DEPARTMENT OF APPLIED MECHANICS
& BIOMEDICAL ENGINEERING Indian Institute Of Technology Madras

Babji Srinivasan

Associate Professor

Ph.D., Chemical Engineering -Texas Tech University (August 2008 - May 2011).

M.S., Chemical Engineering - Indian Institute of Technology, Madras (August 2005 - May 2008 ).



B.Tech., Instrumentation and Control - Madras Institute of Technology (August 2001 - May 2005).

914422574085

babji[.]srinivasan[at]iitm[.]ac[.]in

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 Research Interest

  • Cognitive systems engineering.
  • Behavioral informatics (hardware development, instrumentation and analytics).
  • Human cyber-physical systems.

 Contact

   Babji Srinivasan
   babji.srinivasan@iitm.ac.in
   Phone: 044-2257-4085

 July 2020 - Present

  Associate Professor

  Indian Institute of Technology Madras - Applied Mechanics.

 December 2012 - July 2020

  Assistant Professor

  Indian Institute of Technology Gandhinagar - Electrical Engineering, Chemical Engineering.

 Summer 2014

  Visiting Assistant Professor

  Columbia University, New York.

 January 2012 - November 2012

  Postdoctoral Research Scientist

  Columbia University, New York.

 Publications

 Courses Taught

  • Probability and Random Processes
  • Applied Multivariate Data Analysis
  • Design of Experiments
  • Cognitive Systems Engineering
  • Control Theory
  • Modern Control Theory
  • Electronic Instrumentation

 Funded Projects - HILCPS, IIT Madras

  • Intelligent power management system (IPMS) for monitoring, diagnosis and prognostics of electric loads in armored fighting vehicles.
  • Advanced Optimization Strategies for Efficient Water and Energy Utilization in Batch Processes: Case Studies in Pharmaceutical and Textile Industries.
  • Fundamental Limitations for Unordered Signal Sensing in the Presence of Noise
  • Human-in-the-loop Analytics for Operator Learning: Knowledge Assessment through Eye Tracking
  • Cost effective Eye Tracking Approaches to Analyze Human Machine Interface in Nuclear Power Plants
  • Development of label propagation framework using active learning approaches in industrial settings