Matt O'Shaughnessy

About me

I am a Ph.D. student in the School of Electrical and Computer Engineering and Center for Machine Learning at Georgia Tech. I'm very fortunate to be advised by Mark Davenport and Chris Rozell, and to be supported by the NDSEG Fellowship.

My broad research interests span statistics, signal processing, and machine learning; I am particularly interested in the role of structure and causality in statistical inference. My past and current work involves (1) Bayesian methods for tracking sparse signals; (2) the use of low-dimensional models in theory and algorithms for causal inference; and (3) causality and sparsity in dynamical system identification and control.

Outside of research, I enjoy hiking and cycling, music (especially classical), reading, and cooking. I have an only slightly tenuous claim to an Erdös-Bacon-Sabbath number: my Erdös number is 4; as an extra in a major movie I have a Bacon number of 2; and as a former violist I performed with friends who now record with major artists.

Publications

Journal papers

M. O'Shaughnessy, M. Davenport, and C. Rozell, "Sparse Bayesian learning with dynamic filtering for inference of time-varying sparse signals," Submitted, February 2019.

Conference papers

M. O'Shaughnessy, M. Davenport, and C. Rozell, "Dynamical system implementations of sparse Bayesian learning," Submitted.
G. Canal*, M. O'Shaughnessy* (equal contribution), C. Rozell, and M. Davenport, "Joint estimation of trajectory and dynamics from paired comparisons," Submitted.
M. O'Shaughnessy, M. Davenport, and C. Rozell, "Robust incorporation of signal predictions into the sparse Bayesian learning framework," in Proc. Workshop on Signal Processing with Adaptive Sparse Structured Representations (SPARS), July 2019.
M. O'Shaughnessy and M. Davenport, "Localizing users and items from paired comparisons," in Proc. Int. Workshop on Machine Learning for Signal Processing (MLSP), September 2016.
R. Ortman, D. Carr, R. James, D. Long, M. O'Shaughnessy, C. Valenta, and G. Tuell, "Real-time, mixed-mode computing architecture for waveform-resolved lidar systems with total propagated uncertainty," in Proc. Laser Radar Technology and Applications XXI, May 2016.

Other

Work Experience

Intern, MIT Lincoln Laboratory (Open and Embedded Systems Group), Summer 2016.
Co-op, Georgia Tech Research Institute (Remote Sensing Group), 2014—2016 (three semesters full-time; two semesters part-time).
Intern, Boeing Satellite Systems (DSP Algorithms Group), Summer 2015.

Teaching

From Fall 2013 to Spring 2016, I was an undergraduate teaching assistant for CS 1371, Georgia Tech's introductory computing class for engineers. I taught a weekly recitation section and led a team developing software tools for students.

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