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Prahalada Rao

Associate Professor

Prahalada Rao's scholastic passion is captured in three words: Manufacturing, Sensing, and Analytics. He was awarded the 2018 NSF CAREER grant for sensor-based monitoring and control of additive manufacturing processes. He earned the 2017 Society of Manufacturing Engineers, Yoram Koren Outstanding Young Manufacturing Engineer Award, and the 2019 UNL College of Engineering Research and Creativity Award. He has over 50 peer-reviewed publications in flag-ship journals, such as the ASME Transactions, IEEE Transactions, IIE Transactions. His research has garnered over $ 2 million in funding from federal agencies, including NSF, DOE, and Office of Naval Research.

  • Ph.D., Industrial Engineering; Oklahoma State University (2013)
  • M.S., Industrial Engineering; Oklahoma State University (2006)
  • B.Eng. degree (First Class) Production Engineering, Victoria Jubilee Technical Institute (VJTI), Bombay University, India (2003)
  • Outstanding Reviewer, Society of Manufacturing Engineers, Journal of Manufacturing Systems, 2018
  • Society of Manufacturing Engineers, Outstanding Young Manufacturing Engineer Award, 2017.
  • Finalist: IIE Manufacturing and Design Division Young Investigator Award, 2016
  • Nominated for Institute of Industrial Engineers, Pritsker Doctoral Dissertation Award, 2014
  • Nominated for university-wide Dissertation Award, 2013
  • Finalist, Institute of Industrial Engineers, John L. Imhoff graduate fellowship,2011
  • Outstanding Research Assistant Award, Alpha Pi Mu, Oklahoma State University chapter, 2008
  • NSF CAREER: Smart Additive Manufacturing Fundamental Research in Sensing, Data Science, and Modeling Toward Zero Part Defects
  • NSF PFI TT: PFI-TT: Ultrafast Thermal Simulation of Metal Additive Manufacturing
  • Department of Energy, Office of Science: Understanding the thermal physics and metallurgy of big area additive manufacturing.
  • NSF RII Track-4: Understanding the Fundamental Thermal Physics in Metal Additive Manufacturing and its Influence on Part Microstructure and Distortion.
  • NSF AI Institute: Planning: AI-enabled Secure and Responsive Smart Manufacturing
  • National Science Foundation – CMMI 1752069, CAREER: Smart Additive Manufacturing: Fundamental Research in Sensing, Data Science, and Modeling Toward Zero Part Defects. 2018-2023
  • National Science Foundation – CMMI 1739696, CPS: Medium: Collaborative Research: Cyber-Enabled Online Quality Assurance for Scalable Additive Bio-Manufacturing. 2017-2021
  • National Science Foundation – CMMI 1719388, Biosensor Data Fusion for Real-time Monitoring of Global Neurophysiological Function.  2015 - 2018
  1. B. Bevans, C. Barrett, T. Spears, A. Gaikwad, A. Riensche, Z. Smoqi, H. Halliday, P. Rao. Heterogeneous Sensing and Shape Agnostic Flaw Detection in Laser Powder Bed Fusion Additive Manufacturing. Virtual and Physical Prototyping, Volume 18, Issue 1, April 2023. doi: /10.1080/17452759.2023.2196266.

  2. S. Gerdes, A. Gaikwad, S. Ramesh, I.V. Rivero, A. Tamayol, P. Rao, Monitoring and Control of Biological Additive Manufacturing Using Machine Learning, Journal of Intelligent Manufacturing, In-Press, January 2023. doi: 10.1007/s10845-023-02092-6

  3. B. D. Bevans, A. Ramalho, Z. Smoqi, A. Gaikwad, T. G. Santos, P. Rao, J. P. Oliveira, Monitoring and Flaw Detection during Wire-based Directed Energy Deposition using In-situ Acoustic Sensing and Wavelet Graph Signal Analysis, Materials and Design, Volume 225, January 2023, 111480. doi:10.1016/j.matdes.2022.111480

  4. A. Riensche, P. Carriere, Z. Smoqi, A. Menendez, P. Frigola, S. Kutsaev, A. Araujo, N.G. Matavalam, P. Rao. Application of Hybrid Laser Powder Bed Fusion Additive Manufacturing to Microwave Radio Frequency Quarter Wave Cavity Resonators, Journal of Advanced Manufacturing Technology, 124, pp.619–632, January 2023. doi:10.1007/s00170-022-10547-y

  5. A. Riensche, B. Bevans, Z. Smoqi, R. Yavari, A. Krishnan, J. Gilligan, N. Piercy, K. Cole, P. Rao, Feedforward Control of Thermal History in Laser Powder Bed Fusion: Toward Physics-based Optimization of Processing Parameters, Materials and Design, Volume 224, December 2022, 111351. doi:10.1016/j.matdes.2022.111351.

