Artificial Intelligence

Dr. Zixiang Xiong received a National Science Foundation grant to gain a fundamental understanding of learned source coding — or data compression that uses machine learning — and to create parameters for the unprecedented tools now available through artificial intelligence.

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.

The Texas A&M RoboMasters Robotics team placed first overall in the 1-versus-1 competition and third overall in the 3-versus-3 competition at the annual RoboMaster North American Regional competition.

Dr. Soaram Kim has developed a remote health and environmental monitoring system, integrated with machine learning, that can be used to detect various viruses, bacteria and cancers.

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

Graduate student Ronald Gatchalian is using machine-learning techniques to predict the physics parameters of a source-driven reactor configuration in a subcritical domain, which can increase safety while reducing experimentation costs and time.

Dr. Suin Yi is working to develop a new computing system known as a memristor computer.

Texas A&M University researchers aim to create a future where data science and artificial intelligence predict, prepare for and respond to natural hazards — from hurricanes to earthquakes — reducing their impact on communities.

Dr. Robin Murphy will lead efforts to innovate and transfer advances in artificial intelligence for disaster management.

Dr. Dileep Kalathil is investigating the robustness, safety and adaptivity of these algorithms so that they can be successful in real-world settings.