
Webinar Series
Speed and Structure Expert Q&A Session
Webinar Overview
Date: Jul 2, 2025
Time: 11:00am CDT (4:00pm UTC)
This session is a dedicated Q&A for the Speed and Structure AI Challenge. Anyone participating in the Challenge should join to ask questions and get direct guidance from our expert team. This is a prime opportunity to clarify concepts and refine your approach to seismic velocity inversion with AI.
Registration
Speakers

Ashley Yaner
Computer Vision Engineer and Data Scientist at ThinkOnward
Ashley Yaner is a Computer Vision Engineer and Data Scientist at ThinkOnward, whose background includes a B.Sc. in Geophysical Engineering and an M.Sc. in Geophysics from Colorado School of Mines, working with the Imaging Team at the Center for Wave Phenomena. Her 16-year career began in computational geophysics within the O&G industry. As a geophysical waveform expert, she has a strong understanding of seismic, microseismic, and borehole accelerometer geomechanics. With her M.Sc. thesis on velocity inversion and reverse time migration, she developed a strong foundation for understanding FWI-related concepts, practical geophysical computational techniques, and waveform-based science. She naturally bridged her deep geophysics background with AI, applying geophysical principles to inform complex AI solutions while leveraging AI to enhance understanding across fields like satellite super-resolution and geophysical FWI deep learning. Ashley values innovation, excellence, thinking outside the box, and strong collaboration. Passionate about applying her data science, AI, geophysics, and software development skills, she leverages advanced methodologies such as high-performance computing and creative problem solving to create and deliver impactful solutions in any field, from the energy sector to the medical sector and beyond.

Ashkan Hosseinloo
Lead Data Scientist at ThinkOnward
Ashkan Hosseinloo is the Lead Data Scientist at ThinkOnward, where he leads efforts at the intersection of machine learning, artificial intelligence, and energy solutions. With extensive expertise in system dynamics and control, he leverages modern AI techniques to address pressing challenges in renewables and sustainability. Ashkan's work spans optimizing renewable energy integration, enhancing efficiency in smart grids, and developing innovative data-driven solutions for energy resilience. His background includes a PhD from MIT and postdoctoral research at the MIT Laboratory for Information and Decision Systems. Ashkan is passionate about harnessing interdisciplinary approaches to create impactful, sustainable solutions in the energy sector.