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