Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
In this project, different optimal control problems will be considered under a contagious financial and insurance market with regime switching and risk uncertainty. In the first chapter, an optimal
-
. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
-
and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some
-
The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
-
dynamically managing power flow, improving system flexibility, and mitigating transmission constraints. However, conventional methods for PST deployment often consider sizing, placement, and control in
-
techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
-
, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific
-
supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
-
engines. The variable rotation speeds, complex loading and operating conditions cause significant blade vibrations. These vibrations, if not properly controlled and reduced, can lead to premature blade
-
its environment and respond optimally in dynamic operating conditions. Meanwhile, you will also develop intelligent control strategies that minimise energy use while ensuring punctuality and safety