Davide Scaramuzza

Professor and Director of the Robotics and Perception Group


Short Biography


Davide Scaramuzza

Davide Scaramuzza (Italian) is a Professor of Robotics and Perception at both departments of Informatics (University of Zurich) and Neuroinformatics (joint between the University of Zurich and ETH Zurich), where he directs the Robotics and Perception Group. His research lies at the intersection of robotics, computer vision, and machine learning, using standard cameras and event cameras, and aims to enable autonomous, agile, navigation of micro drones in search-and-rescue applications.

After a Ph.D. at ETH Zurich (with Roland Siegwart) and a postdoc at the University of Pennsylvania (with Vijay Kumar and Kostas Daniilidis), from 2009 to 2012, he led the European project sFly, which introduced the PX4 autopilot and pioneered visual-SLAM-based autonomous navigation of micro drones in GPS-denied environments. From 2015 to 2018, he was part of the DARPA FLA program(Fast Lightweight Autonomy) to research autonomous, agile navigation of micro drones in GPS-denied environments. In 2018, his team won the IROS 2018 Autonomous Drone Race and in 2019 it ranked second in the AlphaPilot Drone Racing world championship.

For his research contributions to autonomous, vision-based, drone navigation and event cameras, he won prestigious awards, such as a European Research Council (ERC) Consolidator Grant, the IEEE Robotics and Automation Society Early Career Award, an SNSF-ERC Starting Grant, a Google Research Award, the KUKA Innovation Award, two Qualcomm Innovation Fellowships, the European Young Research Award, the Misha Mahowald Neuromorphic Engineering Award, a Facebook Distinguished Faculty Research Award, two NASA TechBrief Awards, and several paper awards.

He coauthored the book "Introduction to Autonomous Mobile Robots" (published by MIT Press; 10,000 copies sold) and more than 100 papers on robotics and perception published in top-ranked journals (Science Robotics, TRO, T-PAMI, IJCV, IJRR) and conferences (RSS, ICRA, CVPR, ICCV, CORL, NeurIPS).

He served as a consultant for the United Nations on topics such as disaster response and disarmament, as well as the Fukushima Action Plan on Nuclear Safety He also consulted several drones and computer-vision companies, to which he has also transferred research results. In 2015, he co-founded Zurich-Eye, today Facebook Zurich, which developed the world-leading virtual-reality headset, Oculus Quest, which sold over 10 million units. In 2020, he co-founded SUIND, which developes smart agricultural drones. He was also the strategic advisor of Dacuda, today Magic Leap Zurich.

Many aspects of his research have been prominently featured in broader media, such as The New York Times, The Economist, Forbes, Discovery Channel, La Repubblica, Neue Zurcher Zeitung and also in technology-focused media, such as IEEE Spectrum, MIT Technology Review, Tech Crunch, Wired, The Verge.

FOR A DETAILED BIOGRAPHY CHECK OUT HERE.


Contributions

Davide Scaramuzza is most known for:

  • (1) pioneering contributions to learning agile vision-based flight. video, paper, research.
  • (2) pioneering contributions to event-camera-based algorithms for mobile robots. 2014, 2017. Link to the research page.
  • (3) pioneering contributions to visual-inertial-SLAM-based autonomous navigation of micro drones. ICRA'10 paper.
  • (4) inventing the 1-point RANSAC algorithm, an effective and computationally efficient (1000 times faster) reduction of the standard 5-point RANSAC for visual odometry, when the vehicle motion is non-holonomic. IJCV'11 paper.
  • (5) developing the Omnidirectional Camera Calibration Toolbox for MATLAB (OCamCalib), used at many companies (e.g., NASA, Philips, Bosch, Daimler, etc.). LINK. The toolbox is also part of the Matlab Computer Vision Toolbox.


In the Press (full list here)

28.1.2022 The Economist

RPG research on event cameras featured in The Economist! : [ Link ]

26.10.2021 Forbes

This hotshot AI drone can speed through complex environments thanks to new kind of virtual training : [ Link ]

23.07.2021 Forbes

"AI-Controlled Drone Racer Has Beaten Human Pilots For The First Time" [ Link ]

09.01.2020 New York Times

"A drone from the University of Zurich is an engineering and technical marvel..." (full article)


13.08.2019 BBC News

Drones are able to change their shape while flying [ Link ]

29.05.2019 BBC

Tech gives drone the ability to avoid mid-air crashes [ Link ]

21.04.2015BBC

"Drones Under Control" [ Link ]


