Nikolaos Diaggelakis

Nikolaos Diaggelakis serves as an Assistant Professor in the Department of Process Development, Analysis & Design (II) at the School of Chemical Engineering, Technical University of Crete, where his work bridges theoretical optimization and industrial process applications.

Education:

• Ph.D. in Chemical Engineering, Imperial College London, 2017
• M.Sc. in Chemical Engineering, Imperial College London, 2012
• Diploma in Chemical Engineering, National Technical University of Athens, 2011
• Visiting Doctoral Researcher, Texas A&M Energy Institute, 2017

His research pioneers process systems engineering through mathematical optimization with moving time horizons, simultaneous design-control integration, and multi-parametric programming frameworks. Key applications span chemical process intensification, energy-efficient microgrids, and environmental systems, emphasizing worst-case and nonlinear optimization robustness. His theoretical contributions directly enable industrial implementations in energy systems and manufacturing.

Publications from 2015-2022 reveal a concentrated evolution toward real-time optimization and decentralized control architectures, with increasing focus on data-driven surrogate models and robust explicit MPC strategies. The work consistently bridges fundamental algorithm development (e.g., multi-parametric quadratic programming solutions) with tangible industrial applications like air separation units and combined heat-power systems.

Scientific Awards:

• Excellence Award for Outstanding PhD Thesis in Computer Aided Process Engineering (CAPE), Third Place, 2017
• Invited Speaker, Distinguished Young Researchers Seminar Series, Northwestern University, 2016
• Best Poster Award, CPSE Autumn Industrial Consortium Meeting, Imperial College London, 2014

Dr. Diaggelakis actively secures competitive funding, including U.S. Department of Energy grants (2018-2020) for smart manufacturing in chemical processing and National Science Foundation projects (2015-2016) on integrated process design-control frameworks. His leadership in the PAROC research group drives software development (POP toolbox) and industry collaborations through consortia like CPSE. Current projects emphasize uncertainty-aware scheduling for process industries and energy-efficient microgrid operation.

He co-develops the industry-standard PAROC framework and POP toolbox, enabling multi-parametric optimization for complex process systems, and maintains active partnerships with Texas A&M and Imperial College London through ongoing research consortia.