People

Assem Kadirova is a sophomore Computer Science student and Research Assistant at Texas Christian University. Her interests focus on developing efficient software systems, optimizing performance, and exploring how computers can process and interpret visual information. Currently, she is developing software tools that help researchers work with large scientific datasets related to solar activity. Her work involves building automated data-processing pipelines, improving software reliability, and making research workflows faster and more efficient.

Duc Le is a junior at Texas Christian University (TCU), pursuing a double major in Computer Science and Mathematics. His research interests include software development, deep learning, computer vision, and explainable artificial intelligence, particularly their applications in scientific research and space weather forecasting. As an undergraduate Research Assistant at TCU, his work focuses on applying deep learning and computer vision techniques to solar image segmentation, analyzing solar phenomena, and improving the detection and characterization of dynamic solar events.

Thu My Banh is a sophomore Computer Science student and Research Assistant at Texas Christian University. Her research interests include machine learning and artificial intelligence, particularly their applications in space weather forecasting and multimodal data analysis. She is also interested in digital behavioral research, research cyberinfrastructure, scientific software engineering and data visualization. Her current research focuses on developing software tools and data pipelines that make large-scale scientific datasets more accessible and easier to analyze.

Tien Nguyen is a junior majoring in Computer Science at Texas Christian University (TCU). His research interests include machine learning, deep learning, and computer vision. As an undergraduate Research Assistant at TCU, his work focuses on applying deep learning and image segmentation techniques to solar imaging data. His research involves data preprocessing, model development, hyperparameter optimization, and performance evaluation to improve the accuracy and generalization of deep learning models for analyzing complex solar phenomena.