16.05.2019 La Repubblica

L'intervista - Davide Scaramuzza: "Ma devono imparare a muoversi da soli" [ Link ]

14.12.2018 La Repubblica

Droni con 'ali pieghevoli' per passare ovunque[ Link ]

14.02.2018La Repubblica

Tra alberi e palazzi ora il drone fa lo slalom [ Link ]


27.07.2019Neue Zurcher Zeitung

"In der Forschung zu autonom fliegenden Drohnen spielt die Uni Z�rich weltweit an vorderster Front mit. Jetzt kann sich deren Robotics-Team an einem internationalen Drohnenrennen in den USA beweisen" [ Link ]

30.08.2018Neue Zurcher Zeitung

"Wie Robotikprofessor Scaramuzza Erdbebenopfern mit Drohnen helfen will [ Link ]

24.01.2018Neue Zurcher Zeitung

"So kommen Drohnen sicher durch die Stadt" [ Link ]


07.07.2022 IEEE Spectrum

IEEE Spectrum reports on the world's first AI vs. Human Drone Race organized by us: [ Link ]

08.10.2021 IEEE Spectrum

Autonomous racing drones dodge through forests at 40 kph: [ Link ]

09.02.2021 IEEE Spectrum

Our work on autonomous quadrotor flight despite rotor failure with onboard vision sensors is featured on IEEE Spectrum: [ Link ]

08.10.2020 IEEE Spectrum

Our work on Deep Drone Acrobatics is featured on IEEE Spectrum. AI-Powered Drone Learns Extreme Acrobatics: [ Link ]

04.06.2019 IEEE Spectrum

To Fly Solo, Racing Drones Have a Need for AI Speed Training [ Link ]

13.05.2019 IEEE Spectrum

"Event Camera Helps Drone Dodge Thrown Objects" [ Link ]

13.12.2018IEEE Spectrum

"Foldable Drone Changes Its Shape in Mid-Air" [ Link ]

25.01.2018IEEE Spectrum

"AI-Powered Drone Mimics Cars and Bikes to Navigate Through City Streets" [ Link ]

25.09.2017IEEE Spectrum

Drone With Event Camera Takes First Autonomous Flight [ Link ]

28.09.2016IEEE Spectrum

"Aggressive Quadrotors Conquer Gaps With Ultimate Autonomy" [ Link ]

14.04.2015IEEE Spectrum

"You Can Launch This Quadrotor by Throwing It in the Air" [ Link ]

07.10.2014IEEE Spectrum

"Dynamic Vision Sensors Enable High-Speed Maneuvers With Robots" [ Link ]

03.05.2012IEEE Spectrum

"sFly Quadrotors Navigate Outdoors All By Themselves" [ Link ]


09.12.2016MIT Technology Review

"Watch This Robotic Quadcopter Fly Aggressively Through Narrow Gaps"[ Link ]


27.06.2018Wired

Drones Just Learned to Fly Solo, Which Means Pro Racers May Soon Meet Their Match [ Link ]

11.02.2016Wired

"This drone uses AI to find its way through a forest"[ Link ]

Video Highlights

July 13, 2022

Our lab is featured on the Italian RAI1 TV program SuperQuark. Watch the full video report about our research on autonomous drones, from drone racing to search and rescue, from standard to event cameras. The video is in Italian with English subtitles.

October 15, 2021

Watch our drone flying at high speeds through cluttered environments! Read our Learning High-Speed Flight in the Wild paper for further etails.

June 11, 2021

TimeLens is the first event-based video frame interpolation method that generates high speed video from low framerate RGB frames and high-temporal-resolution asynchronous events. TimeLens achieves 50 times video ussamplig rates and 40 times memory footprint savings! a href="https://rpg.ifi.uzh.ch/TimeLens.html">Visit the project page

Jan 13, 2021

Watch our quadrotor flies after motor failure with only onboard vision sensors! Read our RA-L paper for further details.

June 11, 2020

AI Drone faster than Humans? Time-Optimal Planning for Quadrotor Waypoint Flight. Read our Time-optimal planning for quadrotor waypoint flight paper for further details.

June 11, 2020

Watch our drone flying very agile acrobatics maneuvers! Read our Deep Drone Acrobatics paper for further details.

March 18, 2020

Watch our drone play dodgeball using an event camera! Read our Science Robotics paper for further details.

December 13, 2018

The foldable drone (RAL'18 paper).