  6. Z. Smoqi, J. Toddy, H. Halliday, J. E. Shield, and P. Rao. Process-Structure Relationship in the Directed Energy Deposition of Cobalt-Chromium Alloy Coatings. Materials and Design, Volume 197, January 2021. doi: 10.1016/j.matdes.2020.109229

  7. S. Ramesh, Y. Zhang, D. Cormier, O. Harrysson, P. Rao, A. Tamayol, I. Rivero Extrusion Bioprinting: Recent Progress, Challenges, and Future Opportunities. Bioprinting, (In-Press) doi: 10.1016/j.bprint.2020.e0011

  8. H. Yang, P. Rao, T. Simpson, Y. Lu, P. Witherell, A. R. Nassar, E. Reutzel, and S. Kumara Six-sigma Quality Management of Additive Manufacturing. Proceedings of the IEEE (In-Press) doi: 10.1109/JPROC.2020.3034519

  9. J. Liu, J. Zheng, P. Rao, and Z. Kong. Machine learning–driven in situ process monitoring with vibration frequency spectra for chemical mechanical planarization. International Journal Advanced Manufacturing Technology, 111, 1873–1888 (2020). https://doi.org/10.1007/s00170-020-06165-

  10. A. C. Gaikwad, B. Giera, G.M. Guss, J-B Forien, M. J. Matthews, and P. Rao. Heterogeneous Sensing and Scientific Machine Learning for Quality Assurance in Laser Powder Bed Fusion – A Single-track Study. Additive Manufacturing (Accepted, In-Press, October 7th, 2020). doi:/10.1016/j.addma.2020.10165

  11.  R. Yavari, R.J. Williams, K. Cole, P. Hooper, and P. Rao. Thermal Modeling in Metal Additive Manufacturing using Graph Theory: Experimental Validation with In-situ Infrared Thermography Data from Laser Powder Bed Fusion. ASME Transactions, Journal of Manufacturing Science and Engineering, 142(12): 121005, 2020. doi: 10.1115/1.4047619.
  12. J. Williams, P. Rao, A. Samal, M. Johnson. Paired Trial Classification: A Novel Deep Learning Technique for MVPA. Frontiers of Neuroscience, Volume 14, Issue 47, April 2020. doi: 10.3389/fnins.2020.00417

  13. R. Salary, J.P. Lombardi, D. L. Weerawane, M.S. Tootooni, P. Rao, M. Poliks. A Sparse Representation-based Classification (SRC) Approach for Near Real-time Functional Monitoring of Aerosol Jet-Printed Electronic Devices. ASME Transactions, Journal of Manufacturing Science and Engineering 142(8): 081007, 2020.  doi:/10.1115/1.4047045

  14. K. Cole, R. Yavari, and P.Rao. Computational heat transfer with spectral graph theory: Quantitative verification, International Journal of Thermal Sciences. Volume 153, July 2020. doi: 10.1016/j.ijthermalsci.2020.106383

  15. S. Gerdes, A. Mostafavi, S. Ramesh, A. Memic, I. Rivero, P. Rao, and A. Tamayol. Process-Structure-Quality Relationships of 3D Printed PCL-Hydroxyapatite Scaffolds, Tissue Engineering (Part A), (Accepted, in-press, available online). doi: 10.1089/ten.TEA.2019.0237

  16. A.C. Gaikwad, R. Yavari, M. Montazeri, K. Cole, L. Bian, P. Rao. Toward the Digital Twin in Metal Additive Manufacturing – Integrating Thermal Simulations, Sensing, and Analytics to Detect Process Faults, IISE Transactions (Accepted) doi: 10.1080/24725854.2019.1701753

  17. A.C. Gaikwad, F. Imani, H. Yang, E. Reutzel, and, P. Rao Prediction of Build Quality in Laser Powder Bed Fusion using Deep Learning of In-Situ Images, ASTM Journal of Smart and Sustainable Manufacturing System 3 (1), pp. 98-121, 2019. doi:10.1520/SSMS20190027

  18. M. Montazeri, A. Nassar. C. Stutzman, P. Rao Heterogeneous Sensor-based Condition Monitoring in Directed Energy Deposition, Additive Manufacturing, Volume 30, December 2019, 100916. doi.org/10.1016/j.addma.2019.100916.

