2. Paper 'Prediction of the Power of Low-Power Networks Using Inertial Sensors' accepted at IEEE Transactions on Instrumentation and Measurement.
3. Paper 'Locality regularized reconstruction: structured sparsity and Delaunay triangulations' accepted at Sampling Theory, Signal Processing, and Data Analysis.
Research Experience
Currently an Assistant Professor in the Department of Mathematics at Tufts University. In addition to these research areas, he also has a broad interest in applied mathematics, including problems in gas dynamics and shock waves. His research is partially supported by the National Science Foundation (NSF DMS 2304489).
Background
Research interests lie at the intersection of applied mathematics, optimization, and machine learning. Specific areas include distance geometry, matrix completion, compressive sensing, and structured dictionary learning, with applications to structure prediction, signal processing, and machine learning.
Miscellany
Looking for motivated students with a strong mathematical background. Interested students are encouraged to contact via email.