Carl Laird

Carl D. Laird is the John E. Swearingen Professor and Department Head of Chemical Engineering at Carnegie Mellon University. He leads an internationally recognized research program in process systems engineering, known for high-performance computing techniques in large-scale nonlinear optimization, parallel scientific computing, and open-source software development.

Education:

• Ph.D. in Chemical Engineering, Carnegie Mellon University (2006)
• B.S. in Chemical Engineering, University of Alberta (2000)

Research Focus: His work solves problems in non-traditional domains including public health, homeland security, critical infrastructure, and energy systems through advanced optimization methodologies. Current research integrates machine learning with optimization for improved decision-making in complex systems.

Publication Trends: Recent work focuses on mathematical optimization frameworks, decomposition methods for large-scale problems, integration of machine learning surrogates, and applications in energy systems and chemical manufacturing. Research demonstrates consistent innovation in computational methods for engineering challenges.

Awards and Honors:

• Steven J. Fenves Award for Systems Research
• INFORMS Computing Society Prize
• CAST Division Outstanding Young Researcher Award
• NSF CAREER Award
• Montague Center Teaching Excellence Award
• Wilkinson Prize for Numerical Software (for IPOPT development)

Leadership and Funding: As director of the Center for Advanced Process Decision-Making, he oversees collaborative research with industry partners. His research has been supported by NSF, DOE, and industrial consortia.