▌Process systems engineering
Using various optimization tools, data analysis, multivariate statistical analysis including time series analysis our faculty are involved in investigating undertraining propagation in information theory, combinatorial chemistry, development of medical devices, particle synthesis and in designing and controlling water distribution networks. These are accompanied computations for model developments, process monitoring, fault diagnoses and network reconstruction. There is also current interest in working towards development of point of care devices, intensifying processes in microfluidic systems, developing computational tools for micro-fluidic systems with regard to lab on chip applications for various bio and pharma industries.
Systems Engineering and Data Sciences
Our group works on the use of both first principles modeling and data science methods for solving design and operational problems in complex systems. We look at rational approaches to optimally design a wide variety of engineered systems. We also research on operational aspects of the engineered systems such as monitoring, diagnosis, control and so on. Further, our group also explores the use of systems approach for challenging inter-disciplinary problems.
Integrated Process Manufacture
The goal of process industries is to operate their processes at optimal conditions under stringent environmental and safety constraints. However, these processes are often operated at sub-optimal level due to several reasons ranging from poor automation, or lack of expertise. For example, process recipes in pharma and specialty chemical industries are often not optimized for maximizing the yield of the desired products due to poor understanding of underlying processes, and lack of quality data. The objective of our group is to achieve process improvement and development via process integration not only at process design but also at process control and optimization stage. We develop methods and techniques based on systems- engineering, data analytics and computational fluid dynamics tools combined with experimental data to achieve this goal.
Metabolism remains a common denominator for a myriad of clinical conditions, including metabolic disorders, neuro-degenerative diseases, and cancer. A systems approach warrants better understanding of the disease mechanisms, as well as, provide novel solutions for efficient medical diagnostics and therapeutics. Our group works on, (i) multi-scale modeling of the human metabolism, employing the steady-state and dynamic methods, (ii) modeling microbe-host interactions and, (iii) algorithm development for integration and analysis of ‘omics’ data.
Energy and Water Systems
It is estimated that energy generation accounts for approximately 15% of global water use, while approximately 8% of energy is used for treating and transporting water. The resulting water-energy nexus is well studied and the process systems engineering community has contributed significantly in formulating and solving complex problems in this domain, e.g., in design control, operation, monitoring of water distribution networks and next generation energy generation devices (fuel cells, flow batteries). At IIT Madras, our focus spans the spectrum from theory to practical algorithms, experimental validation and field implementation.