Artificial intelligence · Computer vision · Perception · Autonomous vehicles

About me

I’m a Research Scientist in NVIDIA’s Spatial Intelligence Lab (SIL), following a postdoctoral position at NVIDIA. My research spans artificial intelligence, computer vision, perception, and autonomous vehicles. I’m particularly interested in foundation and world models, learning from LiDAR and cameras, targeting autonomous driving or robotics applications.

I completed my PhD at the University of Trento’s MHUG laboratory, advised by Elisa Ricci, Nicu Sebe, and Fabio Galasso. My doctoral work focused on deep learning and computer vision. During my PhD, I also visited the Technical University of Munich, working with Aljoša Ošep and Laura Leal-Taixé, and completed a research internship at NAVER LABS Europe.

Outside research, I enjoy climbing, hiking in the mountains, and playing guitar.

Research interests

  • 3D computer vision
  • LiDAR & camera perception
  • Foundation & world models
  • Autonomous driving & robotics
  • 3D reconstruction

Education

PostDoc, NVIDIA

Multimodal perception & reconstruction

2024 – 2026

PhD, University of Trento

Deep Learning for Computer Vision · cum laude

Nov 2019 – Apr 2024

MSc, University of Trento

Information and Communications Engineering · cum laude

Sep 2017 – Oct 2019

Background

Experience

  1. NVIDIA2026 – Present

    Research Scientist

    Work on perception, reconstruction, and foundation models for autonomous vehicles in the Spatial Intelligence Lab (SIL), contributing to internal products and research publications. Supervise research interns.

  2. NVIDIA2024 – 2026

    Postdoctoral Researcher

    Researched multimodal 2D, 3D, and 4D perception and reconstruction across research and product projects. Co-supervised Complete Anything in LiDAR, from implementation and research to paper writing, and contributed to efficient multi-camera tokenization for autonomous driving.

  3. NAVER LABS EuropeApr 2023 – Oct 2023

    PhD Research Intern

    Investigated multimodal perception and knowledge transfer across dense and sparse recognition tasks in the Vision Representation Learning team, supervised by Riccardo Volpi and Yannis Kalantidis. Received the NAVER LABS Europe Intern Day Distinguished Award for the multitask learning project.

  4. Technical University of MunichMar 2022 – Nov 2022

    Visiting PhD Researcher

    Developed 3D perception methods that remain robust across different domains and environments, under the supervision of Laura Leal-Taixé and Aljoša Ošep.

  5. University of TrentoNov 2019 – Apr 2024

    PhD Researcher

    Studied 3D point-cloud perception under distribution shifts and limited supervision, including self-supervised representation learning and novel-class discovery. Completed a PhD in Deep Learning for Computer Vision, cum laude, advised by Elisa Ricci, Nicu Sebe, and Fabio Galasso.

Research

Publications

A selection of my work in computer vision and 3D perception.

All papers on Google Scholar

ICML · 2025

Towards Learning to Complete Anything in Lidar

Ayça Takmaz, Cristiano Saltori, Neehar Peri, Tim Meinhardt, Riccardo de Lutio, Laura Leal-Taixé, Aljoša Ošep

IJCV · 2025

Novel Class Discovery Meets Foundation Models for 3D Semantic Segmentation

Luigi Riz, Cristiano Saltori, Yiming Wang, Elisa Ricci, Fabio Poiesi

RA-L · 2025

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving

Boris Ivanovic, Cristiano Saltori, Yurong You, Yan Wang, Wenjie Luo, Marco Pavone

CVPR · 2025

Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding

Jinlong Li, Cristiano Saltori, Fabio Poiesi, Nicu Sebe

IJCV · 2024

Unsupervised Point Cloud Representation Learning by Clustering and Neural Rendering

Guofeng Mei, Cristiano Saltori, Elisa Ricci, Nicu Sebe, Qiang Wu, Jian Zhang, Fabio Poiesi

ICCV · 2023

Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation

Cristiano Saltori, Aljoša Ošep, Elisa Ricci, Laura Leal-Taixé

WACV · 2023

Overlap-guided Gaussian Mixture Models for Point Cloud Registration

Guofeng Mei, Fabio Poiesi, Cristiano Saltori, Jian Zhang, Elisa Ricci, Nicu Sebe

CVPR · 2023

Novel Class Discovery for 3D Point Cloud Semantic Segmentation

Luigi Riz, Cristiano Saltori, Elisa Ricci, Fabio Poiesi

TPAMI · 2023

Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation

Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Fabio Poiesi, Elisa Ricci

ECCV · 2022

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

Cristiano Saltori, Evgeny Krivosheev, Stéphane Lathuilière, Nicu Sebe, Fabio Galasso, Giuseppe Fiameni, Elisa Ricci, Fabio Poiesi

BMVC · 2022

Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding

Guofeng Mei, Cristiano Saltori, Fabio Poiesi, Jian Zhang, Elisa Ricci, Nicu Sebe, Qiang Wu

ECCV · 2022

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Elisa Ricci, Fabio Poiesi

3DV · 2020

SF-UDA³D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection

Cristiano Saltori, Stéphane Lathuilière, Nicu Sebe, Elisa Ricci, Fabio Galasso

ICIAP · 2019

Regularized Evolutionary Algorithm for Dynamic Neural Topology Search

Cristiano Saltori, Subhankar Roy, Nicu Sebe, Giovanni Iacca

Get in touch

Contact

Let’s talk research.

If you’d like to discuss my work or a potential collaboration, feel free to reach out.

Connect on LinkedIn