Arman Sabbaghi

Associate Professor in the Area of Applied Statistics
Associate Director, Statistical Consulting Service
Department of Statistics
Purdue University

Visiting Scholar
Department of Statistics
University of California, Berkeley

Contact Information
Purdue University Department of Statistics
150 North University Street
West Lafayette, IN 47907-2066
Office: MATH 204
Phone: (765) 496-0234
Fax: (765) 494-0558

Home | Curriculum Vitæ | Publications | Research | FACAM Blog | Presentations | Teaching | Google Scholar | ResearchGate | LinkedIn


PhD, Statistics, Harvard University, 2014
AM, Statistics, Harvard University, 2011
BS, Mathematics, Purdue University, 2009
BS, Mathematical Statistics, Purdue University, 2009


July 13 - 15, 2021: 2021 Purdue Krannert-Statistics Machine Learning and Causal Inference Boot Camp.

June 18, 2021: Arman Sabbaghi becomes the Program Chair-Elect 2022 of the Physical and Engineering Sciences (est. 1954) SPES/SPQP Section of the American Statistical Association.

December 17, 2020: Arman Sabbaghi becomes an Elected Member of the International Statistical Institute.

June 11, 2020: Purdue Innovators Use Funding to Advance Technologies.

June 11, 2020: Six Purdue innovators advance their technologies through Trask funding.

November 22, 2019: AMapi: An Application Programming Interface for the Control of Additive Manufacturing Systems.

October 2019: Arman Sabbaghi profiled in Purdue University College of Science Insights Magazine.

May 23, 2019: Innovations for the next 150 years were on display, available for licensing at annual Purdue Technology Showcase.

May 21, 2019: Automated machine learning for shape deviation modeling in additive manufacturing systems.

April 8, 2019: Purdue statisticians developing AI/ML methods for additive manufacturing.

February 7, 2019: AI technology addresses parts accuracy, a major manufacturing challenge in 3D printing for $7.3 billion industry.

November 12, 2018: Raquel De Souza Borges Ferreira recognized at the 2018 INFORMS QSR Best Student Paper Competition and the Data Mining Best Theoretical Paper Competition.

April 2015: Quality control for additive manufacturing.

Recent Publications

Keaton T.J., Sabbaghi A. (2022). Dismemberment and design for controlling the risk of regret for the multi-armed bandit. Journal of Statistical Theory and Practice (AISC-2021 Special Collection) (accepted).

Jensen C.L., Rodriguez K.E., MacLean E.L., Wahab A.H.A., Sabbaghi A., O'Haire M.E. (2022). Characterizing veteran and PTSD service dog teams: Exploring potential mechanisms of symptom change and canine predictors of efficacy. PLoS One (accepted).

Geng Z., Sabbaghi A., Bidanda B. (2022). Reconstructing original design: Process planning for reverse engineering. IISE Transactions (in press). DOI: 10.1080/24725854.2022.2040761.

Nieforth L.O., Abdul Wahab A.H., Sabbaghi A., Wadsworth S.M., Foti D., O'Haire M.E. (2022). Quantifying the emotional experiences of partners of veterans with PTSD service dogs using ecological momentary assessment. Complementary Therapies in Clinical Practice 48: 101590.

Zhang Y., Sabbaghi A. (2021). The designed bootstrap for causal inference in Big Observational Data. Journal of Statistical Theory and Practice (Special issue of ``State of the Art in Research on Design and Analysis of Experiments'') 15(4): 1-26.

Odimayomi T., Proctor C.R., Wang Q.E., Sabbaghi A., Peterson K.S., Yu D., Lee J., Shah A.D., Ley C., Noh Y., Smith C., Webster J., Milinkevich K., Lodewyk M., Jenks J., Smith J., Whelton A.J. (2021). Water safety attitudes, risk perception, experiences, and education for households impacted by the 2018 Camp Fire, California. Natural Hazards 108: 947-975.

Sabbaghi A. (2021). An integrative framework for geometric and hidden projections in three-level fractional factorial designs. Journal of Statistical Planning and Inference 215: 257-267. (supplement, R Markdown supplement)

Carroll C.C., Patel S.H., Simmons J., Gorden B.D., Olsen J.F., Chemelewski K., Saw S.K., Hale T.M., Howden R., Sabbaghi A. (2020). The impact of genistein supplementation on tendon functional properties and gene expression in estrogen deficient rats. Journal of Medicinal Food. 23(12): 1266-1274.

Francis J., Sabbaghi A., Shankar R., Ghasri-Khouzani M., Bian L. (2020). Efficient distortion prediction of additively manufactured parts using Bayesian model transfer between material systems. ASME Journal of Manufacturing Science and Engineering. 142(5): 051001 (16 pages).

Ferreira R., Sabbaghi A., Huang Q. (2020). Automated geometric shape deviation modeling for additive manufacturing systems via Bayesian neural networks. IEEE Transactions on Automation Science and Engineering. 17(2): 584-598.

Sabbaghi A. (2020). An algebra for the conditional main effect parameterization. Statistica Sinica. 30(2): 903-924.