Silvia Cernea Clark

A team of researchers at Rice and Baylor College of Medicine has developed a new strategy for identifying hazardous pollutants in soil ⎯ even ones that have never been isolated or studied in a lab.

Rice researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially enabling faster and more precise medical diagnoses and sample analysis.

Rice scientists and collaborators at Baylor College of Medicine have demonstrated a new method for detecting the presence of dangerous chemicals from tobacco smoke in human placentas with unprecedented speed and precision.

A team of researchers at Rice is working on solutions to make AI models less expensive and more accessible, customizable and environmentally friendly.

A team of Rice engineers and partners won a $1.5 million NSF award for a project that leverages responsible AI to enhance emergency response to coastal compound hazard events.

Rice researchers have found that training successive generations of generative artificial intelligence models on synthetic data gives rise to self-consuming feedback loops.

Rice engineers have developed two new graph-based computational tools for tracking genomic variation within microbiomes.

A team of Rice researchers has developed a tool that is better at integrating single-cell DNA and RNA data than more recent, state-of-the-art technologies. The findings could lead to better early stage cancer detection.

Rice’s Santiago Segarra and Ashutosh Sabharwal have won a grant from the DEVCOM Army Research Laboratory to develop a machine learning framework that improves military communication networks’ decision-making processes. The research could also help

A team of Rice University engineers has launched open-source software that constructs and uses personalized computer models of how individual patients move to optimize treatments for neurologic and orthopedic mobility impairments.

Rice scientist spots clue in discarded data that sets research on the right track.