2023 - Research.com Computer Science in United States Leader Award
2022 - Research.com Computer Science in United States Leader Award
2011 - AAAI Feigenbaum Prize "For their influential contributions to artificial intelligence via achievements in autonomous vehicle research, including experimental efforts and research leadership of teams addressing challenges with the fielding of robotic systems in the open world."
2011 - Max Planck Research Award Intelligent systems
2010 - IEEE ITS Outstanding Research Award
2007 - Member of the National Academy of Engineering For contributions to probabilistic robotics, including mobile robot localization and mapping.
2007 - German National Academy of Sciences Leopoldina - Deutsche Akademie der Naturforscher Leopoldina – Nationale Akademie der Wissenschaften Informatics
2006 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the theory of probabilistic robot navigation and its successful real-world application.
His primary scientific interests are in Artificial intelligence, Robot, Computer vision, Mobile robot and Probabilistic logic. His research investigates the connection between Artificial intelligence and topics such as Machine learning that intersect with problems in Expectation–maximization algorithm. Sebastian Thrun focuses mostly in the field of Robot, narrowing it down to topics relating to Human–computer interaction and, in certain cases, Software architecture, Human–robot interaction and Software.
His Computer vision study frequently links to adjacent areas such as Range. His studies in Mobile robot integrate themes in fields like Matching, Algorithm and Markov chain. His work carried out in the field of Probabilistic logic brings together such families of science as Monte Carlo method, Inertial measurement unit, Robustness and Robotic mapping.
Sebastian Thrun mainly focuses on Artificial intelligence, Computer vision, Robot, Mobile robot and Robotics. In Artificial intelligence, he works on issues like Human–computer interaction, which are connected to Software architecture. The study incorporates disciplines such as Simultaneous localization and mapping and Surface in addition to Computer vision.
His Robot research is multidisciplinary, relying on both Real-time computing and Task. His Mobile robot research includes elements of Motion planning and Markov chain. He interconnects Simulation and Mathematical optimization in the investigation of issues within Motion planning.
His primary areas of investigation include Artificial intelligence, Computer vision, Algorithm, Tracking and Probabilistic logic. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His Global Positioning System research extends to the thematically linked field of Computer vision.
Many of his research projects under Algorithm are closely connected to Gaussian process with Gaussian process, tying the diverse disciplines of science together. His Probabilistic logic study combines topics from a wide range of disciplines, such as Robotics and State. The Mobile robot study combines topics in areas such as Contextual image classification and Cognitive neuroscience of visual object recognition.
Sebastian Thrun mainly investigates Artificial intelligence, Computer vision, Object detection, Point cloud and Tracking. Sebastian Thrun frequently studies issues relating to Key and Artificial intelligence. His Computer vision study incorporates themes from Probabilistic logic and Baseline.
His research in Object detection intersects with topics in Lidar, Beam, Optics and Ranging. His Tracking study combines topics in areas such as Motion and Posterior probability. Sebastian Thrun works mostly in the field of Robot, limiting it down to topics relating to Flexibility and, in certain cases, Sensor fusion.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva;Brett Kuprel;Roberto A. Novoa;Justin M. Ko.
Text Classification from Labeled and Unlabeled Documents using EM
Kamal Nigam;Andrew Kachites McCallum;Sebastian Thrun;Tom Mitchell.
Machine Learning (2000)
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Michael Montemerlo;Sebastian Thrun;Daphne Koller;Ben Wegbreit.
national conference on artificial intelligence (2002)
The dynamic window approach to collision avoidance
D. Fox;W. Burgard;S. Thrun.
IEEE Robotics & Automation Magazine (1997)
Stanley: The Robot that Won the DARPA Grand Challenge
Sebastian Thrun;Michael Montemerlo;Hendrik Dahlkamp;David Stavens.
Journal of Field Robotics (2006)
Robust Monte Carlo localization for mobile robots
Sebastian Thrun;Dieter Fox;Wolfram Burgard;Frank Dallaert.
Artificial Intelligence (2001)
Robotic mapping: a survey
Exploring artificial intelligence in the new millennium (2003)
Monte Carlo localization for mobile robots
F. Dellaert;D. Fox;W. Burgard;S. Thrun.
international conference on robotics and automation (1999)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Sebastian Thrun;Wolfram Burgard;Dieter Fox.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: