Julia Lindberg
Scholar

Julia Lindberg

Google Scholar ID: xrsmw6cAAAAJ
University of Texas-Austin
applied algebraoptimizationstatisticspower flow
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
192
 
H-index
7
 
i10-index
6
 
Publications
20
 
Co-authors
0
 
Contact
CVOpen ↗
Publications
3 items
Reinforcement Learning for Power-Flow Network Analysis
2026
Cited
0
Efficient Tensor Decomposition via Moment Matrix Extension
2025
Cited
0
Tropical Bisectors and Carlini-Wagner Attacks
2025
Cited
0
Resume
Academic Achievements
  • An up-to-date version of her publications is provided here (link); Her thesis work was awarded the Excellence in Mathematical Research Award and John A. Nohel Prize for an outstanding thesis in applied math.
Research Experience
  • Assistant Professor in the math department at Georgia Tech; Bing Postdoctoral Instructor in the math department at UT Austin working with Joe Kileel; Postdoc of Bernd Sturmfels in the nonlinear algebra group at the Max Planck Institute in Leipzig, Germany.
Education
  • PhD obtained in May 2022 from the University of Wisconsin-Madison, advised by Jose Rodriguez and Bernie Lesieutre. Also worked with Nigel Boston before his retirement.
Background
  • Research interests: Applied algebra and convex geometry. Specifically, using techniques from algebraic geometry to solve problems arising in power engineering, statistics, and optimization.
Miscellany
  • Organizes the MPI Nonlinear Algebra Seminar; Co-organizes viewing events surrounding the virtual ICM meeting; Participates as a member of the technical program committee for ACM e-Energy 2026, speaks at ICMS on 'Computational aspects of algebraic geometry', and more.