Prahalada Rao

Prahalada Rao, PhD

Assistant Professor
Academic Degrees
  • 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)
Areas of Research and Professional Interest
  • Monitoring of ultraprecision nanomanufacturing and additive manufacturing (AM) processes: Empirical and phenomenological study of process machine interactions in ultraprecision machining (UPM), diamond turning (DT),  semiconductor chemical mechanical planarization (CMP), fused deposition modeling (FDM), and selective laser sintering (SLS).

  • Sensor-based predictive analytics and quality monitoring of data rich complex systems: Novel neuro-dynamic and graph theoretic image processing algorithms for real-time defect detection in manufacturing processes from heterogeneous sensor data.

  • Surface Morphology and dimensional integrity monitoring: Approaches for non-destructive quantification of ultraprecision surface morphology and dimensional integrity assurance of complex non-euclidean surfaces.

  • Design of wireless sensors networks and digital data acquisition: Customization of wired, as well as wireless sensors for high-speed data acquisition in manufacturing and healthcare applications.

Courses Taught
  • MECH 498/898 Additive Manufacturing

About Prahalada Rao

Prahalad Rao’s research focuses on sensor-based monitoring and diagnosis of complex bio-physical and manufacturing processes (e.g., additive manufacturing, ultraprecision machining, semiconductor planarization, and neurophysiology). He was recently (2015) awarded a NSF grant (CMMI 1538059) for applying graph theoretic techniques towards monitoring of neurophysiological anomalies.

Prior to joining the Mechanical and Materials Engineering Department at University of Nebraska-Lincoln (UNL) he held the position of Assistant Professor (2014-2016), System Science and Industrial Engineering (SSIE), Binghamton University. From 2013-2014, he was a Post-Doctoral Research Associate at Virginia Tech. He received the B. Engg. degree (First Class) in Production Engineering from Victoria Jubilee Technical Institute (VJTI), Bombay University, India, in 2003; and the M.S. and Ph.D. degrees in industrial engineering from Oklahoma State University (OSU) in 2006 and 2013, respectively.

Prahalad is a member of Institute of Industrial Engineers (IIE), American Society for Quality (ASQ), and Institute for Operations Research and the Management Sciences (INFORMS). He was awarded the Alpha Pi Mu Outstanding Research Assistant Award by OSU in 2008. He was a finalist for two awards offered by the IIE, namely, Manufacturing and Design Division Young Investigator Award (2016), and the John L. Imhoff (2011) graduate fellowship. His PhD dissertation was nominated for the university-wide best dissertation award (2013), and the IIE Pritsker Dissertation Prize (2014) by the industrial engineering department at OSU. He is an amateur radio ARRL General Class licensee with the call sign K5RAO.



Experience

  • Assistant Professor (2016-present), Mechanical and Materials Engineering
    University of Nebraska-Lincoln
  • Assistant Professor (2014-2016), Systems Science and Industrial Engineering            
    Binghamton University (State University of New York)                                                  
  • Post-Doctoral Research Associate (2013-2014), Industrial and Systems Engineering
    Virginia Polytechnic Institute and State University (Virginia Tech)     
    Supervisor: Dr. Zhenyu (James) Kong

Honors and Awards

  • 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


Funding

  • National Science Foundation – CMMI, Service, Manufacturing and Operations Research Program, Grant Number: CMMI 1538059, Biosensor Data Fusion for Real-time Monitoring of Global Neurophysiological Function. Project Duration: September 2015 - 2018, Role: PI, Amount $217,971. Co-PIs: V. Miskovic (Psychology); C-A Chou (Industrial Engineering).
  • State of New York, Strategic Partnership for Industrial Resurgence (SPIR), Quality Assurance in Direct Metal Sintering Process. With Incodema3D, Ithaca, NY. September 2015 – January 2016; January 2016 - May 2016.
  • SUNY Binghamton Transdisciplinary Area of Excellence (TAE) Real-Time Monitoring of Global Neurophysiological Function Using Customized 3D Printed BioSensors and Sensor Data Fusion Algorithms ($15,000, granted March 2015, Position PI).
    Co-PIs: V. Miskovic (Psychology); C-A Chou (Industrial Engineering).
  • SUNY Binghamton Instructional Labs and Software Grant for Additive Manufacturing Instructional Lab ($36,000, granted January 2015).
  • University of Nebraska-Lincoln, Layman Seed Grant, March 2017 ($10,000)

Selected Publications

Peer Reviewed Journal Articles Published/Accepted (18)

* corresponding author; # student under my sole supervision; ^ student supported by NSF REU under my supervision; @ joint supervision with another faculty.

