Symbolic Data Analysis Workshop 2026 - Registration open!
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Registration is open for Symbolic Data Analysis Workshop 2026, Lisbon, Portugal - visit the official website
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Registration is open for Symbolic Data Analysis Workshop 2026, Lisbon, Portugal - visit the official website
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Pedro Estróia has successfully defended the MSc thesis titled “Gesture classification for assembly tasks with event cameras”.
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Paper Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low-Earth Orbit has been published in IEEE Transactions on Aerospace and Electronic Systems.
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Paper Ranking with Confidence for Large Scale Comparison Data has been accepted at 2025 SIAM International Conference on Data Mining (SDM25). This work proposes a new rank aggregation method for noisy pairwise comparisons.
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Paper Maximum likelihood localization of a network of moving agents from ranges, bearings and velocity measurements was published in Signal Processing. This is my latest work on Optimization methods for network localization.
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Paper Probabilistic registration for Gaussian Process 3D shape modelling in the presence of extensive missing data was published in the SIAM Journal on Mathematics of Data Science.
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Paper A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel was published in the Journal of Mathematics in Industry. It was motivated by our participation in the ECMI 2021 Student Competition.
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I have finally defended my thesis Gaussian Processes for 3D Shape Modelling of Noisy and Incomplete Data. An Application to Human Ears Reconstruction!
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With Stevo Racković (University of Lisbon) and Greta Malaspina (University of Novi Sad), we won the first place in the ECMI 2021 Student Competition.
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Paper From noisy point clouds to complete ear shapes: Unsupervised pipeline was published in IEEE Access.
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With two colleagues from the BIGMATH program, Stevo Racković (University of Lisbon) and Rongjiao Ji (University of Milan), we won third place in the e-Poster competition for the graduate students, with the title ‘Meet my Avatar’. This work merges ideas from our three research fields: inverse rig estimation, face reconstruction, and emotion recognition.