Treangen Lab program using common gene to profile microbial communities featured in Nature Methods journal
While data scientists work to extract and analyze data, software engineers develop systems and applications to meet user and business needs. Learn more from Rice.
Cascante-Bonilla and Ordóñez introduce SimVQA at CVPR 2022
Open-source program IDs synthetic, naturally occurring gene sequences
COVID-19 variants can’t hide from Variabel Monday, Mar. 14, 2022
Treangen Lab develops program to find ‘low-frequency’ variants in sequence data
Adam Zawierucha is developing products and communication skills Friday, Mar. 11, 2022
CS and math major helped create the map app for Rice Public Art.
Three Rice CS faculty researchers win NSF CAREER Awards Wednesday, Mar. 2, 2022
Dautenhahn, Kyrillidis and Yao earn grants, which are among the most competitive and prestigious given by the federal agency.
Vicky Yao wins CAREER Award Tuesday, Mar. 1, 2022
Rice CS assistant professor will build tools to study DNA methylation
Charles Jiang is building AI to empower software engineers Monday, Feb. 28, 2022
Computer science Ph.D. student's research lies at the intersection of machine learning and program synthesis.
AI and Machine Learning Engineers: Roles and Career Pathways Thursday, Feb. 24, 2022
AI & ML engineers are in high demand due to their skills and experience. Learn what these engineers do and how to launch your career in AI or ML.
Data Science vs. Artificial Intelligence & Machine Learning: What’s the Difference? Friday, Feb. 18, 2022
Though data science, artificial intelligence, and machine learning are all connected, there are key differences. Learn more about the distinctions from Rice.
Manansala's episode of The National College Championship aired February 8th
The grant will help further develop their system for creating machine-learning models used in Internet of Things industrial hardware
ML models teach computer programs to write other computer programs Friday, Feb. 11, 2022
Jermaine, Mukherjee and team combine neural machine learning and symbolic methods to write programs without semantic errors