Training program

The Doctoral Meeting (DM) is a CiTIUS initiative aimed at developing and stimulating the communication, argumentation and scientific criticism skills of young CiTIUS researchers, providing them with an opportunity to present the development of the research carried out in their doctoral thesis in an informal atmosphere that favors an open and productive discussion.

`$Training program - $Doctoral Meeting`

/talent/training-program/doctoral-meeting

Distributed quantum computing integrated in heterogeneous systems, Bioinformatics procedures for the advancement of the implementation of clinical metagenomics, LitS: A novel Neighborhood Descriptor for Point Clouds, Enhancing Few-Shot Object Detection through Pseudo-Label Mining, Explainable AI an Bayesian Networks: Development, Explanation, and Real-World Application Insights, Bayesian nonparametric dynamic clustering of time sequences, Doctoral Meeting: In-Memory Computing CMOS Circuits for Computer Vision Deep Learning Models, Alternatives to physical touch when interacting with molecular simulations in VRAlternatives to physical touch when interacting with molecular simulations in VR, Dealing with hallucinations and omissions in neural Natural Language Generation, Improving the performance of alignment-based conformance checking, Smart Modeling for Water Quality Prediction for Resource Management Systems, Explainability in Process Mining: A Framework for Improved Decision-Making, Explaining black-box AI models, A Multistage Retrieval System for Health-related Misinformation Detection, Fabrication of CMOS ToF sensors with 2D/3D capabilities, Analog to Information Converters with CMOS Event Cameras with Spatio-Temporal Processing through Deep Learning Techniques, Testing the private mode of web browsers. Are you sure it is private?, Multiple 0bject visual tracking through deep convolutional networks, Argumentative counterfactual explanation generation for enhancing human-machine interaction, Techniques for the extraction of spatial and spectral information in the supervised classification of hyperspectral imagery for land-cover applications, Five-year prediction of glucose changes with missing data in a Reproducing Kernel Hilbert Space, Deep learning for predictive process monitoring based on change characterization and detection, Doctoral meeting: 'Process-to-Text: A Framework for the Description of Processes in Natural Language', Doctoral meeting: 'Ultra-low power CMOS circuit design for energy harvesting applications', Fuzzy Quantified Protoforms for Data-To-Text Systems: a new model with applications, Efficient registration of hyperspectral images on GPU, RoI Feature Propagation for Video Object Detection, Development of a 'glocal' and continuous machine learning strategy applicable to devices, Understanding complex processes through frequent and infrequent behaviour, Structural change detection on process models, Processing of airborne LiDAR Data: power line detection and search of optimal routes, Efficient query over large datasets of analytical chemistry, Next Generation Edge and Federation Large-scale Data Analytics: the scalability and security concerns, In-Pixel Analog Processing Elements of the HO-PBAS Algorithm for Background Subtraction, Using hardware counter data to model performance and energy usage in NUMA systems , Automatic dental age calculation from significant parameters extracted automatically from orthopantomographies, Line-based Structure-from-Motion, Corpus-based Construction of Polarity Lexicon, Ensemble and choice modelling for recommending items, Efficient object classification from airborne LiDAR, Micro-energy harvesting on CMOS chips, Deep Learning Based Classification Techniques for hyperspectral imagery in real time, Efficient techniques for change detection in multitemporal hyperspectral images, Nanodevice simulations: tools and insights, Motion planning and controller learning in robotics, Approaching Big Data technologies to scientific applications, Automatic Learning of Simple and Accurate Fuzzy Rule Systems for Regression, Semantic Virtual Integration of Observation Data through Sensor Observation Services, Improving Design Smell Detection for Adoption in Industry, Data Mining Algorithms for Discovering Exception and Deviation Patterns in Temporal Databases, Time-of-Flight sensors in standard CMOS technologies, Efficient optimization techniques for automatic composition of Web services, Simultaneous characterization of deterministic and stochastic components in Heart Rate Variability, Spatial Observation Data Acquisition and Declarative AnalyticalProcessing, Efficient Segmentation and Classification of n-dimensional Images in GPU for Real Time Processing , Classifiers for biosignal interpretation? Not beyond toy examples..., Development of tools to improve the efficiency of amorphous silicon solar cells , Automatic Characterization of Thoracic Aortic Aneurysms from CT Images, ProDiGen: mining complete, precise and minimal structure process models with a genetic algorithm, Computing With Perceptions for the linguistic description of complex processes through time series data analysis, Ordinal classification and time series segmentation: Potential applications, Context-based adaptive QRS clustering in real-time, Advanced visualization and interaction applied to virtual scenarios, Graph-based semantic annotation for enriching documents with linked data, Discovering metric temporal constraint networks on temporal databases , Semantic Relation Extraction. Resources, Tools and Strategies, Hardware Counters Based Methods for the Analysis of Shared Memory Parallel Codes, Scale and Rotation Invariant Feature Detectors on CMOS-3D Technologies for Low Power Vision Systems, 3D diagnonis in Orthodontics: Clinical and research applications, Development of simulation tools for devices based on magnetic semiconductors, Development, deployment and validation of an oceanographic virtual laboratory based on Grid computing, Time and space scale adaptive whitening as visual dynamic attentional mechanism, Development of GPU-efficient visualization and segmentation algorithms for 3D medical datas, Fuzzy Syllogistic Reasoning with Generalized Quantifiers, Self-organized multi-camera system for a fast and easy deployment of service robots in unknown environments, Combining retrieval, learning and NLP to estimate polarity in social media