USC’s Space Engineering Research Center is giving students hands-on experience designing, building and operating spacecraft, highlighted by the successful launch of the student-built MAVERIC CubeSat, which is testing autonomous spacecraft technologies and AI applications in orbit. Research professor David Barnhart said the program’s close partnerships with industry and faculty provide students with real flight experience and professional engineering training, creating a strong pipeline to aerospace employers such as SpaceX. SERC is also advancing AI-enabled spacecraft by using satellite data to train reinforcement learning models on the ground and upload improved control algorithms, while emphasizing that autonomous systems will work alongside—not replace—human operators. Looking ahead, the center is pursuing ambitious projects including a kilometer-wide virtual space telescope, autonomous tentacle-like robotic systems for space operations, and new NASA Astrobee collaborations.

Researchers in China propose a physics-data co-driven deep neural network. By embedding coupled mode theory into a data-driven deep neural network, this framework achieves rapid and precise prediction of physical parameters in complex coupled resonant systems, deciphering their underlying physical properties in a unified way. As a proof-of-principle experiment, the precise measurement of nanometer-scale displacements is demonstrated. This study not only provides a new method for analyzing the underlying physical mechanisms of coupled resonant systems but also opens up a new avenue for high-precision sensing applications.

Insilico Medicine (“Insilico”; HKEX: 3696), a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, today announced the nomination of ISM9077, the AI-empowered, potential first-in-class Target Y inhibitor with pipeline-in-a-drug potential, as a Preclinical Candidate (PCC) for the treatment of ocular diseases including dry Age-Related Macular Degeneration (dry AMD), uveitis, and dry eye disease. As the 32nd PCC nominated since 2021, ISM9077 boasts potent inhibition across species, excellent exposure and permeability traits, and a favorable safety profile in preclinical studies.

A new artificial intelligence tool developed by researchers at the FAMU-FSU College of Engineering and Florida State University’s Center for Advanced Power Systems treats the power grid as a connected network to generate more accurate forecasts. The research was published in IEEE Transactions on Network Science and Engineering.