Tiexing Wang

I'm a Project Research Geophysicist in the R&D team at Shearwater GeoServices in the United Kingdom. I hold a Ph.D. in applied physics and have almost six years of experience applying scientific machine learning, generative AI, and signal processing to real-world challenges in subsurface imaging.

My research focuses on bridging physics-based modeling with machine learning, particularly in developing self-supervised, physics-informed frameworks. These frameworks aim to serve as robust solvers for inverse problems in seismic data processing and inversion. My work supports applications such as traditional marine seismic acquisition and offshore windfarm site assessments.

At Shearwater GeoServices, I lead and support research efforts in self-supervised, physics-informed learning, generative AI for seismic data reconstruction, and marine vibroseis technologies. These initiatives are part of our broader mission to advance seismic imaging and acquisition technologies. My long-term goal is to build a physics-aware deep learning framework that's scientifically rigorous and accelerates innovation across the energy sector.

Beyond technical research, I'm actively involved in the geoscience community. I currently serve as Vice President of the EAGE Local Chapter London and as a committee member of the EAGE Young Professionals. Through these roles, I help promote energy innovation, tackle scientific challenges during the energy transition, and support the next generation of geoscientists.

I'm always open to new ideas, interdisciplinary collaboration, and partnerships at the intersection of geophysics, AI, and sustainability. If you'd like to connect, chat over coffee, or discuss potential collaborations, feel free to reach out through the email and LinkedIn buttons below.