close-up of power transmission tower

Dr. Le Xie is working to bring more awareness to the importance of data science integration as it relates to the power grid.

A test tube with water and a light shining on it.

A new National Science Foundation Faculty Early Career Development Award will help Dr. Garrett McKay study the chemical composition of chromophores in dissolved organic matter, which is found in all bodies of water on Earth.

Carlo Fiorina

Dr. Carlo Fiorina was recently awarded the Early Career Reactor Physicist Award by the Reactor Physics Division of the American Nuclear Society.

Yassin Hassan, nuclear engineering

Dr. Yassin Hassan was elected as a corresponding member of the Slovenian Academy of Engineering for his outstanding contributions to the fields of technical sciences.

Denis Johnson, Dr. Djire Abdoulaye and Bright Ugochukwu.

Two Texas A&M University graduate students received Best Poster presentation awards at the Southwest Catalysis Society Symposium out of 39 research presentations and six universities.

Five male and one female student stand on a staircase, smiling at the camera. The female student holds a vial and needle.

A senior capstone team developed a solution to reduce the risk of injections in space for their final project.

Dr. Wenping Wang

Dr. Wenping Wang received the 2023 Distinguished Researcher Award from Shape Modeling International and the 2023 Bézier Award from the Solid Modeling Association for his prominent career and contributions to shape modeling and analysis.

smiling man stands in front of wall featuring Texas A&M logo

Paul Deere received his undergraduate degree in electrical engineering from Texas A&M University in 1992 and used his entrepreneurial spirit to solve a problem for the oil and gas industry.

five students and the director of a competition hold a trophy together

The 2023 South-Southwest Medical Device Make-A-Thon, where teams were asked to create a model to treat a heart problem in 48 hours, was hosted for the first time by the Biomedical Engineering Society at Texas A&M University.

smiling man on left with Texas A&M University Engineering logo on right

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.