Ihmiset

Francesco Verdoja

Academy Research Fellow

T410 Dept. Electrical Engineering and Automation

Full researcher profile

https://research.aalto.fi/...

Sähköposti

francesco.verdoja@aalto.fi

Puhelinnumero

+358504709544

Palkinnot

Best Safety, Security, and Rescue Robotics Paper finalist

Nominated for the Best Safety, Security, and Rescue Robotics Paper award sponsored by the International Rescue System Initiative (IRSI) at the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Invitation or ranking in competition Department of Electrical Engineering and Automation Oct 2024

2022 Best Paper Award

Award or honor granted for a specific work Department of Electrical Engineering and Automation Sep 2024

PhD scholarship Sisvel Technology

3-year PhD scholarship, founded by Sisvel Technology, devoted to the PhD project "Innovative techniques for segmentation and movement estimation in HD video sequences".

Award or honor granted for academic or artistic career Department of Electrical Engineering and Automation Jan 2014

Best Student Award

A scholarship of 500 € awarded to the best PhD student attending the school

Invitation or ranking in competition Department of Electrical Engineering and Automation Jul 2014

Best 10% Paper

The article "Superpixel-driven Graph Transform for Image Compression" has been ranked amongst the best 10% of all the accepted articles at ICIP 2015.

Award or honor granted for a specific work Department of Electrical Engineering and Automation Sep 2015

Academic GPU Grant

Awarded a GPU NVIDIA GeForce Titan Xp to support my research on deep learning in robotics

Award or honor granted for academic or artistic career Department of Electrical Engineering and Automation Aug 2018

Tutkimusryhmät

Intelligent Robotics, Academy Research Fellow
Intelligent Robotics, Staff Scientist

Francesco Verdoja

Palkinnot

Best Safety, Security, and Rescue Robotics Paper finalist

2022 Best Paper Award

PhD scholarship Sisvel Technology

Best Student Award

Best 10% Paper

Academic GPU Grant

Tutkimusryhmät

Julkaisut

REACT: Real-time Efficient Attribute Clustering and Transfer for Updatable 3D Scene Graph

Do Visual-Language Grid Maps Capture Latent Semantics?

QuASH: Using Natural-Language Heuristics to Query Visual-Language Robotic Maps

Jointly Learning Cost and Constraints from Demonstrations for Safe Trajectory Generation

Jointly Learning Cost and Constraints from Demonstrations for Safe Trajectory Generation

Evaluating the quality of robotic visual-language maps

Localization Under Consistent Assumptions Over Dynamics

Modeling movable objects improves localization in dynamic environments

Object-Oriented Grid Mapping in Dynamic Environments

Bayesian Floor Field: Transferring people flow predictions across environments