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I am a PhD student in Data Science and Engineering in the Bredesen Center for Interdisciplinary Studies and Graduate Education at the University of Tennessee, Knoxville. For the past two years I have been researching how data science principles may be leveraged for metal additive manufacturing throughout the entire toolchain - modeling and simulations, process optimization, data management, in-situ monitoring, defect detection, and post-build analysis.

Additionally, I am interested in studying and developing policies for data collection, data management and algorithms as these tools become more pervasive and consequential in our society.

My Publications

In Progress

Published

  • W. Halsey, “Application of Data Science and Engineering,” in Encyclopedia of Materials: Metals and Alloys, F. G. Caballero, Ed. Elsevier, 2022, pp. 212–222. https://doi.org/10.1016/B978-0-12-819726-4.00118-6

  • W. Halsey, D. Rose, L. Scime, R. Dehoff, and V. Paquit, “Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning,” Front. Mech. Eng., vol. 7, no. November, pp. 1–14, 2021. https://doi.org/10.3389/fmech.2021.767444

  • A. Plotkowski et al., “A stochastic scan strategy for grain structure control in complex geometries using electron beam powder bed fusion,” Addit. Manuf., vol. 46, p. 102092, 2021. https://doi.org/10.1016/j.addma.2021.102092

  • W. Halsey, J. Ferguson, A. Plotkowski, R. R. Dehoff, and V. Paquit, “Geometry-independent microstructure optimization for electron beam powder bed fusion additive manufacturing,” Addit. Manuf., vol. 35, no. April, p. 101354, Oct. 2020. https://doi.org/10.1016/j.addma.2020.101354

  • M. Kirka et al., “Analysis of Data Streams for Qualification and Certification of Inconel 738LC Airfoils Processed through Electron Beam Melting,” in Structural Integrity of Additive Manufactured Materials & Parts, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959: ASTM International, 2020, pp. 352–366. https://doi.org/10.1520/STP163120190146

  • C. A. Steed, W. Halsey, R. R. Dehoff, S. L. Yoder, V. Paquit, and S. Powers, “Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing,” Comput. Graph., vol. 63, pp. 50–64, Apr. 2017. https://doi.org/10.1016/j.cag.2017.02.005

Patents

  • L. Scime, V. Paquit, D. Goldsby, W. Halsey, C. Joslin, M. Richardson, D. Rose, D. Siddel, “Systems and methods for powder bed additive manufacturing anomaly detection,” US20220134435A1, May 5, 2022. https://patents.google.com/patent/US20220134435A1/en?oq=US20220134435

Technical Reports

  • L. Scime et al., Report on Progress of correlation of in-situ and ex-situ data and the use of artificial intelligence to predict defects, no. September. 2020. https://doi.org/10.2172/1684671

  • L. Scime et al., Development of Monitoring Techniques for Binderjet Additive Manufacturing of Silicon Carbide Structures, no. September. 2020. https://doi.org/10.2172/1671401

Abstracts

  • W. Halsey, C. Steed, R. Dehoff, V. Paquit, and S. Yoder, “Segmented time series visualization tool for additive manufacturing,” in 2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV), 2016, pp. 97–98. https://doi.org/10.1109/LDAV.2016.7874336