Faculty profile
Simone Brugiapaglia
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Research
Latest papers
Development and Application of Children's Sex- and Age-Specific Fat-Mass and Muscle-Mass Reference Curves From Dual-Energy X-Ray Absorptiometry Data for Predicting Cardiometabolic Risk.
Pediatric obesity · 2025
Real-time motion detection using dynamic mode decomposition.
EURASIP journal on image and video processing · 2025
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks.
Neural networks : the official journal of the International Neural Network Society · 2025
Latest funding
- $182,459
AI Platforms, PropTech and the Housing Crisis
SSHRC · 2025 · Co-investigator
- $135,000
Théorie de l'approximation pour l'analyse des systèmes dynamiques et l'apprentissage automatique scientifique
NSERC · 2024 · Principal investigator
- $12,500
Robust sparse recovery and deep learning algorithms in computational mathematics
NSERC · 2020 · Principal investigator
4 publications.
Development and Application of Children's Sex- and Age-Specific Fat-Mass and Muscle-Mass Reference Curves From Dual-Energy X-Ray Absorptiometry Data for Predicting Cardiometabolic Risk.
Saputra ST, Van Hulst A, Henderson M, Brugiapaglia S, Faustini C, Kakinami L
Real-time motion detection using dynamic mode decomposition.
Mignacca M, Brugiapaglia S, Bramburger JJ
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks.
Adcock B, Brugiapaglia S, Dexter N, Moraga S
Generalization limits of Graph Neural Networks in identity effects learning.
D'Inverno GA, Brugiapaglia S, Ravanelli M
AI Platforms, PropTech and the Housing Crisis
Principal investigators: Renzi, Alessandra
Théorie de l'approximation pour l'analyse des systèmes dynamiques et l'apprentissage automatique scientifique
Principal investigators: Brugiapaglia, Simone
Keywords: Modelling and mathematical simulation of natural processes; Information, computer and communication technologies
Robust sparse recovery and deep learning algorithms in computational mathematics
Principal investigators: Brugiapaglia, Simone
Robust sparse recovery and deep learning algorithms in computational mathematics
Principal investigators: Brugiapaglia, Simone
Keywords: computational mathematics; sparse recovery; neural networks; robustness analysis; compressive sensing; high-dimensional approximation; uncertainty quantification; partial differential equations; greedy algorithms; approximation theory
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Lisa Kakinami and Andraea Van Hulst: 12 shared papers
- Lisa Kakinami and Simone Brugiapaglia: 1 shared paper
- Andraea Van Hulst and Simone Brugiapaglia: 1 shared paper
- Mirco Ravanelli and Simone Brugiapaglia: 1 shared paper
- Mathematics and Statistics
- School of Nursing
- Department of Computer Science and Software Engineering/Gina Cody School of Engineering and Computer Science
Co-authors at Concordia University, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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