I am a doctoral candidate in the Division of Applied
Mathematics at Brown University, and a visiting scholar at the University of Texas at Austin. My primary research interests include applied topology and utilizing methods from topological
data analysis to study dynamical systems, pattern
formation, and biological phenomena. I am also
interested in machine learning applications. This summer, I was a machine learning engineer intern at Spotify.
My research advisor is Björn Sandstede, and I am co-advised by Andrew Blumberg at the University of Texas at Austin. I am a recipient of the National Science Foundation GRFP award.
Beyond research and teaching, I am dedicated to outreach. I served as an officer for the Brown University Student Chapter of SIAM for the last four years, and I am a member of QSIDE . As part of The Math CoOp at Brown, I created a presentation on graph theory for elementary school students. This presentation is based on work by Joel David Hamkins, please feel free to use it!
Room 209, 170 Hope St.
University of Texas:
Room 3.402, P.O.B.
melissa_mcguirl at brown dot edu
News and Events
Dissertation defended! “Quantifying Patterns in Dynamical Systems and Biological Data”
On May 12, 2020 I successfully defended my dissertation titles “Quantifying Patterns in Dynamical Systems and Biological Data.”
Recipient of the
2020 Stella Dafermos Award,
Division of Applied Mathematics, Brown University
I am honored to have received the 2020 Sigma Xi Award from the Division of Applied Mathematics. The prize goes to one or more outstanding graduate students who also share Stella’s goals.
Selected Past Events
- Spring 2019: I am honored to have received the 2019 Sigma Xi Award for excellence in research and high potential for future contributions from the Division of Applied Mathematics at Brown University.
- Spring 2019: I am honored to have received the 2019 SIAM Student Chapter Certificate of Recognition for outstanding service and contributions to the Brown Student Chapter of SIAM.
- Summer 2019: I was a machine learning engineer intern at Spotify during the summer of 2019.
- August 5-9, 2019: I was invited to be a research group facilitator for the ICERM conference on Applied Mathematical Modeling with Topological Techniques. My group researched modeling gun violence with topological techniques, and we are continuing this work.
- July 8-12, 2019: Invited to present on "Quantifying Zebrafish Patterns: A Study of Pattern Variability and Robustness" in the minisymposium on "Topological data analysis of dynamical systems" at the Equadiff conference in Leiden.
- May 19-23, 2019: Invited to present on "A Topological Study of Spatio-Temporal Pattern Formation" in the mini-symposium on Topological Data Analysis and Applications in Dynamical Systems at the SIAM Conference on Applications of Dynamical Systems.
- April 1, 2019: Paper titled Fast Estimation of Recombination Rates Using Topological Data Analysis in collaboration with Devon P. Humphreys, Michael Miyagi, and Andrew Blumberg has been published in GENETICS. The paper presents a fast model for predicting recombination rates using topological statistics.
- January 7-11, 2019: Invited to participate in Collaborate@ICERM: Topological Data Analysis and Music Information Retrieval.
- December 3, 2018: Presented "Hierarchical Clustering of Gene-Level Association Statistics Reveals Differential Genetic Architecture Between Immunological and Metabolic Phenotypes in the UK Biobank" at the Women in Machine Learning Workshop poster session in Montreal.
- November 8, 2018: Invited to speak on "A Topological Study of Spatio-Temporal Pattern Formation" at the Texas State University Topology Seminar.
- October 23-24, 2018: Presented a poster on "Thresholded Hierarchical Clustering of Gene-Level Association Statistics" at the second TRIPODS PI workshop in Santa Cruz, CA.
- October 5-7, 2018: Invited to speak on "A Topological Approach to Spatio-temporal Pattern Formation" at the Applied Topology Mini Symposium at the SIAM Central States Section Meeting in Norman, Oklahoma.
- September 23-27, 2018: Paper titled SE and SnL Diagrams: Flexible Data Structures for MIR, in collaboration with Katherine Kinnaird, Claire Savard, and Erin Bugbee, was published in the Proceedings of the 19th ISMIR Conference.
- August 13-15, 2018: Invited to participate in the Tutorial on Multiparameter Persistence, Computation, and Applications at the IMA.
- August 6-10, 2018: Co-organized the TRIPODS Summer Bootcamp: Topology and Machine Learning at ICERM. The workshop consisted of a hands-on tutorial and mini research conference.
- Summer 2018: Instructor of APMA 0350: Applied Ordiniary Differential Equations at Brown University for the 2018 summer sesstion.
- Fall 2017-2018: Co-organized the Applied Topology and Geometry seminar at Brown University. (Seminar webpage.)
- Fall 2017-Spring 2018: Co-organized "Are we putting too much faith in math?," a Horizons reading group that focused on investigating and reflecting on the social impact of mathematical research. We are generously funded by the Women and Mathematics Program at IAS.
- April 12, 2018: Spoke on "Topological Data Analysis and Applications" at the Spring 2018 Math Slam at Brown University.
- April 7, 2018: Spoke on "A Topological Analysis of Model Sensitivity and Classification for Pattern Formation on Zebrafish" at the 2018 Advancing Women's Impact in Mathematics Symposium (AWIMS) at WPI.
- December 4, 2017: Presented a poster on "Classifying Zebrafish Stripe Patterns using TDA and Multi-class SVMs" at the Women in Machine Learning Workshop in Long Beach, CA.
- November 30, 2017: Spoke on "A Topological Analysis of Model Sensitivity for Pattern Formation on Zebrafish" at the 2017 Brown-BU Dynamics and PDE seminar at Boston University.
- October 23, 2017: Spoke on "A Topological Analysis of Model Sensitivity for Pattern Formation on Zebrafish" at the Brown University Applied Math Graduate Seminar.
- Summer 2017: Teaching Assistant for Summer@ICERM: Topological Data Analysis, an 8-week research experience for undergraduates that brought together students from around the world to learn about TDA.