Benedikt Soja: Catalogue data in Spring Semester 2021 |
| Name | Prof. Dr. Benedikt Soja |
| Field | Space Geodesy |
| benedikt.soja@geod.baug.ethz.ch | |
| URL | http://twitter.com/b_soja |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Assistant Professor (Tenure Track) |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 101-0522-10L | Doctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering  Number of participants limited to 21. | 1 credit | 2S | B. Soja, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, M. J. Van Strien | |
| Abstract | Current research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to provide a platform where research challenges can be discussed, and also to practice scientific presentations. | ||||
| Learning objective | - learn about discipline-specific methods and applications of data science in neighbouring fields - network people and methodological expertise across disciplines - establish links and discuss connections, common challenges and disciplinespecific differences - practice presentation and discussion of technical content to a broader, less specialised scientific audience | ||||
| Content | Current research at D-BAUG will be presented and discussed. | ||||
| Prerequisites / Notice | This doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar. Participants are expected to possess elementary skills in statistics, data science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects. | ||||
| 101-0523-11L | Frontiers in Machine Learning Applied to Civil, Env. and Geospatial Engineering (FS21) Number of participants limited to 21. | 1 credit | 2S | M. Lukovic, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, K. Schindler, B. Soja, M. J. Van Strien | |
| Abstract | This doctoral seminar organised by the D-BAUG platform on data science and machine learning aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms). | ||||
| Learning objective | Students will • Critically read scientific papers on the recent developments in machine learning • Put the research in context • Present the contributions • Discuss the validity of the scientific approach • Evaluate the underlying assumptions • Evaluate the transferability/adpatability of the proposed approaches to own research • (Optionally) implement the proposed approaches. | ||||
| Content | With the increasing amount of data collected in various domains, the importance of data science in many disciplines, such as infrastructure monitoring and management, transportation, spatial planning, structural and environmental engineering, has been increasing. The field is constantly developing further with numerous advances, extensions and modifications. The course aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms). Each student will select a paper that is relevant for his/her research and present its content in the seminar, putting it into context, analyzing the assumptions, the transferability and generalizability of the proposed approaches. The students will also link the research content of the selected paper to the own research, evaluating the potential of transferring or adapting it. If possible and applicable, the students will also implement the adapted algorithms The students will work in groups of three students, where each of the three students will be reading each other’s selected papers and providing feedback to each other. | ||||
| Prerequisites / Notice | This doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar. Participants are expected to possess elementary skills in statistics, data science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects. | ||||
| 103-0178-00L | Geodetic Earth Monitoring | 4 credits | 3G | M. Rothacher, B. Soja | |
| Abstract | The three pillars of geodesy, i.e. the geometry, rotation and gravity field of the Earth contribute to Earth system monitoring and will be considered here. 1) Earth rotation: theory, estimation and interpretation; 2) Gravity field: satellite missions, theory, estimation and interpretation; 3) Geodynamics (geometry): plate tectonics, earthquake cycle, isostasy and uplift rates. | ||||
| Learning objective | Understand the basics of Earth rotation and gravity field theory, with what type of methods they are determined and what they contribute to monitoring the Earth system. Get familiar with the major geodynamic processes within the crust and mantle and how they are being observed and monitored. | ||||
| Content | Part 1: Earth rotation - Kinematics of a solid body - Dynamic Eulerian equations of Earth rotation - Kinematic Eulerian equations of Earth rotation - Free rotation of the flattened Earth - Influence of Sun and Moon, Precession, Nutation - Earth as an elastic body - Determination of Earth rotation parameters - Mass distribution and mass transport affecting Earth rotation Part 2: Gravity field - Satellite missions - Gravity field determination from satellite data - Geoid computation from terrestrial data - Combination of satellite and terrestrial gravity fields - Precision of geoid computations - Mass distribution and transport affecting the Earth gravity field Part 3: Geodynamics: - Plate tectonics theory: including ocean bottom floor magnetism Curie temperature, age of the ocean bottom floor - Notions on crust material (oceanic/continental) - Concepts of mantle plumes, mantle convection and mantle flow and evidences supporting them - Earthquake cycle: elastic rebound theory, strain and stress measurements and measurements in the field during inter-, co- and post-seismic periods - Isostasy and strength models - Surface uplift rate applied to continental crust, volcanism, eroded areas. | ||||
| Lecture notes | A script and slides will be made available | ||||
| Literature | Beutler G., Methods of Celestial Mechanics. II: Application to Planetary System, Geodynamics and Satellite Geodesy, Springer, ISBN 3-540-40750-2, 2005. Hofmann-Wellenhof B. and Moritz H., Physical Geodesy, Springer, ISBN 13-978-3-211-33544-4, 2005/2006. Fowler C.M.R., The Solid Earth: An Introduction to Global Geophysics, Cambridge Univ. Press, ISBN 0-521-38590-3, 2005. | ||||
| Prerequisites / Notice | Recommended: Basics of Higher Geodesy Of advantage: Basics of Geodetic Earth Observation | ||||