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Tanny Chavez Esparza

Computational Research Scientist
Computing, Photon Science Development

Contact

tanchavez@lbl.govMailstop: 2R0100510-486-6903
Location(s): 002-0232

Biographical Information

Education:

  • Ph.D. in Electrical Engineering, University of Arkansas, Fayetteville, AR, USA
  • M.S. in Electrical Engineering, University of Arkansas, Fayetteville, AR, USA
  • B.S. in Electronics and Telecommunications Engineering, Escuela Superior Politecnica del Litoral, Guayaquil, Ecuador

Past work experience:

  • Postdoc – Computing Group, Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  • Research Assistant – Intelligent Information Sensing, Processing and Transmission Laboratory, University of Arkansas, Fayetteville, AR, USA
  • Teaching Technician – Simulation of Telecommunications Systems Laboratory, Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
  • Teaching Assistant, Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador

Selected Publications

  • T. Chavez, E. J. Roberts, P. H. Zwart, and A. Hexemer, “A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering,” Journal of Applied Crystallography, vol. 55, no. 5, pp. 1277–1288, Oct 2022. doi: 10.1107/S1600576722007105
  • Z. Zhao, T. Chavez, E. A. Holman, G. Hao, A. Green, H. Krishnan, D. McReynolds, R. J. Pandolfi, E. J. Roberts, P. H. Zwart, H. Yanxon, N. Schwarz, S. Sankaranarayanan, S. V. Kalinin, A. Mehta, S. I. Campbell, and A. Hexemer, “MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies,” in 2022 4th Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP), 2022, pp. 10–15. doi: 10.1109/XLOOP56614.2022.00007
  • E. J. Roberts, T. Chavez, A. Hexemer, and P. H. Zwart, “DLSIA: Deep learning for scientific image analysis,” 2023
  • T. Chavez, N. Vohra, K. Bailey, M. El-Shenawee, and J. Wu, “Supervised Bayesian learning for breast cancer detection in terahertz imaging,” Biomedical Signal Processing and Control, vol. 70, p. 102949, 2021. doi: https://doi.org/10.1016/j.bspc.2021.102949
  • T. Chavez, N. Vohra, J. Wu, K. Bailey, and M. El-Shenawee, “Breast cancer detection with low-dimensional ordered orthogonal projection in terahertz imaging,” IEEE Transactions on Terahertz Science and Technology, vol. 10, no. 2, pp. 176–189, 2020. doi: 10.1109/TTHZ.2019.2962116
  • T. Chavez, T. Bowman, J. Wu, K. Bailey, and M. El-Shenawee, “Assessment of terahertz imaging for excised breast cancer tumors with image morphing,” Journal of Infrared, Millimeter, and Terahertz Waves, vol. 39, no. 12, pp. 1283–1302, 2018. doi: 10.1007/s10762-018-0529-8
  • T. Bowman, T. Chavez, K. Khan, J. Wu, A. Chakraborty, N. Rajaram, K. Bailey, and M. O. El-Shenawee, “Pulsed terahertz imaging of breast cancer in freshly excised murine tumors,” Journal of Biomedical Optics, vol. 23, no. 2, pp. 1 – 13, 2018. doi: 10.1117/1.JBO.23.2.026004
  • N. Vohra, T. Chavez, J. R. Troncoso, N. Rajaram, J. Wu, P. N. Coan, T. A. Jackson, K. Bailey, and M. El-Shenawee, “Mammary tumors in Sprague Dawley rats induced by N-ethyl-N-nitrosourea for evaluating terahertz imaging of breast cancer,” Journal of Medical Imaging, vol. 8, no. 2, pp. 1 – 17, 2021. doi: 10.1117/1.JMI.8.2.023504
  • T. Chavez, N. Vohra, J. Wu, M. El-Shenawee, and K. Bailey, “Spatial image segmentation for breast cancer detection in terahertz imaging,” in 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, 2020, pp. 1157–1158. doi: 10.1109/IEEECONF35879.2020.9330445
  • T. Chavez, T. Bowman, J. Wu, M. El-Shenawee, and K. Bailey, “Cancer classification of freshly excised murine tumors with ordered orthogonal projection,” in 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, 2019, pp. 525–526. doi: 10.1109/APUSNCURSINRSM.2019.8888653