Planetary Imaging & Earth Hazards

Dr. Ziqi Zhang, the first PhD graduate of the Olugboji Earth Imaging Lab, is heading to the Australian National University (ANU) to join an international Laureate team led by Professor Hrvoje Tkalčić investigating the hidden interiors of planets. Building on

Here, Sayan shares his work using AI to unlock the secrets of ocean sound. His new paper introduces Spec2VEC, an AI technique for extracting information from planetary signals. He’s now applying it to detect submarine volcanic eruptions along the Titan

We are incredibly proud to celebrate our graduating Class of 2026:  Dr. Jean-Joel Legre and Dr. Carr! Both are moving on to exciting careers at the frontiers of earth science: one heading into the energy industry, and the other joining

At EGU, Dr. Olugboji and Swar presented how global nuclear-monitoring hydrophones reveal the ocean’s “natural acoustic amplifiers.” By mapping seafloor coupling, we transform submarine earthquakes and volcanoes into virtual active sources. This calibration atlas is a game-changer, providing essential baselines

The Olugboji Lab rocked Pasadena 2026! We showcased AkiNET, Spec2Vec, CRISP-RF, and ArrayBayes—our explainable AI toolkit for extracting signals from noise, monitoring submarine volcanoes, and probing the deep mantle. From imaging African rifting to engaging with global experts, it was

We are thrilled to announce that our second-year Ph.D. student, Sayan Swar, has received the UofR GEPA travel award  and SSA Global travel grant to support his conference travel to Pasadena, California. He will be presenting his frontier work at

The Olugboji Planetary Imaging Lab has secured a competitive allocation on the upcoming Empire AI Beta supercomputer. Our proposal, “Planetary Imaging with AI,” was awarded 3,000 service units on the cutting-edge DGX GB200 NVL72 SuperPOD architecture. Starting March 2026, this

We are thrilled to announce that our first-year Ph.D. student, Molly Maenner, has been selected for a highly competitive research school in Bayrischzell, Germany, focused on advanced cryo-seismology. This workshop perfectly aligns with Molly’s interdisciplinary research, which sits at the

We are proud to announce that Canberk Eckmeki has successfully defended his dissertation: “Uncertainty quantification for learning based computational imaging.” Co-advised by myself and Professors Mujdat and Mateos (ECE), Canberk’s defense on December 5 marks the culmination of a successful

Huge congratulations to former lab member Siyu Xue (now PhD at Cornell) on her new paper! AkiNet: A Physics-Informed AI for Wave Extraction from Noise is now published in JGR: Machine Learning and Computation. This work advances seismic imaging by