معرفی
Carl D. Laird is the John E. Swearingen Professor and Department Head of Chemical Engineering at Carnegie Mellon University's College of Engineering. He holds affiliations with the Center for Advanced Process Decision-making (CAPD) and the Center for Materials Data Science for Reliability and Degradation (MDS-Rely). His academic journey includes a B.S. from the University of Alberta (2000), a Ph.D. from Carnegie Mellon (2006), and postdoctoral training in Epidemiology at the University of Pittsburgh.
Laird's research integrates optimization, data science, and systems engineering. Key focus areas include high-performance computing for large-scale nonlinear problems, parallel scientific computing, and open-source software development, applied to domains like public health, homeland security, critical infrastructure, and energy systems. His work also spans machine learning, operations research, and advanced process decision-making.
Awards and Honors:
- 2024 Steven J. Fenves Award for Systems Research
- INFORMS Computing Society Prize
- Wilkinson Prize for Numerical Software (for IPOPT development)
- NSF CAREER Award
- Best Oral Presentation at ESCAPE 33
- John E. Swearingen Endowed Professorship
He advises graduate students including Carolina Colombo Tedesco and leads the Laird Research Group, part of the Center for Advanced Process Decision Making (CAPD). His collaborations include projects with Imperial College and Sandia National Labs, such as the OMLT Python package for machine learning optimization.
