Riccardo de Lutio

Riccardo de Lutio

Research Scientist

Toronto AI Lab, NVIDIA

Biography

I am a Research Scientist at NVIDIA in the Toronto AI Lab, generally interested in 3D computer vision and neural reconstruction.

Prior to that I obtained my PhD at ETH Zurich in the EcoVision Lab, Photogrammetry and Remote Sensing Group under the supervision of Prof. Jan Wegner and Prof. Konrad Schindler. During my PhD I worked on super-resolution, depth upsampling/completion, fine-grained classification and biodiversity monitoring.

Education

  • PhD in Computer Vision, 2023

    ETHZ

  • MSc in Machine Learning, 2017

    Imperial College London

  • BSc in Physics, 2016

    EPFL

Publications

John Y. Park, Riccardo de Lutio, Brendan Rapazzo, Barbara A. Ambrose, Fabian Michelangeli, Kimberly A. Watson, Serge J. Belongie, Damon P. Little (2024). NAFlora-1M: Continental-Scale High-Resolution Fine-Grained Plant Classification Dataset. In DMLR.

PDF Cite Code Dataset

Philipp Brun, Dirk N. Karger, Damaris Zurell, Patrice Descombes, Lucienne de Witte, Riccardo de Lutio, Jan D. Wegner, Niklaus E. Zimmermann (2024). Multispecies Deep Learning Using Citizen Science Data Produces More Informative Plant Community Models. In Nature Communications.

PDF Cite

Ashkan Mirzaei, Riccardo de Lutio, Seung Wook Kim, David Acuna, Jonathan Kelly, Sanja Fidler, Igor Gilitschenski, Zan Gojcic (2024). RefFusion: Reference Adapted Diffusion Models for 3D Scene Inpainting. In arXiv.

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Riccardo de Lutio, Alexander Becker, Stefano D'Aronco, Stefania Russo, Jan D. Wegner, Konrad Schindler (2022). Learning Graph Regularisation for Guided Super-Resolution. In CVPR.

PDF Cite Code

Riccardo de Lutio, John Y. Park, Kimberly A. Watson, Stefano D'Aronco, Jan D. Wegner, Jan J. Wieringa, Melissa Tulig, Richard L. Pyle, Timothy J. Gallaher, Gillian Brown, Gordon Guymer, Andrew Franks, Dhahara Ranatunga, Yumiko Baba, Serge J. Belongie, Fabian Michelangeli, Barbara A. Ambrose, Damon P. Little (2022). The Herbarium 2021 Half–Earth Challenge Dataset and Machine Learning Competition. In Frontiers in Plant Science.

PDF Cite Dataset

Riccardo de Lutio, Yihang She, Stefano D'Aronco, Stefania Russo, Philipp Brun, Jan D. Wegner, Konrad Schindler (2021). Digital Taxonomist: Identifying Plant Species in Community Scientists' Photographs. In ISPRS.

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Riccardo de Lutio, Stefano D'Aronco, Jan D. Wegner, Konrad Schindler (2019). Guided Super-Resolution as Pixel-to-Pixel Transformation. In ICCV.

PDF Cite Code Poster Blog

Experience

 
 
 
 
 
NVIDIA Toronto AI Lab
Research Scientist
NVIDIA Toronto AI Lab
Oct 2023 – Present Zurich
Working on in Zan Gojcic’s team, part of Prof. Sanja Fidler’s group.
 
 
 
 
 
NVIDIA Toronto AI Lab
Research Scientist Intern
NVIDIA Toronto AI Lab
Jul 2022 – Dec 2022 Zurich
Working in Prof. Sanja Fidler’s team.
 
 
 
 
 
ETHZ
Research Assistant
ETHZ
Oct 2018 – Feb 2023 Zurich
Research Assistant as a PhD student in the EcoVision Lab, Photogrammetry and Remote Sensing Group, supervised by Prof. Jan Dirk Wegner and Prof. Konrad Schindler.
 
 
 
 
 
Machine Learning and Optimization Lab at EPFL
Scientific Assistant
Machine Learning and Optimization Lab at EPFL
Oct 2017 – Jun 2018 Lausanne

Working on A Machine Learning Platform for Emerging Viral Diseases in Africa (part of SAFIA project) with Prof. Martin Jaggi and Dr. Mary-Anne Hartley

  • Designing an algorithm that helps clinicians better predict the cause of paediatric fever
  • Potentially helps detecting epidemic outbursts
 
 
 
 
 
Argelander-Institut für Astronomie at Bonn University
Research Intern
Argelander-Institut für Astronomie at Bonn University
Jun 2016 – Jul 2016 Bonn

Working on Artificial neural networks handling noisy features with Dr. Malte Tewes

  • Noisy multivariate data, which depend on some physical explanatory parameters
  • Creating a model neural network architecture that finds accurate estimates for parameters

Education

 
 
 
 
 
ETHZ
PhD Computer Vision
ETHZ
Oct 2018 – Jun 2023 Zurich
Ph.D. in the EcoVision Lab, Photogrammetry and Remote Sensing Group, supervised by Prof. Jan Dirk Wegner and Prof. Konrad Schindler.
 
 
 
 
 
Imperial College London
MSc Computing (Machine Learning)
Imperial College London
Sep 2016 – Aug 2017 London

First Class Honours. Master Project, F1 Overtaking Model with Mercedes F1 Team and Prof. Marc Deisenroth.

  • Creating a probabilistic model for overtaking during a race, key aspect of race simulation engine.
 
 
 
 
 
Imperial College London
BSc Physics - Exchange Program
Imperial College London
Sep 2015 – Jun 2016 London

Bachelor Project, Machine Learning and Galaxy Surveys with Dr. David Clements.

  • Finding clusters in an unsupervised way and comparing them with the astronomical classification of the galaxies.
 
 
 
 
 
EPFL
BSc Physics
EPFL
Sep 2013 – Jun 2016 Lausanne

Teaching

Courses

  • Introduction to object-oriented programming (C++) - Fall 2014, Spring 2015
  • Image Interpretation - Fall 2018 - 2020
  • Geodetic Project Course: 3D modeling using different sensors - Summer 2019, Summer 2021

Supervision

  • Monitoring vitality of urban trees combining airborne imagery and deep learning, Luca Gaia
  • Using machine learning to identify plant species in images acquired by citizen scientists, Yihang She
  • Curriculum learning - helping computers to gradually learn new things, Luca Gaia
  • Detektion von Füssgängerstreifen in Luftbildern, Elie Vuadens

Additional Activities

Organiser of the Herbarium Competition,
CVPR Jan 2021 – Jun 2022
Organiser of the Herbarium Competition, Fine-Grained Visual Categorization, CVPR.
Co-Editor of the Medium blog of the EcoVision Lab.
Medium Jan 2020
Co-Organiser of the tutorial session at MLEG.
MLEG Jan 2019 – Jan 2019
Co-Organiser of the tutorial session at the 1st Swiss Workshop on Machine Learning for Environmental and Geosciences, MLEG.
Volunteer Responsible for Speakers
AMLD Jan 2018 – Jan 2018
Volunteer responsible for speakers at 2nd Applied Machine Learning Days, AMLD.