Paper Awards




  • 2022.27.05 - RAL Best Paper Award for our paper on controlling a quadrotor after motor failure using event cameras. PDF
  • 2021.10.05 - IEEE Transactions on Robotics Best Paper Award Honorable Mention for our paper Deep Drone Racing
  • 2020.07.16 - RSS Best Systems Paper Award for AlphaPilot
  • 2020.07.16 - RSS Best Paper Award finalist for Deep Drone Acrobatics
  • 2019.05.24 - ICRA 2019 workshop on SLAM Benchmarking, Best Paper Award, PDF
  • 2019.05.22 - RAL Best Paper Award Honorable Mention for paper "Ultimate SLAM". PDF
  • 2018.11.01 - CORL Best System Paper Award for our paper Deep Drone Racing. PDF
  • 2018.05.14 - IEEE Transactions on Robotics Best Paper Award, PDF, Press coverage
  • 2017.09.27 - IROS 2017 Best Paper Award finalist in Rescue Robotics. PDF
  • 2017.06.01 - RSS 2017 Best Student Paper Award Finalist for our paper on Fast Trajectory Optimization. PDF
  • 2016.10.01 - IROS 2016 Best Application Paper finalist for our paper on visual Odometry with Event Cameras. PDF
  • 2016.09.20 - BMVC 2016 Best Industry Paper Award for our paper on Event-based Multi View Stereo. PDF
  • 2015.06.01 - RSS 2015 Best Paper Award finalist! for our paper on IMU Preintegration. PDF


Other Awards


Davide Scaramuzza

  • 2021.26.09 - NASA Tech Briefs Award for our work on controlling a quadrotor after motor failure using event cameras. PDF
  • 2019.10.12 - ERC (European Research Council) Consolidator Grant (2M EUR) (press release)
  • 2019.04.09 - Drone Hero Contest 2019 - Innovative Drone for the foldable drone
  • 2019.01.01 - Facebook Distinguished Faculty Award
  • 2018.10.03 - IROS 2018 Autonomous Drone Race 1st place winner
  • 2017.09.27 - IROS 2017 Autonomous Drone Race 2nd place winner
  • 2017.07.01 - Intel Network of Intelligent System Award (170k USD)
  • 2017.06.01 - Misha Mahowald Prize for Neuromorphic Engineering
  • 2017.03.01 - EU Robotics Transfer Award to Fotokite
  • 2016.03.30 - AAAI Video Award nomination
  • 2014.11.21 - SNSF-ERC Starting Grant (1.5 million EUR for 5 years)
  • 2014.06.01 - IEEE Robotics and Automation Society Early Career Award"
  • 2014.06.01 - KUKA Innovation Award (20,000 EUR)
  • 2014.04.01 - Google Research Award
  • 2012.06.01 - European Young Researcher Award 2012 - Sponsored by EU and Euroscience
  • 2010.03.30 - Finalist of the George Giralt EURON PhD award (for the best European PhD thesis)
  • 2009.09.09 - ROBOTDALEN Scientific Award for my PhD thesis. Sponsored by EU, IEEE, ABB.
  • 2009.09.09 - European Micro Aerial Vehicle competition.
  • 2005.04.01 - FEDERCOMIN-AICA Master thesis Award (best Italian Master thesis in ICT).
  • 2004.07.02 - Best student of the year Award (800 EUR), Ternana Opera Educatrice, Terni, Italy.


Talks



CORL - November 2021 Keynote
Learning to Fly in the Wild


RoboHub Podcast - March 2022
Event Cameras




CMU Seminar - October 2021 Seminar
Visual SLAM


IEEE RAS Interview - July 2021
My research plus lab tour




MIT Robotics Today Seminar - November 2020
Autonomous, Agile Micro Drones: Perception, Learning, and Control


TEDx Zurich - November 2012
Autonomous Flying Robots




Book


I was the main author of this second edition to which I dedicated a full year of intense writing and literature research. This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners in their Master or PhD programs.


R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza

Introduction to autonomous mobile robots 2nd Edition (hardback)

A Bradford Book, The MIT Press, ISBN: 978-0-262-01535-6, February, 2011

MIT Website Book Website Buy


Patents



Event-SLAM patent

H. Rebecq, G. Gallego, D. Scaramuzza

Simultaneous Localization and Mapping with an Event Camera

Pub. No.: US 2019/0197715 A1

PDF


Event-SLAM patent

H. Rebecq, D. Scaramuzza

Visual Inertial Odometry with an Event Camera

Pub. No.: EP2018073641W2018-09-03

PDF


Select Publications


For a full list of publications, see here or Google Scholar.


