Yuanyuan Yang

Biography

Yuanyuan Yang is an Affiliated Student Researcher at ICSI, where her work applies machine learning to the challenges of subsurface monitoring. She is also a Visiting Scholar at Lawrence Berkeley National Laboratory. She is earning a Ph.D. in Geophysics at King Abdullah University of Science and Technology (KAUST), where she works with Professor Tariq Alkhalifah on advanced seismic methods for characterizing the Earth’s subsurface.

Yang’s research centers on machine learning–enhanced subsurface monitoring, combining data-driven models with the physics of wave propagation to interpret seismic signals more accurately and efficiently. Her work spans several applications critical to the energy transition, including geothermal reservoir development, carbon sequestration and storage, and hydraulic fracturing. A recurring theme is bridging the gap between cutting-edge machine learning and the practical demands of geophysical monitoring in the field, developing methods that are robust to the noise, uncertainty, and limited data of real-world settings and that can be trusted for long-term monitoring of critical infrastructure such as carbon storage sites and geothermal fields.

Beyond her research, Yang serves as Technical Program Chair in the SEG (Society of Exploration Geophysicists) Passive Seismic Committee, helping shape the technical direction of a leading professional organization in the field. Her technical interests include machine learning, deep learning and neural networks, generative AI and foundation models, and AI for climate change, energy, and environmental sustainability. Through her research and professional service, she is committed to advancing innovative seismic techniques that support a more sustainable and energy-secure future.

Publications

Selected Leadership Activities

• Technical Program Chair in SEG Passive Seismic Committee

Areas of Expertise

• Machine Learning (Supervised, Unsupervised, Reinforcement Learning)
• Deep Learning and Neural Networks
• Generative AI and Foundation Models
• AI for Climate Change, Energy, and Environmental Sustainability

ICSI Activity