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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Ranking with Confidence for Large Scale Comparison Data has been accepted at 2025 SDM25!
Published:
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.
Maximum likelihood localization of a network of moving agents from ranges, bearings and velocity measurements has been published!
Published:
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.
Probabilistic registration for Gaussian Process 3D shape modelling in the presence of extensive missing data has been published!
Published:
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.
A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel has been published!
Published:
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.
I have defended my thesis!
Published:
I have finally defended my thesis Gaussian Processes for 3D Shape Modelling of Noisy and Incomplete Data. An Application to Human Ears Reconstruction!
First place in ECMI 2021 Students Competition!
Published:
With Stevo Racković (University of Lisbon) and Greta Malaspina (University of Novi Sad), we won the first place in the ECMI 2021 Student Competition.
From noisy point clouds to complete ear shapes: Unsupervised pipeline has been published!
Published:
Paper From noisy point clouds to complete ear shapes: Unsupervised pipeline was published in IEEE Access.
Third place in AAAS Student E-poster Competition!
Published:
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.
publications
Range and bearing data fusion for precise convex network localization
C. Soares, F. Valdeira, and J. P. Gomes, “Range and bearing data fusion for precise convex network localization,” IEEE Signal Processing Letters , vol. 27, 2020.
From noisy point clouds to complete ear shapes: Unsupervised pipeline
F. Valdeira, R. Ferreira, A. Micheletti, and C. Soares, “From noisy point clouds to complete ear shapes: Unsupervised pipeline,” IEEE Access, vol. 9, pp. 127720–127734, Sep. 2021
A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel
G. Malaspina, S. Rackovic, and F. Valdeira, “A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel,” Journal of Mathematics in Industry, vol. 13, 2023
Probabilistic registration for Gaussian Process 3D shape modelling in the presence of extensive missing data
F. Valdeira, R. Ferreira, A. Micheletti, and C. Soares, “Probabilistic registration for Gaussian Process 3D shape modelling in the presence of extensive missing data,” SIAM Journal on Mathematics of Data Science, vol. 5, pp. 505–527, 2023
Maximum likelihood localization of a network of moving agents from ranges, bearings and velocity measurements
F. Valdeira, C. Soares and J. Gomes. "Maximum likelihood localization of a network of moving agents from ranges, bearings and velocity measurements." Signal Processing 221 (2024): 109471.
Ranking with Confidence for Large Scale Comparison Data
F. Valdeira and C. Soares, “Ranking with Confidence for Large Scale Comparison Data,” accepted at 2025 SIAM International Conference on Data Mining (SDM25)
Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low-Earth Orbit
R. Ferreira, F. Valdeira, M. Guimarães and C. Soares, "Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low-Earth Orbit," in IEEE Transactions on Aerospace and Electronic Systems, doi: 10.1109/TAES.2025.3566085.
software
REGISTRATION MODULE
Implements a registration class that can accomodate calls to other methods in a unified manner.
SHAPES MODULE
Handles shapes and datasets in 2D or 3D, including plotting, transform and io capabilities
talks
Big data processing for multivariate, noisy, and time-correlated data: human face reconstruction
Published:
As part of a Minisymposium organized by BIGMATH, I presented the initial segment of my research, with Stevo Racković (University of Lisbon) and Rongjiao Ji (University of Milan).
From noisy point clouds to complete ear models: an unsupervised pipeline for application in the prosthetic industry
Published:
An overview of my initial research with emphasis on the application component, as part of the Virtual Seminars on Complexity organized by the Universtiy of Milan.
Learning from 3D data: how mathematics can create a realistic human face
Published:
An event organized by PhD students at UNIMI to share their work with undergraduate and graduate students. I presented an overview of 3D shape modelling and the main lines of my research work.
MathYourAvatar
Published:
Dissemination event for the general public with the University of Milan, as part of the European Researchers Night. With Stevo Racković (Uni. of Lisbon) and Rongjiao Ji (Uni. of Milan), we prepared didatic activities, presented by Alessandra Micheletti (Uni. of Milan).
From noisy point clouds to complete ear models
Published:
I presented the main results of the first part of my research in the Mini Symposia Mathematics for Big Data, at the 21st ECMI Conference.
Gaussian Processes for shape modelling and registration
Published:
I presented the GP framework for 3D shape modelling and our method SFGP, together with its application to the challenging case of ear modelling.
Probabilistic registration in Gaussian Processes for shape modelling
Published:
I presented my latest work at the Euro Conference 2022, at Aalto University. It was also the final event of BIGMATH!
GP for Shape Modelling: a Probabilistic Registration Approach
Published:
Highlights of my PhD work with emphasis on the use of Gaussian Processes for Probabilistic Registration.
GP for Shape Modelling: a Probabilistic Registration Approach
Published:
Highlights of my PhD work for Postdocs, PhD and Master students in Mathematics of Lisbon Universities.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.