Margaret H. Regan, William W. Elliott Assistant Research Professor
Margaret Hayley Regan grew up in Montclair, New Jersey before attending Swarthmore College in Pennsylvania, where she graduated with a B.A. in Mathematics and Physics with Honors in 2014. At Swarthmore she also received her teaching certificate in secondary education in mathematics and physics. After attending Swarthmore, Regan worked for Cambridge Associates, a finance company in Boston, MA for a short time before entering graduate school in applied mathematics. Regan completed her PhD at the University of Notre Dame in 2020 with a dissertation entitled "Parameterized Polynomial Systems and Their Applications." The research associated with her PhD focused on numerical algebraic geometry in applications such as kinematics and computer vision. Regan is currently a William E. Elliott Assistant Research Professor at Duke.
Her expertise is in solving polynomial systems using numerical algebraic geometry with a focus on real solution sets that are applicable for real world scenarios in kinematics, computer vision, and biology.  Contact Info:
Teaching (Fall 2022):
 MATH 221.01, LINEAR ALGEBRA & APPLICA
Synopsis
 Physics 119, TuTh 01:45 PM03:00 PM
 MATH 221.02, LINEAR ALGEBRA & APPLICA
Synopsis
 Physics 235, TuTh 03:30 PM04:45 PM
 MATH 721.01, LINEAR ALGEBRA & APPLICA
Synopsis
 Physics 119, TuTh 01:45 PM03:00 PM
 MATH 721.02, LINEAR ALGEBRA & APPLICA
Synopsis
 Physics 235, TuTh 03:30 PM04:45 PM
 Office Hours:
 Tuesdays 10:00  11:00 am ET in my office
Tuesdays 3:15  4:15 pm ET in my office Fridays 1:00  2:00 pm ET on Zoom Contact me for Zoom information (or by appointment)
 Education:
Ph.D.  University of Notre Dame  2020 
 Keywords:
Algebraic geometry • Applications in numerical analysis • General applied mathematics • Geometric methods (including applications of algebraic geometry)
 Recent Publications
(More Publications)
 Bernal, EA; Hauenstein, JD; Mehta, D; Regan, MH; Tang, T, Machine learning the real discriminant locus,
Journal of Symbolic Computation, vol. 115
(March, 2023),
pp. 409426 [doi] [abs]
 Fabbri, R; Duff, T; Fan, H; Regan, M; da Costa de Pinho, D; Tsigaridas, E; Wampler, C; Hauenstein, J; Giblin, P; Kimia, B; Leykin, A; Pajdla, T, TRPLP – Trifocal Relative Pose From Lines at Points,
Proceedings of the Ieee/Cvf Conference on Computer Vision and Pattern Recognition (Cvpr)
(June, 2020),
pp. 1207312083, IEEE [doi]
 Regan, M; Hauenstein, J, Real monodromy action,
Applied Mathematics and Computation, vol. 373
(May, 2020),
pp. 124983124983, Elsevier [doi]
 Hauenstein, J; Regan, M, Evaluating and differentiating a polynomial using a pseudowitness set,
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12097
(2020),
pp. 6169, SpringerVerlag, ISBN 9783030521998 [doi]
 Regan, M; Hauenstein, J, Adaptive strategies for solving parameterized systems using homotopy continuation,
Applied Mathematics and Computation, vol. 332
(September, 2018),
pp. 1934, Elsevier [doi]
