I’m Kathryn, and I’m an applied mathematician. I’m currently a Research Scientist at Google. I studied low-level computer vision with Prof. Todd Zickler, and received a Ph.D. in Applied Mathematics (AM) from Harvard SEAS as a Draper Laboratory Fellow in 2021. Prior to that, I received an MS in AM from Harvard in 2016, and a BS in AM from UCLA in 2014. I was an AI Resident at X (formerly Google X) from 2020-2021.

Let’s chat! Email: kathematical@gmail.com

Algebraic Vision Research Cluster, ICERM, 2019
  • Upcoming: Mini-symposium talk at SIAM-MDS in San Diego, Sept 2022.
  • Talk at USC-ICT Seminar, May 2022.
  • Talk at Applied Algebra Seminar at Univ. Wisconsin Madison, March 2022.
  • Talk at SIAM Algebraic Geometry conference, Aug 2021.
  • Talk at Graphics Seminar at Carnegie Mellon, Feb 2021.
  • Talk at Google AI, 3D Understanding group, Nov 2020.
  • CVPR virtual conference, June 2020. Gave an oral presentation on shape from shading, and participated in the Doctoral Consortium.
  • Graphics Colloquium at MIT CSAIL, Oct 2019. Gave a talk on current work on shape from shading.
  • Visitor of the Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany, Summer 2019.
  • Workshop on Real Algebraic Geometry at ICERM, October 2018, presenting a poster titled “Representing the Space of Visual Depth Ambiguities as a Real Affine Variety”.
  • S3PM (Shape, Solid, Structure & Physical Modeling) at UC Berkeley, June 2017. Received a NSF student travel award.
  • ISIT (Information Theory) at RWTH Aachen University in Germany, June 2017, giving a talk titled The Number of Independent Sets in Hexagonal Graphs. Slides from my talk.
  • SIAM-AG (Algebraic Geometry) at Georgia Tech, July 2017, presenting a poster titled Induced Probability Measures on Persistence Diagrams.

Selected Publications

I am most passionate about computer vision, applied algebraic geometry, and machine learning. The following two papers came from my doctoral studies.

  • Heal K, Kulkarni A, Sertöz E. Deep Learning Gauss-Manin Connections; Advances in Applied Clifford Algebras 32, 24. 2022.
  • Heal K, Wang J, Gortler S, Zickler T. A Lighting-Invariant Point Processor for Shading; IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Accepted as Oral Presentation. 2020.

For breadth, during my master’s studies I focused on statistical theory and resource allocation. Here are some of those papers.

  • Ding J, Shahrampour S, Heal K, and Tarokh V. Analysis of Multi-State Autoregressive Models ; IEEE Transactions on Signal Processing. 2018.
  • Deng Z, Ding J, Heal K, Tarokh V. The Number of Independent Sets in Hexagonal Graphs ; 2017 IEEE International Symposium on Information Theory (ISIT). 2017.
  • Magnusson S, Heal K, Enyioha C, Li N, Fischione C, Tarokh V. Convergence of Limited Communications Gradient Methods, in American Control Conference. Boston, MA ; 2016.

Undergraduate research first introduced me to signal processing and computer vision.

  • Gilles J, Heal K. A parameterless scale-space approach to find meaningful modes in histograms – application to image and spectrum segmentation. International Journal of Wavelets, Multiresolution and Information Processing. 2014.