Arxiv21_Sun

S. Sun, A. Romero, P. Foehn, E. Kaufmann, D. Scaramuzza

A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight

IEEE Transactions on Robotics, 2022

PDF YouTube


Arxiv21_Romero

A. Romero, S. Sun, P. Foehn, D. Scaramuzza

Model Predictive Contouring Control for Time-Optimal Quadrotor Flight

IEEE Transactions on Robotics, 2022

PDF YouTube


TRO21_Yunlong

Y. Song, D. Scaramuzza

Policy Search for Model Predictive Control with Application for Agile Drone Flight

IEEE Transactions on Robotics (T-RO), 2022.

PDF YouTube Project Webpage Code


Science21_Loquercio

A. Loquercio*, E. Kaufmann*, R. Ranftl, M. Müller, V. Koltun, D. Scaramuzza

Learning High-Speed Flight in the Wild

Science Robotics, 2021.

Project Webpage and Datasets PDF YouTube Code


RSS20_Foehn

P. Foehn*, D. Brescianini*, E. Kaufmann*, T. Cieslewski, M. Gehrig, M. Muglikar, D. Scaramuzza

AlphaPilot: Autonomous Drone Racing

Autonomous Robots (AuRo), 2021

Best Systems Paper Award!

PDF YouTube RSS2020 Pitch Video


Time-Optimal Quadrotor Trajectories

P. Foehn, A. Romero, D. Scaramuzza

Time-Optimal Planning for Quadrotor Waypoint Flight

Science Robotics, July 21, 2021.

PDF YouTube Code


RSS21_Bauersfeld

L. Bauersfeld*, E. Kaufmann*, P. Foehn, S. Sun, D. Scaramuzza

NeuroBEM: Hybrid Aerodynamic Quadrotor Model

Robotics: Science and Systems (RSS), 2021.

PDF YouTube Project Page and Dataset


CVPR21_Gehrig

S. Tulyakov*, D. Gehrig*, S. Georgoulis, J. Erbach, M. Gehrig, Y. Li, D. Scaramuzza

TimeLens: Event-based Video Frame Interpolation

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, 2021.

PDF Video Code Project Page and Dataset Slides


RAL21_Fuchs

F. Fuchs, Y. Song, E. Kaufmann, D. Scaramuzza, P. Duerr

Super-Human Performance in Gran Turismo Sport Using Deep Reinforcement Learning

IEEE Robotics and Automation Letters (RA-L), 2021.

PDF YouTube


RAL21_Sun

S. Sun, G. Cioffi, C. de Visser, D. Scaramuzza

Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors: Frames vs. Events

IEEE Robotics and Automation Letters (RA-L), 2021.

Best Paper Award!

PDF YouTube Code


RSS20_Kaufmann

E. Kaufmann*, A. Loquercio*, R. Ranftl, M. Müller, V. Koltun, D. Scaramuzza

Deep Drone Acrobatics

Robotics: Science and Systems (RSS), 2020

Best Paper Award finalist!

PDF YouTube RSS2020 Pitch Video Blog Post Code


Science20_Falanga

Davide Falanga, Kevin Kleber, and Davide Scaramuzza

Dynamic Obstacle Avoidance for Quadrotors with Event Cameras

Science Robotics, March 18, 2020.

PDF Supplementary Material YouTube


High Speed and High Dynamic Range Video with an Event Camera

H. Rebecq, R. Ranftl, V. Koltun, D. Scaramuzza

High Speed and High Dynamic Range Video with an Event Camera

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.

PDF YouTube Code Project Page


TRO19_Loquercio

A. Loquercio, E. Kaufmann, R. Ranftl, A. Dosovitskiy, V. Koltun, D. Scaramuzza

Deep Drone Racing: From Simulation to Reality with Domain Randomization

IEEE Transactions on Robotics, 2019

YouTube PDF Code


EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames

D. Gehrig, H. Rebecq, G. Gallego, D. Scaramuzza

EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames

International Journal of Computer Vision (IJCV), 2019.

PDF YouTube Evaluation Code Tracking Code


Nano-Dronet

D. Palossi, A. Loquercio, F. Conti, E. Flamand, D. Scaramuzza, L. Benini

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

IEEE Internet of Things Journal, 2019

Video, PDF, Code


Event-based Vision: A Survey

G. Gallego, T. Delbruck, G. Orchard, C. Bartolozzi, B. Taba, A. Censi, S. Leutenegger, A. Davison, J. Conradt, K. Daniilidis, D. Scaramuzza

Event-based Vision: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.

