Matteo Matteucci ("Laurea" 1999, MS 2002, Phd 2003) is Associate Professor at Dipartimento di Elettronica Informazione e Bioingegneria of Politecnico di Milano, Italy. In 1999 he got a Laurea degree in Computer Engineering at Politecnico di Milano, in 2002 he received a Master of Science in Knowledge Discovery and Data Mining at Carnegie Mellon University (Pittsburgh, PA), and in 2003 he got a Ph.D. in Computer Engineering and Automation at Politecnico di Milano (Milan, Italy). His main research topics are pattern recognition, machine learning, machine perception, robotics, computer vision and signal processing. His main research interest is in developing, evaluating and applying, in a practical way, techniques for adaptation and learning to autonomous systems interacting with the physical world. He has co-authored more than 50 (peer-reviewed) papers on international journals, 25 papers in International Books, and more than 150 (peer-reviewed) contributions to international conferences and workshops. He has been the principal investigator in national and international funded research projects on machine learning, autonomous robots, sensor fusion and benchmarking of autonomous and intelligent systems. His research in robotics started with the Milan Robocup Team a RoboCup team of six soccer robots equipped with custom panoramic vision sensors, adaptive color classification algorithms, and a conceptual model to integrate robot perception with information from teammates. After that he has worked on a complete 6DoF SLAM (i.e., Simultaneous Localization and Mapping) system based on multi-camera vision sporting hierarchical map decomposition through conditionally independent filtering. He is now working on sensor fusion in SLAM to fuse odometric estimates coming from different sensors (e.g., inertial measurements, laser range finder, single and multiple cameras, etc.) and semantic information coming from deep neural networks into an accurate and robust perception of the robot environment. He has been involved in the Euron Special Interest Group on Good Experimental Methodologies and Benchmarking and he is in the IEEE RAS Standard Group for the definition of IEEE P1873/D1 Draft Standard for Robot Map Data Representation for Navigation. He has been the Coordinator of the European project RAWSEEDS (http://www.rawseeds.org) a Specific Support Action for the development of a benchmarking toolkit for multi-sensor SLAM algorithms. He has been the National Scientific Coordinator of the ROAMFREE project for the development of methods for the robust estimation of robot odometry by sensor fusion funded by the Italian Ministry for the University and the Research (MIUR) under the PRIN 2009 program.
He has been the Politecnico di Milano Principal Investigator in the FP7 project RoCKIn (http://rockinrobotchallenge.eu/) for the development of 2 robot benchmarking competitions and Project Technical Manager of the European project ALMA (http://www.alma-aal.org), funded under the AAL Joint Program, for the realization of an Ambient Assisted Living system to support the autonomous mobility of the elderly. He has been Principal investigator for Politecnico di Milano of the H2020 project RockEU2 and for the development of the European Robotics League (https://www.eu-robotics.net/robotics_league/), H2020 project SciRoc (https://sciroc.eu/) for the development of a novel Smart City and Robotics competition, H2020 project DeepField for the study of deep learning techniques in field robotics, H2020 project METRICS for the development of novel robotics benchmarks and competitions, especially in the agricultural field.