About Me

Dr. Rocío Díaz Martín is an Argentinian mathematician and a Postdoctoral Researcher at Tufts University, where she works with Prof. James Murphy. Her research is grounded in the field of Harmonic Analysis, and she is currently focusing on applications of Optimal Transport Theory to Machine Learning. Her earlier studies were in Abstract Harmonic Analysis, and her PhD thesis was on the spherical Fourier transform on Lie groups. Later, she transitioned to Sampling and Frame Theory, specifically on Dynamical Sampling, a topic she pursued due to its intriguing connection with Control Theory, particularly the observability problem. Currently, she is deeply interested in utilizing Optimal Transport Theory for data and signal analysis, with a particular focus on linearized optimal transport for machine learning applications.

Research interests: Harmonic Analysis, Functional Analysis, Frame Theory, Sampling Theory, Control Theory, Optimal Transport Theory and Applications to Machine Learning.