SAN ANTONIO — September 16, 2025 — Southwest Research Institute (SwRI) and The University of Texas at San Antonio (UT San Antonio) are collaborating to create a detection system to identify pre-ignition in hydrogen internal combustion engines (H₂-ICE). Researchers will combine machine learning (ML) algorithms and artificial intelligence with onboard sensors to help detect pre-ignitions based on their tell-tale signs.

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. 

A research team has unveiled a non-destructive, highly accurate approach for determining the optimal timing of embryo rescue sampling.

Binghamton University is the only higher learning institution in New York state to make Forbes' Top 25 Public Colleges list. 

A research team introduces Plant-MAE, a self-supervised learning framework designed to automate 3D segmentation of plant organs from point cloud data.

Bioelectrical signals (including EEG, EMG, and ECG signals) have been widely applied in health monitoring, disease treatment, wearable devices, myoelectric exoskeletons, brain-machine interfaces, and other fields. Microneedle electrodes penetrate the stratum corneum, effectively reducing the impedance at the electrode-skin interface without the need for conductive gel, thus meeting the requirements for long-term and high-precision measurements. This review comprehensively summarizes the electrode materials, fabrication methods, performance evaluation, and applications of microneedle electrodes for bioelectrical signal acquisition. It particularly emphasizes the development of materials used to fabricate microneedle electrodes. Furthermore, we discuss the challenges related to material selection and performance testing, and provide insights into the future trends in this field.

Aiming to better equip educators for the growing artificial intelligence (AI) wave, Kennesaw State University Department Chair of Information Technology Shaoen Wu, along with assistant professors Seyedamin Pouriyeh and Chloe “Yixin” Xie, were awarded two grants to help unite educators and lay the foundation for common guidelines in AI education.