Purdue University Mechanical Engineering | Neera Jain: Jain Research Lab @PurdueME | Uploaded January 2023 | Updated October 2024, 7 hours ago.
Website: https://engineering.purdue.edu/JainResearchLab
Our research team is driven by a desire to advance technologies and systems that will have a lasting impact on society. Our systems-based approach is grounded in two fundamental areas of mechanical engineering:
DYNAMICS
We are interested in deriving reduced- or low-order dynamic models of complex processes and systems with the intent of using those models for real-time feedback and decision-making. A key focus is understanding the appropriate balance of physics-based and empirical methods when considering systems ranging from thermal energy storage to steel manufacturing. We are also tackling modeling of human cognitive behavior, where reliance on data is necessary. There, we strive to ensure that our data-driven modeling is still grounded in findings from cognitive psychology and human factors engineering.
CONTROL & OPTIMIZATION
Motivated by real world problems, we are tackling several problems, theoretical and applied, in the field of controls. This includes developing scalable algorithms for control co-design suitable for complex thermal-fluid systems, iterative learning control for time-delayed systems with model uncertainty, as well as reachability analysis for hybrid systems with state and input-based switching. We are also designing optimal control algorithms for less conventional systems – namely for the purpose of human-aware adaptive automation.
Email: neerajain@purdue.edu
Purdue Mechanical Engineering: https://purdue.edu/ME
Website: https://engineering.purdue.edu/JainResearchLab
Our research team is driven by a desire to advance technologies and systems that will have a lasting impact on society. Our systems-based approach is grounded in two fundamental areas of mechanical engineering:
DYNAMICS
We are interested in deriving reduced- or low-order dynamic models of complex processes and systems with the intent of using those models for real-time feedback and decision-making. A key focus is understanding the appropriate balance of physics-based and empirical methods when considering systems ranging from thermal energy storage to steel manufacturing. We are also tackling modeling of human cognitive behavior, where reliance on data is necessary. There, we strive to ensure that our data-driven modeling is still grounded in findings from cognitive psychology and human factors engineering.
CONTROL & OPTIMIZATION
Motivated by real world problems, we are tackling several problems, theoretical and applied, in the field of controls. This includes developing scalable algorithms for control co-design suitable for complex thermal-fluid systems, iterative learning control for time-delayed systems with model uncertainty, as well as reachability analysis for hybrid systems with state and input-based switching. We are also designing optimal control algorithms for less conventional systems – namely for the purpose of human-aware adaptive automation.
Email: neerajain@purdue.edu
Purdue Mechanical Engineering: https://purdue.edu/ME
