying Author Fingerprints in Texts via Graph Neural Networks , Elvin Isufi, Tomas Sipko (2019/2020) Graph-Adaptive Activation Functions for Graph Neural Networks , Elvin Isufi, Bianca Iancu (2019/2020) Accuracy-Diversity Trade-off in Recommender Systems Via Graph Convolutions , Elvin Isufi, M. Pocchaiari (2019/2020) Automatic Depth Matching for Petrophysical Borehole Logs , Elvin Isufi, A. Garcia Manso (2019/2020) Visually grounded fine-grained speech representations learning , Elvin Isufi, Tian Tian (2019/2020) Advances in Graph Signal Processing: Fast graph construction & Node-adaptive graph signal reconstruction , Elvin Isufi, Maosheng Yang (2019/2020) Graph-Time Convolutional Neural Network: Learning from Time-Varying Signals defined on Graphs , Elvin Isufi, Gabriele Mazzola (2019/2020) Applying Machine Learning to Learn System Dynamics Models for Urban Systems , Elvin Isufi, Rukai Yin (2019/2020) Designing an escape room sensory system: S.C.I.L.E.R.: sensory communication inside live escape rooms , Elvin Isufi, Issa Hanou (2019/2020) Designing an escape room sensory system: S.C.I.L.E.R.: sensory communication inside live escape rooms , Elvin Isufi, Gwennan Smitskamp (2019/2020) Designing an escape room sensory system: S.C.I.L.E.R.: sensory communication inside live escape rooms , Elvin Isufi, Marijn de Schipper (2019/2020) Active Semi-Supervised Learning For Diffusions on Graphs , Elvin Isufi, Biswadeep Das (2019/2020) Interpreting Information of Deep Neural Networks for Profiled Side Channel Analysis , Elvin Isufi, Marius Pop (2019/2020) Blind Graph Topology Change Detection: A Graph Signal Processing approach , Elvin Isufi, Ashvant Mahabir (2019/2020) Can fourier neural operators replicate the intrinsic predictability of spatiotemporal chaos?: for the Kuramoto-Sivashinsky system , Riccardo Taormina, Kevin Schuurman () Estimating new reservoir locations with the use of a hydrological model for small holder cotton farmers in Maharashtra, India , Riccardo Taormina, Jente Janssen ()