  19. M. Amini, S.I. Chang, P. Rao. A Cybermanufacturing and Artificial Intelligence Framework for Laser Powder Bed Fusion (LPBF) Additive Manufacturing Process, Manufacturing Letters, 21, pp. 41-44, 2019. doi:10.1016/j.mfglet.2019.08.007

  20. M. Montazeri, A. Nassar, A. Dunbar, P. Rao, In-Process Monitoring of Porosity in Additive Manufacturing Using In-Process Optical Emission Spectroscopy Signals, IISE Transactions (Manufacturing and Design), 2019, Accepted, In-Press. doi: 0.1080/24725854.2019.1659525

  21. R. Yavari, K. Cole, P. Rao, Thermal Modeling in Metal Additive Manufacturing using Graph Theory. ASME Transactions, Journal of Manufacturing Science and Engineering, 2019, Vol. 141, pp. 0710071-20. doi: 10.1115/1.4043648

  22. M. Roy, R. Yavari, C. Zhou, O. Wodo, and P. Rao. Prediction and Experimental Validation of Part Thermal History in Fused Filament Fabrication Additive Manufacturing Process, ASME Transactions, Journal of Manufacturing Science and Engineering, 141(12), pp. 121001-10, 2019. doi: 10.1115/1.4045056

  23. J. Lombardi, R. Salary, D. Weerawarne, P.Rao, M. Poliks,  Image-Based Closed-Loop Control of Aerosol Jet Printing Using Classical Control Methods, ASME Transactions, Journal of Manufacturing Science and Engineering, 141(7), 071011-20, 2019. doi: 10.1115/1.4043659

  24. L.J. Rhodes, M. Rios, J. Williams, G. Quiñones, P. Rao, V. Miskovic, The Role of Low-Level Image Features in The Affective Categorization Of Rapidly Presented Scenes, PLoS ONE 14(5): e0215975. doi: 10.1371/journal.pone.0215975

  25. F. Imani, B. Yao, R. Chen, P. Rao, H. Yang, Joint Multifractal and Lacunarity Analysis of Image Profiles for Manufacturing Quality Control (Technical Brief), ASME Transactions, Journal of Manufacturing Science and Engineering, 141(4), 044501-08, 2018. doi: 10.1115/1.4042579.

  26. J. Williams, P. Dryburgh, A. Clare, P. Rao, A. Samal, Defect Detection and Monitoring in Metal Additive Manufactured Parts through Deep Learning of Spatially Resolved Acoustic Spectroscopy Signals. ASTM Journal of Smart and Sustainable Manufacturing, Vol. 2(1), 204-226, 2018. doi/10.1520/SSMS20180035

  27. J. Liu, C. Liu, Y. Bai, Z. Kong, P. Rao, and C. Williams. Layer-wise Spatial Modeling of Porosity in Additive Manufacturing. IISE Transactions, (Additive Manufacturing Special Issue), Accepted, In-Press, 2018. Article Highlighted in January 2019 issue of the Industrial and Systems Engineer Magazine. doi:/10.1080/24725854.2018.1478169

  28. F. Imani, A. Gaikwad, M. Montazeri, P. Rao, H. Yang, E. Reutzel. Process Mapping and In-Process Monitoring of Porosity in Laser Powder Bed Fusion Using Layerwise Optical Imaging. ASME Transactions, Journal of Manufacturing Science and Engineering, 140(10), 101009-23, 2018. doi: 10.1115/1.4040615

  29. X. Wang, M. Sealy, R. Williams, P. Rao, Y. Guo. Stochastic Modeling and Analysis of Spindle Energy Consumption During Hard Milling. ASME Transactions, Journal of Manufacturing Science and Engineering, 140(6), 060801-14, 2018. doi: 10.1115/1.4038644

  30. M. Montazeri, P. Rao. Heterogeneous Sensor-based Build Condition Monitoring in Laser Powder Bed Fusion Additive Manufacturing Process using a Spectral Graph Theoretic Approach. ASME Transactions, Journal of Manufacturing Science and Engineering, 140(9), 091002-18, 2018. doi: 10.1115/1.4040264

