“The goal of this project is to develop SmartScript, a novel static code analysis that automatically detects type and semantic inconsistency errors in dynamic scripts, such as shell scripts, Python, LUA, Javascript, etc,” Huang said.
A team of researchers from Texas A&M University, Yale University and the American College of Cardiology investigated how machine learning techniques can be applied in health care to predict the probability of a patient bleeding during or after a coronary procedure.
The Department of Computer Science and Engineering at Texas A&M University had an influential role in this year's Institute of Electrical and Electronics Engineers’ 33rd International Parallel and Distributed Processing Symposium (IPDPS).
