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Margaret H. Regan, William W. Elliott Assistant Research Professor

Margaret H. Regan

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.

Please note: Margaret has left the Mathematics department at Duke University; some info here might not be up to date.

Contact Info: 
Office Location:  120 Science Drive, Durham, NC 27708
Email Address: send me a message
Web Pages:  http://www.margaretregan.com
https://duke.box.com/s/leywwvcsb61lsthq7yi2emauytu3mhxs

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 Dame2020
Keywords:

Algebraic geometry • Applications in numerical analysis • General applied mathematics • Geometric methods (including applications of algebraic geometry)

Recent Publications   (More Publications)

  1. Rotzoll, M; Regan, MH; Husty, ML; Hayes, MJD, Kinematic geometry of spatial RSSR mechanisms, Mechanism and Machine Theory, vol. 185 (July, 2023) [doi]  [abs]
  2. 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. 409-426 [doi]  [abs]
  3. 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. 12073-12083, IEEE [doi]
  4. Regan, M; Hauenstein, J, Real monodromy action, Applied Mathematics and Computation, vol. 373 (May, 2020), pp. 124983-124983, Elsevier [doi]
  5. Hauenstein, J; Regan, M, Evaluating and differentiating a polynomial using a pseudo-witness set, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12097 (2020), pp. 61-69, Springer-Verlag, ISBN 9783030521998 [doi]

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320