Fall 22 | Syllabus
Class description: This class focuses on how science – specifically active tectonic processes - is depicted in disaster movies. We discuss fundamental earth science concepts such as plate tectonics and mantle convection, and how large-scale processes lead to local phenomena such as volcanic eruptions, tsunamis and earthquakes. Subjects will include theory of plate tectonics, earthquakes and faulting, volcanic eruptions, plate boundary processes, mantle convection, hot spots, surface deformation, elastic rebound, tsunamis, intraplate earthquakes and seismic hazard along the New Madrid seismic zone. These topics will be introduced through the lens of Hollywood movies. Disaster movies have a long tradition in Hollywood film making; and although special effects significantly improved much of the science remains flawed.
Fall 21 | Syllabus
Class description: Artificial intelligence and machine learning (ML) - driven by the availability of exceedingly large amounts of data - have led to a rapid acceleration in tech and science breakthroughs. ML is not only useful for google-searches and movie selections on Netflix but also for fault mapping, earthquake detection, phase picking, elastic stress calculations, failure predictions, aftershock forecasting and much more. The goal of this class is to expose students to the newest developments in machine learning and applications in engineering and science. We will discuss basics of unsupervised and supervised learning, classification and regression problems, model training and performance evaluation as well as ensemble and deep learning.
Fall 20 / Spring 23 | Syllabus
Topics covered: brittle fracture, fracture mechanics, friction, seismic cycle, mechanics of faulting, earthquake statistics and prediction, crustal hydrology and fluid flow, induced seismicity
Fall 2020/21/22 | Syllabus
Topics covered: Intro to MATLAB and Python, data I/O, multivariate statistics, earthquake catalog analysis, time series and waveform analysis with obspy, spectral analysis of fault roughness, pressure recession analysis and model fitting, regression models, predictive modeling with artificial neural networks
Spring 2020/22 | Syllabus
Topics covered: IDEs, functions and modules, root finding, optimization problems, numerical integration, ODEs, PDEs, introduction to machine learning
Online | Fall 2018, Summer 2019 | Syllabus
Topics covered: plate tectonics, faults and friction, seismic waves, strong ground motions, seismic hazard, earthquake probabilities, tsunamis, induced earthquakes, early warning and earthquake preparedness, Cascadia Subduction Zone and San Andreas fault earthquakes
Spring 2019 | Syllabus
Topics covered: data I/O, plotting and animations, derivatives and numerical integration, solving systems of equations, statistical analysis, least-squares and MLE, ODEs and PDEs, intro to machine learning classification with MLPs
Sping 2017 | Syllabus
Topics covered: Object oriented programming, Python modules, Data handling, matlab
Spring 2016, Summer 2017 | Course Summary
Topics covered: state-of-the-art methods for the analysis of micro-seismicity, Geomechanical simulation of hydraulic fracturing and microseismicity, Geomechanical modeling and analysis of pore pressure and fault stress, Hands-on problem-sets using real micro-seismicity data