Research

COOPS plays a pivotal role in fostering cutting-edge research, equipping students with the skills needed for industry success, and providing expertise for industry partners. The center focuses on:

  • Conducting state-of-the-art research combining modeling and theoretical studies to solve complex systems engineering problems.

  • Engaging undergraduate, MS, and PhD students in hands- on research and specialized courses to prepare the next generation of leaders in process systems engineering.

  • Providing expert consultation and innovative solutions for industry challenges, ensuring that our research has practical, real-world impact.

  • Collaborating with other departments at Purdue to promote interdisciplinary research and education.

Rakesh Agrawal

  • Chemical Process Synthesis and process intensification
  • Separation process analysis and efficiency improvement
  • Electrification of chemical processes and unit operations for sustainable economy

(Optimized crude oil separation distillation sequences with 16% CO2 reduction)

David E. Bernal Neira

  • Advanced algorithms for process operation and optimization
  • Novel computational tools for computational process simulation and optimization
  • Integrated multi-scale modeling for process systems

Can Li

  • Privacy-preserved data sharing for decarbonizing the chemical industry
  • Explain supply chain optimization problems using large language models
  • Physics-informed machine learning for chemical process design

(Multi-timescale optimization of electrified chemical supply chain)

Cornelius Masuku

  • Decarbonization by Renewable Electrification
  • Synthesis and design of electrically driven process units
  • Modeling and optimization of chemical processes with electricity as a major energy source

Zoltan Nagy

  • Process intensification, optimization and advanced control of particulate systems
  • Process synthesis and distributed control of modular integrated manufacturing systems and networks
  • Process analytical technologies, uncertainty analysis and robust control
  • Model identification and model-based experimental design

(Optimal pharmaceutical campaign manufacturing using PharmaPy)

Joe Pekny

  • Knowledge acquisition frameworks and algorithm engineering for large scale combinatorial optimization
  • Novel sensors for nuclear phenomena (e.g. neutron emission)
  • Tool and techniques for supporting a manufacturing modeling culture

Rex Reklaitis

  • Application of real time sensing and digital twins to monitoring and multi-level control of batch and continuous processes
  • Condition-based monitoring and maintenance scheduling strategies employing AI/ML diagnosis methods and real time scheduling
  • Treatment of uncertainty in design space development and its utilization for risk management in operations

Shweta Singh

  • Material Flow Analysis and Life Cycle Analysis for Manufacturing Networks: Automation of Process to Network Scale
  • Design of Circular Economy in Manufacturing Networks
  • Dynamics of Material Flows in Manufacturing Networks using ML based surrogate models

Mohit Tawarmalani

  • Electrification, intensification, and sustainability enhancements for unit operations, particularly separations
  • Network design and operation via AI architectures aligned for data-driven decision making
  • Nonconvex optimization theory and algorithms