Xinming Wu, USTC (University of Science and Technology of China)

Topic: Deep Learning For Interpreting Seismic Structures and Building Subsurface Models

Xinming Wu is a professor of Geophysics at USTC (University of Science and Technology of China), where he is leading the Computational Interpretation Group (CIG). Xinming received a Ph.D. (2016) in Geophysics from the Colorado School of Mines.From 2016 to 2019, he was a postdoctoral fellow working with Dr. Sergey Fomel at Bureau of Economic Geology, The University of Texas at Austin. He received the SEG's awards for: J. Clarence Karcher Award, 2020; Honorary Lecturer, South & East Asia, 2020;  Best Paper in Geophysics with Dave Hale in 2016;  Honorable Mention for Best Paper presented at the 2018 SEG Annual Convention with Sergey Fomel in 2018.

Lindsey Allen, Microsoft

Lindsey is Senior Director of Data Science in Azure R&D, focusing on applied AI (Deep Learning and Traditional ML) on real world use cases across industry segments and geographical regions. Lindsey started working at Microsoft 26 years ago, held many roles including GPM for Azure SQL Database, SQL Server, and SQL core engine (SE, RE, EE, In-Memory OLTP, Columnstore), Security Compliance for Azure Data Service & SQL Server, Lead Architect in MCS, Manager of SQLCAT & Azure DataCAT; Throughout the 26 years, Lindsey extensively worked with many strategic customers worldwide. Lindsey worked on a very broad spectrum of solution patterns, end to end architecture, optimization and operation – NLP/NLG/NLU, AGI, Image processing, RPA, IoT connected cars, connected hospitals, mission critical transactional and data warehouse systems for different industrial segments, real time fraud detection, and first party system optimization like Sharepoint/SPO, Dynamics (AX, NV, GP) and TFS.

Jesper Dramsch, ECMWF 

Topic: What AI in Geophysics Can Learn from Self-Driving Cars?

Jesper Dramsch works at the intersection of machine learning and physical data. Currently working as a machine learning engineer on applied exploratory problems, e.g. satellites and Lidar imaging on trains, they have just defended a PhD in machine learning for geoscience. During the PhD, Jesper wrote multiple publications and often presented at workshops and conferences. Additionally, they create notebooks on Kaggle, reaching rank 81 worldwide. Moreover, they worked as consultant machine learning and Python educator in places such as Shell and the UK government.

Kenton Prindle, Studio X  

Topic: How AI is Changing the Future of Work in Exploration Through Knowledge Capture, Data Automation, Augmented Reality and AI Accessibility

Kenton is currently head of Data Science and Geoscience at Studio X. Prior to that, Kenton was also a Machine Learning Geophysical Engineer at Google and Google X, a subject matter expert for Oil and Gas (Geophysics), and Machine Learning for Geophysics and HPC/CloudComputing. In these role, he is responsible for building/deploying and leading a team of engineers to build engineering solutions for Google Cloud Platform centered around geophysics and machine learning/AI for customers. He strives to apply current and upcoming AI/ML technologies to materialize proofs of concept and drive long-term transformations. At Google X Kenton led a team of data scientists trying to solve moonshots focused on understanding the global subsurface.