  31. M. Montazeri, R. Yavari, P. Rao, P. Boulware. In-process Monitoring of Material Cross-Contamination Defects in Laser Powder Bed Fusion. ASME Transactions, Journal of Manufacturing Science and Engineering, 140(11), 111001-20, 2018. doi: 10.1115/1.4040543

  32. M. Sealy, G. Madireddy, R. Williams, P. Rao, M. Toursangsaraki. Review Article - Hybrid Processes in Additive Manufacturing. ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 140(6), pp. 060801-14, 2018. doi:10.1115/1.4038644.

  33. H. Sun, P. Rao, Z. Kong, X. Deng and R. Jin. Functional Quantitative and Qualitative Models for Quality Modeling in a Fused Deposition Modeling Process. IEEE Transactions, Automation Science and Engineering, Vol. 15(1), pp. 393-403, 2018. doi: 10.1109/TASE.2017.2763609.

  34. M. S. Tootooni, P. Rao, C-A. Chou, Z. Kong.  A Spectral Graph Theoretic Approach for Monitoring Multivariate Time Series Data from Complex Dynamical Processes. IEEE Transactions, Automation Science and Engineering, Vol.15(1), pp.127-144, 2018. doi: 10.1109/TASE.2016.2598094

  35. M. Khanzadeh, P. Rao, R. Jafari-Marandi, B. K. Smith, M. Tschopp, L. Bian. Characterizing the Geometric Accuracy of Additively Manufactured Components Using Self-Organizing Maps. ASME Transactions, Journal of Manufacturing Science and Engineering, Vol 140(3), pp. 031011-  031023, 2017. doi: 10.1115/1.4038598

  36. M. Aboutaleb, M. Tschopp, P. Rao, L. Bian. Accelerated Multiobjective Optimization of Part Geometric Accuracy in Additive Manufacturing (AM). ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 139(10), pp. 101001 – 101014, 2017. doi: 10.1115/1.4037319

  37. R. Salary, J. Lombardi, P. Rao, M. Poliks. Aerosol Jet Printing (AJP) of Flexible Electronic Devices: Online Monitoring of Functional Electrical Properties Using Shape-from-Shading (SfS) Image Analysis. ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 139(10), pp. 101010 – 101023, 2017. doi:10.1115/1.4036660

  38. M.S. Tootooni, A. Dsouza, R. Donovan, P. Rao, Z. Kong, P. Borgesen. Classifying the Dimensional Variation in Additive Manufactured Parts from Laser-Scanned 3D Point Cloud Data using Machine Learning Approaches. ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 139(9), pp. 091005 – 091019, 2017. doi: 10.1115/1.4036641

  39. M.S. Tootooni, C. Liu, D. Roberson, R. Donovan, P. Rao, Z. Kong, S.T.S. Bukkapatnam. Online Non-contact Surface Finish Machining using Graph-based Image Analysis. SME Journal of Manufacturing Systems, Vol. 41, pp. 266-276, October 2016. doi: 10.1016/j.jmsy.2016.09.007.

  40. R. Salary, J. Lombardi, M.S. Tootooni, R. Donovan, P. Rao, M. Poliks, P. Borgesen. Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process. ASME Transactions, Journal of Manufacturing Science and Engineering, 139(2), pp. 021015-021036, October 2016. doi:10.1115/1.4034591

  41. J. Liu, Omer F. Beyca, P. Rao, Z. Kong, and S. Bukkapatnam. Dirichlet Process Gaussian Mixture (DPGM) Models for Real-Time Monitoring and its Application to Chemical Mechanical Planarization. IEEE Transactions, Automation Science and Engineering, Vol. 14(1), pp. 208-221, 2017. doi: 10.1109/TASE.2016.2599436

  42. K. Bastani, P. Rao, and Z. Kong. An Online Sparse Estimation-based Classification (OSEC) Approach for Real-time Monitoring in Advanced Manufacturing Process from Heterogeneous Sensor Data. IIE Transactions, Quality and Reliability Engineering, 48(7), pp. 579-598, 2016. doi: 10.1080/0740817X.2015.1122254 Best Paper Award, Invited talk at IISE Conference, 2018. Article highlighted in the June 2016 (Volume 48, Number 9) Issue of the Industrial and Systems Engineer (ISE) Magazine.

