Computer Science and Engineering

Dr. Nitesh Saxena is teaming up with the Texas A&M Engineering Experiment Station and Rutgers University to create software that could stop voice-control mischief in manufacturing settings.

Funded by the National Science Foundation, Dr. Tianbao Yang is developing deep learning technologies for medical image classification, making deep models interpretable and the training more efficient by sampling multiple CT scans of a patient for computation.

To correctly diagnose and treat patients with long COVID-19, Dr. Tianbao Yang has received a $3.7 million grant to develop self-supervised deep learning technologies that recognize subtypes of post-COVID lung progression phenotypes.

Researchers from five academic institutions, including Texas A&M University, investigated how ear speaker vibrations and motion sensor data on newer smartphones could compromise caller information security.

A Texas A&M University engineering scientist was awarded a National Science Foundation grant to develop a new method of using hardware to detect malicious software on future computers.

Texas A&M University professor Dr. Shuiwang Ji recently received a National Science Foundation grant to develop an artificial intelligence (AI) method to make predictions from geometric graphs.

Dr. Guni Sharon will conduct research to improve the applicability of machine learning using a grant he received from the National Science Foundation.

Dr. Nima Kalantari was awarded a National Science Foundation Faculty Early Career Development Program grant to research ways to improve the efficiency of computer-generated image rendering.

Dr. Shuiwang Ji is part of an international research project called BigNeuron, which is working to develop a standard framework for fast and accurate automatic neuron reconstruction.

Dr. Nate Veldt and his team have developed a mathematical framework using hypergraphs to measure and define homophily in social group interactions.