Early steps of my research were in the field of control systems, which I truly took a liking to during my undergraduate days at IIT Madras. Gradually, thanks to my doctoral studies at the University of Alberta, and the independent research that followed, I was drawn into the allied fields of mathematical modelling, fault detection (process monitoring) and optimization of processes. Indispensable to these areas are the subjects of applied signal processing and statistical data analysis. Over the years, our group's research work has metamorphosed into topics belonging to the broad fields of process systems engineering (including mathematical modelling, control and optimization) and data science (including statistical signal processing, multivariate data analysis and machine learning).

 

I believe that research should focus on developing solutions [to new / old problems], give rise to novel perspectives, strengthen our theoretical understanding [of that subject] and importantly, contribute to applications of societal / industrial relevance. Finally, it should be generic - the ideas should be applicable universally with some tailoring for each domain. In essence, we work on solving practical and theoretical problems of interest across different disciplines of engineering and science, using the tools of systems theory, optimization and data science. We believe in developing theory that has a healthy balance of rigour and practicality, and taking up applications that are useful, challenging and thought provoking.

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Research Areas: 

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• Health Monitoring of Control Loops

• Data-Driven and Grey-Box Modelling (System Identification)

• Complex Networks (Modelling and Reconstruction)

• Sparse Optimization and Compressive Sensing

• Systems Biology

• Hybrid Energy Systems - Modelling, Control and Monitoring