  1. 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 (Accepted, Pending Revisions), 2017.
  2. 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 (Accepted, Pending Revisions), 2017.
  3. 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
  4. R. Salary@, J. Lombardi, M.S. Tootooni#, R. Donovan#^, P. Rao*, M. Poliks, P. Borgesen, Modeling and Monitoring of Aerosol Jet Printing (AJP) Process. ASME Transactions, Journal of Manufacturing Science and Engineering, 139(2), pp. 021015-021036, October 2016,  doi:10.1115/1.4034591
  5. 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 (Accepted, In-Press), July 2016. doi: 10.1109/TASE.2016.2598094
  6. 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 (CMP). IEEE Transactions, Automation Science and Engineering (Accepted, In-press), July 2016.
  7. 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. Article highlighted in the June 2016 (Volume 48, Number 9) Issue of the Industrial and Systems Engineer (ISE) Magazine.
  8. 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
  9. 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
  10. 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
  11. 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).
  12. 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
  13. 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
  14. 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
  15. 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: doi:10.1016/j.ijmachtools.2008.05.006.
  16. 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
  17. 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
  18. 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

Peer Reviewed Archival Conference Papers.

  1. M. S. Tootooni#, M. Fan, R. Sivasubramony#, C.-A. Chou, V. Miskovic, and P. Rao*, Graph Theoretic Compressive Sensing Approach for Classification of Global Neurophysiological States from Electroencephalography (EEG) Signals, in Lecture Notes in Computer Science, Vol 9919, 2016, pp. 42-51.  doi: 10.1007/978-3-319-47103-7_25. Brain Informatics and Health: International Conference, BIH 2016, Omaha, NE, USA, October 13-16, 2016 Proceedings. Online ISBN: 978-3-319-47103-7. doi: 10.1007/978-3-319-47103-7_5
  2. M. Fan, M.Tootooni#, R. Sivasubramony#, V. Miskovic, P. Rao, C-A. Chou*. Acute Stress Detection Using Recurrence Quantification Analysis of Electroencephalogram (EEG) Signals. in Lecture Notes in Computer Science, Vol 9919, 2016, pp. 252-261.  doi: 10.1007/978-3-319-47103-7_25. Brain Informatics and Health: International Conference, BIH 2016, Omaha, NE, USA, October 13-16, 2016 Proceedings. Online ISBN: 978-3-319-47103-7. doi: 10.1007/978-3-319-47103-7_25
  3. R. Salary@, J. Lombardi, M. Tootooni, R. Donovan, P. Rao*, M. Poliks, In-situ Sensor-based Monitoring and Computational Fluid Dynamics Modeling of Aerosol Jet Printing Process. Paper # MSEC2016-8535, 44th Proceedings of the North American Manufacturing Research Institution (NAMRI) of SME/2016 Manufacturing Science and Engineering Conference (MSEC) of the ASME, June 27th-July 1st, Blacksburg, VA, 2016. doi:10.1115/MSEC2016-8535.
  4. P. Rao, Z. Kong*, C. Duty, R. Smith, Three Dimensional Point Cloud-based Dimensional Integrity Assessment for Additive Manufactured Parts using Spectral Graph Theory.   Paper # MSEC2016-8516, 44th Proceedings of the North American Manufacturing Research Institution (NAMRI) of SME/2016 Manufacturing Science and Engineering Conference (MSEC) of the ASME, June 27th-July 1st, Blacksburg, VA, 2016. doi:10.1115/MSEC2016-8516
  5. P. Rao, M. Tootooni#, C-A Liu, D. Roberson, R. Donovan^#, R. Sivasubramony#, S. Bukkapatnam, Z. Kong, Online Non-contact Surface Finish Measurement in Machining using Graph-based Image Analysis Paper # NAMRC 44-5, Komanduri Symposium, 44th Proceedings of the North American Manufacturing Research Institution (NAMRI) of SME/2016 Manufacturing Science and Engineering Conference (MSEC) of the ASME, June 27th-July 1st, Blacksburg, VA, 2016. Note: This Paper was accepted for publication as a peer-reviewed journal paper in the SME Journal of Manufacturing Systems, and was hence withdrawn.
  6. P. Rao, Z. Kong, S. Bukkapatnam*, O. Beyca, K. Case, R. Komanduri, Quantification of Ultraprecision Surface Morphology using an Algebraic Graph Theoretic Approach. Hoken Symposium, 43rd Proceedings of the North American Manufacturing Research Institution (NAMRI) of SME, Paper # NAMRC 43-65, Proceedia Manufacturing, June 8th – June 12th, Charlotte, NC, 2015. doi.org/10.1016/j.promfg.2015.09.025
  7. P. Rao, J. Liu, D. Roberson, Z. Kong,* Sensor-based Online Fault Detection in Additive Manufacturing, Paper # MSEC 2015-9389, 43rd Proceedings of the North American Manufacturing Research Institution (NAMRI) of SME, June 8th – June 12th, Charlotte, NC, 2015. doi:10.1115/MSEC2015-9389.

