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Research Projects

  • Neural networks and knowledge based systems in design and manufacturing
  • Distributed and cooperative AI applied to systems integration
  • Monitoring, diagnosis and control of machining processes
  • Intelligent sensors/sensor integration
  • Wavelet transform applications
  • Product realization for recyclability and reusability
  • Design and manufacturing in mass customization
  • Production software development for
    • group technology
    • computer-aided process planning
    • cost optimization and estimation


  • PhD in Industrial Engineering, Pennsylvania State University, 1994
  • MS in Industrial Engineering, Pennsylvania State University
  • BS in Chemical Engineering, Sri Venkateswara University, India

Research & Scholarship Interests

Machine learning applications in smart and sustainable manufacturing; predictive analytics for smart and connected health; data driven approaches to mass customized instruction
Affiliated With

Department Research Areas

College Research Initiatives

Honors & Awards

  • The 1998 Dell K. Allen Outstanding Young Manufacturing Engineer Award. This award is conferred by the Society of Manufacturing Engineers (SME) and ranks in stature with the SME International Honor Awards and the SME Award of Merit.
  • The 1996 Pritsker Doctoral Dissertation Award for "On-Line Tool Wear Estimation in Turning Through Sensor Data Fusion and Neural Networks.". This award is given by Institute of Industrial Engineers to the outstanding doctoral dissertation research in the areas related to industrial and manufacturing engineering.
  • The 1995 Theoretical Development Award (2nd runner-up) for "Convergence Behavior of an Iterative Process: Application to Neural Networks." at the International Conference on Artificial Neural Networks in Engineering (ANNIE'95), St. Louis, Missouri, USA.
  • The First Prize in the Fourth Annual Graduate Research Exhibition (1989) for "Optical Neural Networks and Their Applications in Manufacturing Systems," at The Pennsylvania State University, University Park, PA, USA.
  • The First Prize in the National Student's Design Competition (1982) for "Manufacture of Formaldehyde," conducted by Indian Council for Science Museums, Bangalore, India.

Teaching Interests

  • Neural networks in manufacturing
  • Computer-aided manufacturing
  • Manufacturing automation
  • Manufacturing methods and processes
  • Design and manufacturing in mass customization
  • Expert Systems
  • Capstone design projects in manufacturing

Selected Publications

  • S. Radhakrishnan, S. Erbis, J.A. Isaacs, S. Kamarthi, Novel Keyword Co-Occurrence Networks Based Methods to Foster Systematic Reviews of Scientific Literature, PLOS ONE, 2017
  • M.G. Uddin, K.S. Ziemer, A. Zeid, Y.-T.T. Lee, S. Kamarthi, Process Control Model for Growth Rate of Molecular Beam Epitaxy of MgO (111) Nanoscale Thin Films on 6H-SiC (0001) Substrates, International Journal of Advanced Manufacturing Technology, 91(1-4), 2017, 907–916
  • S. Radhakrishnan, A. Duvvuru, S. Sultornsanee, S. Kamarthi, Phase Synchronization Based Minimum Spanning Trees for Analysis of Financial Time Series with Nonlinear Correlations, Physica A: Statistical Mechanics and its Applications, 444, 2016, 259-270
  • S. Kamarthi, S. Sultornsanee, A. Zeid, Recurrence Quantification Analysis to Estimating Surface Roughness in Finish Turning Processes, International Journal of Advanced Manufacturing Technology, 87(1-4), 2016, 451–460
  • S. Erbis, Z. Ok, J.A. Isaacs, J.C. Benneyan, S. Kamarthi, Review of Research Trends and Methods in Nano Environmental, Health and Safety Risk Analysis, Risk Analysis: An International Journal, 2016, 1-18
  • S. Erbis, S. Kamarthi, A. Abdollahi-Namin, A. Hakimian, J.A. Isaacs, Stochastic Goal Programming Model for Sustainable CNT-Enabled Lithium-Ion Battery Manufacturing, Environmental Science: Nano, 3, 2016, 1447-1459
See Google Scholar Profile for all publications »

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April 29, 2019

Congratulations to all the winners of the faculty and staff awards, and to everyone for their hard work and dedication during the 2018-2019 academic school year. See Full Photo Gallery Faculty Fellow...

September 7, 2018

Yingzi Lin, MIE associate professor and director of the Intelligent Human-Machine Systems Lab, to lead $1.2M NSF grant to develop a Continuous Objective Multimodal Pain Assessment Sensing System (COMPASS) that improves pain assessment and management, reduces opioid dependency and advances the field of pain management research and patient safety.

August 3, 2016

Sagar Kamarthi (MIE) has been selected as a panel speaker and Andrew Myers (CEE), Yunsi Fei (ECE), & Edgar Goluch (ChE) have been invited to participate at the National Academy of Engineering's eighth Frontiers of Engineering Education (FOEE) symposium.

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