EU

Meet the Team

Albert Reed, Ph.D.

Senior R&D Engineer

Computer Vision

Kitware Remote

Ph.D in Electrical Engineering
Arizona State University

B.S. in Electrical Engineering
New Mexico Institute of Mining and Technology

Albert Reed

Albert Reed is a Senior R&D Engineer working remotely on Kitware’s Computer Vision Team. He is focused on machine learning tasks where he’ll be collaborating with researchers and training algorithms to solve challenging problems.

Albert earned his B.S. in Electrical Engineering from New Mexico Institute of Mining and Technology in May 2014. He earned his Ph.D. in Electrical Engineering from Arizona State University in May 2023. His field of study was computational imaging. In April 2020, he was awarded the Department of Defense’s (DoD’s) National Defense Science and Engineering Graduate Fellowship (NDSEG) Fellowship. In May 2023, his Ph.D. dissertation was awarded the Dean’s Dissertation Award from Arizona State University.

While working towards his Ph.D, he had internships at Amazon Alexa where he worked on using large language models for data retrieval and ranking. He also interned with Lawrence Livermore National Labs where he designed neural-network based algorithms for computed tomography imaging. He also interned for The Applied Research Labs at Penn State where he designed new types of synthetic aperture sonar imaging algorithms.

Publications

  1. A. Reed, T. Blanford, D. Brown, and S. Jayasuriya, "SINR: Deconvolving Circular SAS Images Using Implicit Neural Representations," IEEE Journal of Selected Topics in Signal Processing, vol. 17, no. 2, pp. 458-472, Mar. 2023. [URL]
  2. A. Reed, J. Kim, T. Blanford, A. Pediredla, D. Brown, and S. Jayasuriya, "Neural Volumetric Reconstruction for Coherent Synthetic Aperture Sonar," ACM Transactions on Graphics, vol. 42, no. 4, pp. 1-20, Aug. 2023. [URL]
  3. K. Mohan, K. Champley, A. Reed, S. Glenn, and H. Martz, "Iterative reconstruction of the electron density and effective atomic number using a non-linear forward model," in Anomaly Detection and Imaging with X-Rays (ADIX) VII, 2022. [URL]
  4. G. Vetaw, A. Reed, D. Brown, and S. Jayasuriya, "A 3D GAN Architecture for Volumetric Synthetic Aperture Sonar," in OCEANS 2021: San Diego – Porto, 2021. [URL]
  5. A. Reed, T. Blanford, D. Brown, and S. Jayasuriya, "Implicit Neural Representations for Deconvolving SAS Images," in OCEANS 2021: San Diego – Porto, 2021. [URL]
  6. N. Li, S. Thapa, C. Whyte, A. Reed, S. Jayasuriya, and J. Ye, "Unsupervised Non-Rigid Image Distortion Removal via Grid Deformation," in 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021. [URL]
  7. A. Reed, H. Kim, R. Anirudh, K. Mohan, K. Champley, J. Kang, and S. Jayasuriya, "Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields," in Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021. [URL]
  8. A. Reed, I. Gerg, J. McKay, D. Brown, D. Williamsk, and S. Jayasuriya, "Coupling Rendering and Generative Adversarial Networks for Artificial SAS Image Generation," in OCEANS 2019 MTS/IEEE SEATTLE, 2019. [URL]

Bibliography generated 2023-12-06-04:04:15 (6886)