Books and Book Chapters

  1. P. Rao, Chapter 6: Monitoring and Control, in Laser-based Additive Manufacturing Processes, Eds. John Usher and Linkan Bian, Springer. Expected Publication Date: 2017.
  2. B. Khoda, T. Benny#, P. Rao, M. Sealy, C. Zhou, Chapter 8: Applications of Laser-based Additive Manufacturing, in Laser-based Additive Manufacturing Processes, Eds. John Usher and Linkan Bian, Springer. Expected Publication Date: 2017.
  3. P. Rao, R. Komanduri and, S. Bukkapatnam, Sensor-based Modeling and Monitoring of Chemical Mechanical Polishing, VDM Verlag, ISBN 978-3-639-03564-3.


Recent Presentations

 
  1. Invited Poster and Student Fellow: Real-time monitoring of surface morphology variations in ultra-precision manufacturing processes, NSF Civil Mechanical and Manufacturing Innovation Conference, Boston, MA, 2012.
  2. Invited Poster and Future Academician Colloquium Invitee: Real-time monitoring of surface morphology variations in ultra-precision manufacturing processes, IIE Industrial Engineering Research Conference, Orlando, FL, 2012.
  3. Future Academician Colloquium Invitee: INFORMS, Phoenix, AZ, 2012.
  4. Invited paper and CIRP student grant: S.T.S Bukkapatnam, P.K. Rao, O.F. Beyca, Z.Kong, and R. Komanduri, Towards Real-time Detection of Incipient Surface Variations in Ultra-Precision Machining Process, 44th  CIRP Conference, University of Wisconsin-Madison, Madison, WI, 2011.
  5. Invited paper: R. Komanduri, S. Bukkapatnam, P.K. Rao and U. Phatak , Experimental Dynamics Characterization and Monitoring of Chemical Mechanical Planarization Process, Invited Paper, CMP-MIC 2007, Freemont, CA.
  6. Invited Poster and Student Fellow: Monitoring of Surface Generation in Ultra-Precision Machining using Multi sensor Fusion, NSF Civil Mechanical and Manufacturing Innovation Conference, Atlanta, GA , 2010.
  7. Invited Poster: Heterogeneous Wireless Sensing and Modeling of Chemical-Mechanical Interactions in Chemical Mechanical Planarization Process for Microelectronic Applications, NSF Nanomanufacturing Workshop, Boston, MA, 2009.
  8. Multiple invited talks at INFORMS conference, 2005, 2010, 2011, 2012, 2013, 2014 (2 talks), and 2015 (2 talks).
  9. Multiple invited talks at ISERC conference, 2012, 2015.
  10. Multiple talks at NAMRC/MSEC, 2015 (2 talks), 2016 (3 talks).