Dr. Bukkapatnam's research addresses the harnessing of high-resolution nonlinear dynamic information, particularly from wireless MEMS sensors, to improve the monitoring and prognostics of real-world systems, including ultraprecision and nanomanufacturing processes and machines, and cardiorespiratory processes. His research has led to 185 peer-reviewed publications (115 published/ accepted in journals and 70 in conference proceedings), 1 granted and five pending patents, and has been the basis for 17 Ph.D. dissertations. His research has received support from federal agencies including National Science Foundation, Department of Energy, and Department of Defense, and the private sector including General Motors, Ford, National Instruments, and the Central Rural Electric Cooperative.

education and training
selected publications
Academic Articles118
  • Iquebal, A. S., & Bukkapatnam, S. (2018). Change Detection and Prognostics for Transient Real-World Processes Using Streaming Data. Recent Advances in Optimization and Modeling of Contemporary Problems. (pp. 279-315). INFORMS.
    doi badge
  • Jain, V. K. (2016). Nanofinishing Science and Technology. Nanofinishing Science and Technology: Basic and Advanced Finishing and Polishing Processes. (pp. 549-595). CRC Press.
    doi badge
  • Iyengar, S., Brooks, R., Lu, C., Schwier, J., Griffin, C., & Bukkapatnam, S. (2016). Markov Model Inferencing in Distributed Systems. Distributed Sensor Networks. (pp. 569-580). Chapman and Hall/CRC.
    doi badge
  • Chang, C., Bukkapatnam, S., & Komanduri, R. (2014). Sensing and informatics in laser-based nanomanufacturing processes. Laser and Photonic Systems: Design and Integration. (pp. 201-234). CRC Press.
    doi badge
  • Raff, L., Komanduri, R., Hagan, M., & Bukkapatnam, S. (2012). Applications of Neural Network Fitting of Potential-Energy Surfaces. Neural Networks in Chemical Reaction Dynamics. Oxford University Press.
    doi badge
Conference Papers56
researcher on
chaired theses and dissertations
First Name
Last Name
mailing address
Texas A&M University; Industrial Engineering; 3131 TAMU
College Station, TX 77843-3131