PDF


RAL18_Falanga

D. Falanga, K. Kleber, S. Mintchev, D. Floreano, D. Scaramuzza

The Foldable Drone: A Morphing Quadrotor that can Squeeze and Fly

IEEE Robotics and Automation Letters (RA-L), 2019.

PDF YouTube Project page


A Unifying Contrast Maximization Framework for Event Cameras

G. Gallego, H. Rebecq, D. Scaramuzza

A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth and Optical Flow Estimation

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, 2018.

Spotlight Presentation.

PDF YouTube


3D reconstruction with an Event-based camera in real-time

A. Loquercio, A.I. Maqueda, C.R. Del Blanco, D. Scaramuzza

DroNet: Learning to Fly by Driving

IEEE Robotics and Automation Letters (RA-L), 2018.

PDF YouTube Software and Datasets


RAL18_VidalRebecq

T. Rosinol Vidal, H.Rebecq, T. Horstschaefer, D. Scaramuzza

Ultimate SLAM? Combining Events, Images, and IMU for Robust Visual SLAM in HDR and High Speed Scenarios

IEEE Robotics and Automation Letters (RA-L), 2018.

Best Paper Award finalist (2nd out of 720 papers)!

PDF YouTube ICRA18 Video Pitch Project Webpage


RSS15_Forster

C. Forster, L. Carlone, F. Dellaert, D. Scaramuzza

On-Manifold Preintegration for Real-Time Visual-Inertial Odometry

IEEE Transactions on Robotics, vol 33, no. 1, pp. 1-21, Feb. 2017.

IEEE Transactions on Robotics' Best Paper Award 2017
RSS'15 Best Paper Award Finalist!
Oral Presentation: Acceptance Rate 4%

PDF YouTube


TRO17_Forster-SVO

C. Forster, Z. Zhang, M. Gassner, M. Werlberger, D. Scaramuzza

SVO: Semi-Direct Visual Odometry for Monocular and Multi-Camera Systems

IEEE Transactions on Robotics, Vol. 33, Issue 2, pages 249-265, Apr. 2017.

Includes comparison against ORB-SLAM, LSD-SLAM, and DSO and comparison among Dense, Semi-dense, and Sparse Direct Image Alignment.

PDF YouTube Binaries Download


IROS2013_Majdik

D. Scaramuzza, F. Fraundorfer

Visual Odometry: Part I - The First 30 Years and Fundamentals

IEEE Robotics and Automation Magazine, Volume 18, issue 4, 2011.

PDF



Hobbies


In my free time, I like playing piano and magic tricks. My passion for Magic was born at age 14. I paid my undegraduate studies working part-time as magician in restaurants, bars, and children parties, but I also did several performances on stage in public squares and theatres. Nowadays, I still play magic tricks for colleagues and friends and it has almost become a tradition during the social banquets of robotics conferences (usually ICRA and IROS) ;-) Below, you can see one of my latest show during the Scientifica Science Festival at ETH Zurich. If you would like to see more, you can check out my personal YouTube channel! But notice that, if you are looking for robot videos, then you should check out my lab's YouTube channel! Here, you can read my interview from NCCR Robotics about my hobby and how I decided to follow the academic career (LINK)!


Davide Scaramuzza

Long Biography


Davide Scaramuzza was born in Terni, Italy. He received a Master degree in Electronics and Information Engineering (2004, Summa cum Laude, adviser: Paolo Valigi), from the Dep. of Engineering, of the University of Perugia, and a PhD in Robotics and Computer Vision (2008, adviser: Roland Siegwart) from the Department of Mechanical and Process Engineering of ETH Zurich.

After a postdoc at the GRASP Lab of the University of Pennsylvania, (advisers: Vijay Kumar and Kostas Daniilidis), he was appointed Assistant Professor at the University of Zurich in 2012. He got promoted to Tenured Associated Professor in 2017 with double affiliation with the Departments of Informatics (University of Zurich) and the Dep. of Neuroinformatics (University of Zurich and ETH Zurich).

His research lies at the intersection of Robotics, Computer vision, and Machine Learning. Specifically, he investigates the use of standard cameras, neuromorphic event cameras, and inertial sensors to enable autonomous navigation of micro drones in challenging real-world scenarios, such as remote inspection and search and rescue after natural disasters. These scenarios raise fundamental research challenges, which are currently unsolved, but also touch him personally: he comes from the center of Italy, which is often affected by earthquakes (link).

