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Research Areas
Systems Science
Systems engineers design, develop, manage and optimize complex systems including:
- electrical systems
- information systems
- biological systems
- quantum systems
- economic models
- financial systems
- environmental systems
- telecommunication networks
- transportation networks
- project management
- aerospace systems
Systems engineering is the field of specialization within engineering that uses advanced mathematical methods to model physical systems, and to develop techniques for system optimization and control. Systems engineers are experts at analyzing complex systems and effectively coordinating their many different components.
Meet the Faculty
Xudong Chen
Develops revolutionary methods for analysis and control of large-scale multi-agent systems
ShiNung Ching
Lead author of a textbook, Quasilinear Control
Andrew Clark
Focused on control and security of networked and cyberphysical systems
Ioannis (Yiannis) Kantaros
Designs safe and distributed autonomy algorithms for large-scale multi-robot systems
Jr-Shin Li
Studies complex large-scale systems arising from emerging physical, biological and medical applications
Bruno Sinopoli
Designs safe and secure networked embedded control systems
Shen Zeng
Develops data-integrated computational approaches for controlling complex dynamic systems
Affiliate Faculty
Christopher Gill
Develops novel system software architectures, policies and mechanisms for advanced Real Time, embedded and cyberphysical systems
Geoffrey Goodhill
Strives to understand computational principles that underly brain development
Ilya Monosov
Interested in the neuronal basis of voluntary behavior
Gaia Tavoni
Develops theories and models to understand how information is represented and processed in neuronal networks
Yevgeniy (Eugene) Vorobeychik
Uses techniques from game theory and optimization to create trustworthy AI systems
ShiNung Ching Lab - Electrical & Systems Engineering
The Lab of ShiNung Ching is at the intersection of engineering, science, and medicine with applications of mathematical and engineering principles to unravel the complexities of the human brain. In collaboration with the Washington University School of Medicine, the group analyzes EEGs from pediatric patients, aiming to understand brain dynamics and develop a pattern-detection pipeline for improved interventions. Their focus extends to investigating how early sensory networks process peripheral stimuli information for higher-level brain functions, emphasizing formal mathematical descriptions and training recurrent neural networks to comprehend cognitive tasks and reverse engineer their performance for deeper insights into brain computation.
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