Â鶹´«Ã½AV

Marian Temprana Alonso is a Ph.D. candidate in the Knight Foundation School of Computing and Information Sciences at Florida International University and a member of the Π-CoLab research group under the supervision of Dr. Farhad Shirani. Her research interests include information theory, signal processing, and machine learning, with a focus in energy-efficient compression, communications, and sensing. She earned her B.Sc. in Applied Mathematics from Florida International University in 2022. Throughout her Ph.D., she has contributed to projects on energy-efficient task-based quantization, wireless communications with nonlinear analog processing, accuracy and consensus-based sensor fusion, and deep learning-driven multi-modal sensor fusion for CSI compression, leading to publications in Â鶹´«Ã½AV conferences such as ISIT and ITW. Her achievements include receiving a GAANN Fellowship and being part of the winning team for the ISIT 2023 DeepVerse 6G Machine Learning Challenge. Additionally, she has contributed as a research intern at Sandia National Laboratories, working on power grid resilience.