From 2009 to 2012, he led the European project sFly, which pioneered visual-inertial autonomous drone navigation in GPS-denied environments ([Bloesch, ICRA'10]) and led to the development of the PX4 autopilot (developed by Lorenz Meier), today a standard tool in over half a million hobby and commercial drones. From 2015 to 2018, he was part of one the three teams selected by DARPA for the Fast Lightweight Autonomy (FLA) Program to research autonomous, agile navigation of micro drones in GPS-denied environments ([Mohta, JFR'18]). In 2018, his team won the IROS 2018 Autonomous Drone Race (video, paper) and in 2019 it ranked second in the AlphaPilot Drone Racing world championship (video, paper). In 2022, he and his team organized the first AI vs. Human drone race, where the AI vision-based drone outflew the world's best human pilots (link).

Davide Scaramuzza is recognized as a world expert in autonomous, vision-based drone navigation, visual odometry, and neuromorphic event cameras. To promote research development in these fields, he has edited several journal special issues and co-organized many international workshops on visual navigation of drones and event cameras.

For his research contributions to autonomous, vision-based, drone navigation and event cameras, he won prestigious awards, such as an ERC Consolidator Grant, the IEEE Robotics and Automation Society Early Career Award, an SNSF-ERC Starting Grant, a Google Research Award, the KUKA Innovation Award, two Qualcomm Innovation Fellowships, the European Young Research Award, the Misha Mahowald Neuromorphic Engineering Award, a Facebook Distinguished Faculty Award, and several paper awards. The IEEE Robotics and Automation Society Early Career Award represents the highest recognition for early-career achievements by the IEEE Robotics and Automation Society. He has also been invited to speak at prestigious conferences, international workshops, and universities (full list in his CV).

He has published over 100 scientific articles (link) in top-ranked robotics and computer vision journals and conferences (Science Robotics, PAMI, TRO, IJRR, IJCV, JFR, ICRA, IROS, RSS, CVPR, ICCV) and has released over forty Open Source software packages. His publications have been cited over 35,000 times (Google Scholar). His Google Scholar H-index is 86.

He co-authored the second edition of the book "Introduction to Autonomous Mobile Robots", published by MIT Press in 2011. This book has sold over 10 thousand copies worldwide and is among the most used textbooks for teaching mobile robotics in universities.

He served as a consultant for the United Nations on topics such as disaster response and disarmament, as well as the Fukushima Action Plan on Nuclear Safety He also consulted several drones and computer-vision companies, to which he has also transferred research results. He also has entrepreneurial achievements. In 2015, he co-founded Zurich-Eye, dedicated to the commercialization of visual-inertial navigation solutions for mobile robots. In 2016, Zurich-Eye bacame Facebook Zurich (English, German, recent news), which developed the world-leading virtual-reality headset, Oculus Quest, which sold over 10 million units world wide (full story here). In 2020, he co-founded SUIND, which developes smart agricultural drones. He was also the strategic advisor of Dacuda, which developed inside-out virtual-reality solutions. Dacuda became Magic Leap Zurich in 2017..

Many aspects of his research have been prominently featured in broader media, such as The New York Times, The Economist, Forbes, Discovery Channel, La Repubblica, Neue Zurcher Zeitung and also in technology-focused media, such as IEEE Spectrum, MIT Technology Review, Tech Crunch, Wired, The Verge (full list here).



Contact


Address: University of Zurich, Andreasstrasse 15, Office 2.10, 8050 Zurich, Switzerland
Email: sdavide (at) ifi (dot) uzh (dot) ch (NB: for INTERNSHIP, PhD, and Postdoc applications, please read below)
Phone: +41 44 635 24 09


  • INTERNSHIP applications: If you are seeking an internship in my lab you need to be enrolled in a Master program in your university. Applications from Bachelor students will not be answered. If you are a Master student and you wish to apply, please send me: 1) Your CV; 2) Transcripts of your Bachelor and Master grades; 3) a 2-page proposal containing: a) a description of the project you intend to do in my lab which is relevant to my research; b) comments on your experience in the area; c) related work, and d) a timeline of the project from the start to the end. Please make sure everything fits in two A4 page. Please do not send me reminders asking me the status of your application. I will answer only in case of positive feedback.
  • PhD and Postdoc applications: check out my open positions here. Please notice that unsolicited applications will not be answered.