Arman Sabbaghi

Publications

Ohnishi Y., Sabbaghi A. (2022). A Bayesian analysis of two-stage randomized experiments in the presence of interference, treatment nonadherence, and missing outcomes. Bayesian Analysis (accepted).

Geng Z., Sabbaghi A., Bidanda B. (2022). Automated variance modeling for three-dimensional point cloud data via Bayesian neural networks. IISE Transactions (in press). DOI: 10.1080/24725854.2022.2106389.

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.

Geng Z., Sabbaghi A., Bidanda B. (2022). A framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes. International Journal of Production Research (Special issue of ``Editorial Board contributions celebrating the 60th Anniversary of IJPR'') 60:24, 7475-7491.

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 17(7): e0269186.

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) 16:55, 1-29.

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.

Keaton T.J., Sabbaghi A. (2019). Visualizations for interrogations of multi-armed bandits. Stat. 8(1): e247.

Sabbaghi A. (2019). An evaluation of estimation capacity under the conditional main effect parameterization. Journal of Statistical Theory and Practice. 13(4): 1-16.

Kegele C.S., Oliveira J., Magrani T., Ferreira A., Ferreira R., Sabbaghi A., Ferreira A., Brandão A., Raposo N., Polonini H.C. (2019). A randomized trial on the effects of CitrusiM (Citrus sinensis (L.) Osbeck dried extract) on body composition. Clinical Nutrition Experimental. 27: 29-36.

Patel S.H., Yue F., Saw S.K., Foguth R., Cannon J.R., Shannahan J., Kuang S., Sabbaghi A., Caroll C.C. (2019). Advanced glycation end-products suppress mitochondrial function and proliferative capacity of Achilles tendon-derived fibroblasts. Scientific Reports. 9(1): 1-17.

Wang Y., Ferreira R., Wang R., Qiu G., Li G., Qin Y., Ye P.D., Sabbaghi A., Wu W. (2019). Data-driven and probabilistic learning of the process-structure-property relationship in solution-grown tellurene for optimized nanomanufacturing of high-performance nanoelectronics. Nano Energy. 57: 480-491.

Sabbaghi A., Huang Q. (2018). Model transfer across additive manufacturing processes via mean effect equivalence of lurking variables. Annals of Applied Statistics. 12(4): 2409-2429.

Sabbaghi A., Huang Q., Dasgupta T. (2018). Bayesian model building from small samples of disparate data for capturing in-plane deviation in additive manufacturing. Technometrics. 60(4): 532-544.

Patel S.H., Sabbaghi A., Carroll C.C. (2018). Streptozotocin-induced diabetes alters transcription of multiple genes necessary for extracellular matrix remodeling in rat patellar tendon. Connective Tissue Research. 59(5): 447-457.

Huang Q., Zhang J., Sabbaghi A., Dasgupta T. (2015). Optimal offline compensation of shape shrinkage for 3D printing processes. IIE Transactions on Quality and Reliability Engineering. 47(5): 431-444.

Sabbaghi A., Dasgupta T., Huang Q., Zhang J. (2014). Inference for deformation and interference in 3D printing. Annals of Applied Statistics. 8(3): 1395-1415.

Sabbaghi A., Rubin D.B. (2014). Comments on the Neyman-Fisher controversy and its consequences. Statistical Science. 29(2): 267-284. (supplement)

Sabbaghi A., Dasgupta T., Wu C.F.J. (2014). Indicator functions and the algebra of the linear-quadratic parameterization. Biometrika. 101(2): 351-363.

DeMeyer L., Greve L., Sabbaghi A., Wang J. (2010). The zero-divisor graph associated to a semigroup. Communications in Algebra. 38(9): 3370-3391.

Refereed Book Chapter

Sabbaghi A. (2019). Modeling in-plane deviations of shapes to come based on prior deviation features in additive manufacturing. In: Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, July 24-28, 2019, Washington D.C., USA, ed. M. Di Nicolantonio, E. Rossi, and T. Alexander. Springer International Publishing (Winner of the AHFE 2019 Best Paper Award).

Reviews of Manuscripts Published in Mathematical Reviews

MR4357709. Wang C., Mee R.W. Saturated and supersaturated order-of-addition designs. J. Statist. Plann. Inference 219 (2022), 204--215.

MR4257528. Hazlett C. Kernel balancing: a flexible non-parametric weighting procedure for estimating causal effects. (English summary) Statist. Sinica 30 (2020), No. 3, 1155--1189.

Refereed Conference Proceedings

Sabbaghi A., Huang Q. (2016). Predictive model building across different process conditions and shapes in 3D printing. In: Twelfth Annual IEEE International Conference on Automation Science and Engineering, August 2016.

Sabbaghi A., Huang Q., Dasgupta T. (2015). Bayesian additive modeling for quality control of 3D printed products. In: Eleventh Annual IEEE International Conference on Automation Science and Engineering, August 2015.

Xu L., Huang Q., Sabbaghi A., Dasgupta T. (2013). Shape deviation modeling for dimensional quality control in additive manufacturing. In: ASME 2013 International Mechanical Engineering Congress & Exposition, November 2013.