Mariona Jaramillo Civill

Phd Research Assistant @Northeastern University Center For Signal Processing, Imaging, Reasoning And Learning Spiral

Boston, MA, US

Project 1 – Clustered Federated Learning (CFL) with Unknown Number of Clusters • Addresses client heterogeneity in federated learning via Bayesian nonparametric clustering. • Uses a Dirichlet Process Mixture Model (DPMM) to dynamically infer the number of clusters while training. • Employs restricted Gibbs sampling with split–merge proposals and weighted aggregation. • Aims to improve fairness and robustness in decentralized systems with heterogeneous clients.Project 2 – Bayesian, Federated, and Active Learning Approaches for Jammer Localization • Develops ML models for privacy-preserving GNSS jammer localization in crowdsourced environments. • APBM: Differentiable pathloss model + neural network, trained with FedAvg for decentralized optimization. • Bayesian mixtures of experts: Pathloss expert combined with CNN to capture contextual effects and quantify uncertainty. • Active learning: Used to guide data collection toward the most informative regions.Improves localization accuracy and robustness in complex multipath-affected urban settings.

Northeastern University

Doctor of Philosophy - PhD

Northeastern University

Master of Science - MS

Institut Jaume Vicens Vives

International Baccaulerate (IB) + Spanish Baccaulerate

Fundació Catalunya La Pedrera

Joves i Ciència

CFIS-UPC

Bachelor of Engineering - BE

IRB Barcelona

Crazy about Biomedicine

Weizmann Institute of Science

Dr. Bessie F. Lawrence International Summer Science Institute

CFIS-UPC

Bachelor of Science - BS