Invited Talks  (selected)

Big data for small earthquakes: data mining, deep learning, and explainable AI

Earthquake monitoring, Deep learning and Explainable AI

Explainable AI for Seismology: An interpretable convolutional neural network for earthquake detection

Big Data Analysis in Geoscience

Machine Learning in Seismology: A Fireside Chat

Advancing solid Earth geoscience with machine learning

Distributed acoustic sensing (DAS) and big scientific data analysis 

Event detection in big sensor data: Applications in earthquake seismology and beyond

Big data for small earthquakes: Computational challenges in large-scale earthquake detection

Machine learning for data-driven discovery in solid Earth geoscience.

Earthquake monitoring in the age of “big data:” Challenges and opportunities.

Data mining for earthquake detection: Lessons for data-driven geoscience. 

Machine Learning in Seismology: Using AI to Improve Earthquake Monitoring. 

Towards data-driven earthquake detection: Extracting weak seismic signals with locality-sensitive hashing. 

Improving earthquake detection with data mining and machine learning. 

Big data for small earthquakes: a data mining approach to large-scale earthquake detection.  

FAST: Earthquake Detection using Computationally Efficient Similarity Search. 

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Conference Tutorials


Conference Presentations and Posters (selected)

Interpreting and Evaluating Machine Learning-Based Earthquake Monitoring

Towards robust, reliable earthquake detection with deep neural networks

How robust is deep learning-based earthquake detection? Insights from adversarial machine learning

On the Use of Machine Learning for Seismic Event Detection

Data Mining for Earthquake Detection using Computationally Efficient Search for Similar Seismic Signals

Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Detection