  43. P. Rao, Z. Kong, C. Duty, R. Smith, V. Kunc, and L. Love. Assessment of Dimensional Integrity and Spatial Defect Localization in Additive Manufacturing (AM) using Spectral Graph Theory. ASME Transactions, Journal of Manufacturing Science and Engineering, 138(5), pp. 051007, 2015. doi: 10.1115/1.4031574

  44. O. Beyca, P. Rao, Z. Kong, S. Bukkapatnam, and R. Komanduri, Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) process using non-parametric Bayesian clustering and evidence theory. IEEE Transactions, Automation Science and Engineering, 13(2), pp.1033-1044, 2016. doi: 10.1109/TASE.2015.2447454

  45. P. Rao, J. Liu, D. Roberson, and Z. Kong, and C. Williams. Online Real-time Quality Monitoring in Additive Manufacturing Processes using Heterogeneous Sensors. ASME Transactions, Journal of Manufacturing Science and Engineering. 137(6), pp. 061007, 2015. doi: 10.1115/1.4029823.

  46. P. Rao, S. Bukkapatnam, O. Beyca, Z. Kong, K. Case, and R. Komanduri. A Graph-Theoretic Approach for Quantification Of Surface Morphology and Its Application To Chemical Mechanical Planarization (CMP) Process. IIE Transactions, Quality and Reliability Engineering, 47(10), pp. 1-24, 2015. doi: 10.1080/0740817X.2014.1001927                                    Best Paper Award (Honorable Mention), Invited talk at IISE Conference, 2017. Article highlighted in the September 2015, (Volume 47, Number 6) issue of the Industrial Engineer Magazine (now called Industrial and Systems Engineer)

  47. P. Rao, S. Bukkapatnam, O. Beyca, Z. Kong, and R. Komanduri. Real-time Identification of Incipient Surface Morphology Variations in Ultraprecision Machining Process. ASME Transactions, Journal of Manufacturing Science and Engineering, 136(2), pp. 021008, 2014. doi: 10.1115/1.4026210

  48. P. Rao, M. Bhushan, S. Bukkapatnam, Z. Kong, S. Byalal O. Beyca, A. Fields, and R. Komanduri, Process-Machine Interaction (PMI) Modeling and Monitoring of Chemical Mechanical Planarization (CMP) Process Using Wireless Vibration Sensors. IEEE Transactions, Semiconductor Manufacturing, 27(1), pp. 1-15, 2014. doi: 10.1109/TSM.2013.2293095

  49. S. Bukkapatnam, P. Rao, W-C. Lih, N. Chandrashekeran, and R. Komanduri, Process Characterization and Statistical Analysis of oxide CMP on a Silicon Wafer, Applied Physics (A), 88(4) pp. 785-792, 2007. doi:10.1007/s00339-007-4082-x

  50. S. Bukkapatnam, P.Rao, and R. Komanduri. Experimental Dynamics Characterization and Monitoring of MRR in Oxide Chemical Mechanical Planarization (CMP) Process. International Journal of Machine Tools and Manufacture, 2008, 48(12-13), pp.1375-1386. doi:10.1016/j.ijmachtools.2008.05.006.

  51. Wen-Chen Lih, S. Bukkapatnam, P. Rao, N. Chandrasekharan, R. Komanduri. Adaptive Neuro-Fuzzy Inference System Modeling of MRR and WIWNU in CMP Process with Sparse Experimental Data. IEEE Transactions, Automation Science and Engineering, 5(1), pp. 71 -83, 2008. doi: 10.1109/TASE.2007.911683

  52. S. Bukapatnam, R. Komanduri, H. Yang, P. Rao, W.C. Lih, M. Malshe, L.M. Raff, B. Benjamin, and M. Rockley. Classification of Atrial Fibrillation Episodes from Sparse Electro-Cardiogram Data. Journal of Electrocardiology, 41(4), pp. 292-299, 2008. doi:10.1016/j.jelectrocard.2008.01.004

  53. J.M, Govardhan, S. Bukkapatnam, Y. Bhamare, P. Rao, and V. Rajamani. Statistical analysis and design of RFID systems for monitoring vehicle ingress/egress in warehouse environments. International Journal of Radio Frequency Identification Technology and Applications, 2007, 1(2), pp. 123-146. doi: 10.1504/IJRFITA.2007.013140