CV

Education

• Ph.D in Electrical Engineering, University of Michigan, 2022 (Expected)
• M.S. in Electrical Engineering, University of Michigan, 2019
• B.S. in Electrical Engineering, University of Wyoming, 2017

Work experience

• Graduate Research Assistant (2017-Present)
  • University of Michigan, Ann Arbor, MI
  • Advisor: Laura Balzano
• Summer 2021: Scalable Modeling & Algorithms Graduate Research Intern
  • Sandia National Laboratories
  • Generalized canonical polyadic (GCP) tensor decompositions. Mentored by Eric Phipps.
• Summer 2017: Research Assistant
  • United States Air Force Research Laboratory
  • Filled Elastomer Image Processing
  • Supervisor: Jennifer Price
• Summer 2016: Research Assistant
  • United States Air Force Research Laboratory
  • Polymer Matrix Composite (PMC) Image Processing
  • Supervisor: Michael Uchic

Publications

Gilman, K., Burer, S. & Balzano, L. A Semidefinite Relaxation for Sums of Heterogeneous Quadratics on the Stiefel Manifold. ArXiv Preprint ArXiv:2205.13653. (2022).

Gilman, K., Tarzanagh, D. & Balzano, L. Grassmannian Optimization for Online Tensor Completion and Tracking With the t-SVD. IEEE Transactions On Signal Processing. 70 pp. 2152-2167 (2022).

Hong, D., Gilman, K., Balzano, L. & Fessler, J. HePPCAT: Probabilistic PCA for Data With Heteroscedastic Noise. IEEE Transactions On Signal Processing. 69 pp. 4819-4834 (2021).

Gilman, K. & Balzano, L. Online Tensor Completion and Free Submodule Tracking with the t-SVD. ICASSP 2020-2020 IEEE International Conference On Acoustics, Speech And Signal Processing (ICASSP). pp. 3282-3286 (2020).

Gilman, K. & Balzano, L. Panoramic Video Separation with Online Grassmannian Robust Subspace Estimation. Proceedings Of The IEEE/CVF International Conference On Computer Vision Workshops. pp. 0-0 (2019).

Lectures and Posters at Conferences, Workshops and Symposiums

“Algorithms for Nonconvex Probabilistic PCA for Data With Heteroscedastic Noise,” INFORMS Optimization Society Conference 2022, Greenville, South Carolina, March 2022.

“Streaming Probabilistic PCA for Missing Data with Heteroscedastic Noise”, Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS) 2022, University of Michigan, March 2022.

“HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise,” 2021 Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS), University of Michigan, February 2021.

“Grassmannian Optimization for Online Tensor Completion and Tracking in the t-SVD Algebra,” Institute of Advanced Studies Workshop on Missing data, 2020.

“Online Tensor Completion and Free Submodule Tracking with the t-SVD,” 2020 International Conference on Acoustics, Speech, and Signal Processing. Barcelona, Spain. 2020.

“Panoramic Video Separation with Online Grassmannian Robust Subspace Estimation,” International Conference on Computer Vision 2019 Workshop on Robust Subspace Learning and Applications in Computer Vision. Seoul, South Korea. 2019.

Teaching

Fall 2019 and 2020 EECS 505, Computational Data Science and Machine Learning, Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI.