Jan Skaloud

Web site:  Web site:  https://cryos.epfl.ch

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Administrative data

Fields of expertise

Satellite positioning, inertial and integrated navigation Sensor orientation and calibration, attitude determination Mobile mapping, airborne laser scanning Adjustment methods, Kalman Filtering 

Awards

2021 : Samuel Gamble Award, carrier contribution in photogrammetry & sensing : International Society for Photogrammetry and Remote Sensing

2020 : big U.V. Helava Award - best paper in J ISPRS over 2016-2019 period : International Society for Photogrammetry and Remote Sensing

2017 : Best Demo Award - 4th IEEE International Workshop on Metrology & Aerospace : IEEE

2014 : Hansa Luftbild Award - best-paper of the year in PFG journal : PFG Journal

2012 : Karl Kraus Medal - best textbook in Photogrammetry, Remote Sensing and GIS : International Society for Photogrammetry and Remote Sensing

2009 : GNSS Leader to Watch - Innovation Award : GPS World journal

Publications

Infoscience publications

Teaching & PhD

Teaching

Environmental Sciences and Engineering

Courses

Inference for large-scale time series with application to sensor fusion

Large-scale time series analysis is performed by a new statistical tool that is superior to other estimators of complex state-space models. The identified stochastic dependences can be used for sensor fusion by Bayesian (e.g. Kalman) filtering or for studying changes in natural/biological phenomena.

Estimation methods

The students treat observations affected by uncertainty in a rigorous manner. They master the main methods to adjust measurements and to estimate parameters. They apply specific models to real-world problems encountered in various experimental sciences.

Sensing and spatial modeling for earth observation

The course is organized in three main parts. 1. 3D reconstruction from images
  • Processes of image creation
  • Image matching, orientation and camera calibration
  • Construction of digital elevation models (DEM) and orthophotos
2. Environmental monitoring with machine learning
  • Extracting features from elevation or image data
  • Pred

Robotics practicals

The goal of this lab series is to practice the various theoretical frameworks acquired in the courses on a variety of robots, ranging from industrial robots to autonomous mobile robots, to robotic devices, all the way to interactive robots.