The Carnegie Mellon Process Systems Engineering (PSE) group represents one of the largest university research efforts for process systems engineering in the United States. Over the past four decades, the PSE group (Professors Biegler, Gounaris, Grossmann, Sahinidis, and Ydstie) has changed the global landscape of process systems engineering, providing intellectual leadership in complex decision-making issues faced by process industries, such as the petrochemical and emerging energy technology industries. Our underlying approach is based on developing and advancing systematic modeling and solution methods for multi-scale process systems engineering, covering the full spectrum from the molecular to the enterprise level.

The program has graduated over 150 Ph.D. students, many of whom have gone on to be leaders in their own right at companies and universities around the world. Faculty of the program authored the seminal text Systematic Methods of Chemical Process Design, which is used to teach countless students and researchers every year. Additionally, researchers have created many state-of-the-art optimization software programs, and many research strategies developed in the program have seen widespread adoption in departments in and outside the university.

Housed in the Chemical Engineering department’s state-of-the-art computational facilities, the PSE research group includes about 50 graduate students and 15 post-doctoral researchers and visitors, and is supported by funding in excess of $3 million per year. The PSE research group also hosts the Center for Advanced Process Decision-making (CAPD), an industrial consortium consisting of over 20 members from the chemical and petroleum industries, as well as a number of engineering and software companies.

The research work of the PSE group is focused in four major areas: 

  • Optimization – focuses on advances in large-scale nonlinear programming, mixed-integer and disjunctive programming, global optimization, differential-algebraic systems, stochastic programing, and data-driven models and analytics.
  • Design – involves applications in shale gas facilities, biofuel plants, carbon capture systems, fuel cells, solar cells and power systems, catalyst design, bioinformatics, and more.
  • Operations – includes topics in enterprise-wide optimization, supply chain management under uncertainty, planning of batch and continuous process systems, and smart grid optimization.
  • Control – addresses adaptive control and on-line parameter estimation, self-learning, distributed systems, thermodynamics, passivity theory, design and verification of process operating systems, and real-time data analysis.


Research topics include:

  • Synthesis of complex separation systems
  • Design of shale gas facilities and water management
  • Synthesis of biofuel plants
  • Optimal process water integration
  • Design of carbon capture systems
  • Design of fuel and solar cells, IGCC systems
  • Materials design of metal-oxide surfaces and nanoparticles
  • Scheduling and planning of process systems
  • Planning and optimization of oil and gas field facilities
  • Electric power planning optimization and demand side management
  • Enterprise-wide optimization and supply chain logistics
  • Optimization of inventory management
  • Thermodynamics-based process control
  • Optimization strategies for process control and parameter estimation
  • Adaptive control and on-line parameter estimation
  • Modeling, simulation and control of distributed systems
  • Methods and software for:
    • large-scale nonlinear programming
    • optimization of differential-algebraic systems
    • mixed-integer and disjunctive programming
    • global optimization of nonconvex optimization problems
  • Surrogate models for black box optimization models
  • Optimization under uncertainty: stochastic programming, robust optimization
  • Machine learning and reinforcement learning
  • Metabolic networks, bioinformatics
  • Design of molecules: refrigerants, drilling fluids
  • Design of materials: catalysts, molecular sieves, composites

Center for Advanced Process Decision-making

The Center for Advanced Process Decision-making (CAPD) provides an umbrella organization to give students the opportunity to interact with industry in the area of process systems engineering.