Unlocking the secrets of high-performance in distributed systems
My research seeks answer to the question: How can we combine known invariants with real-world data to guarantee the best performance of physical systems? My focus is on dynamical systems where behaviors emerge from vast networks of interacting objects spread across different locations. These behaviors are driven by partial integro-differential equations equations that are tough to solve, and observing them is often limited by budget constraints on sensors and their placements.
To tackle these challenges, I develop powerful computational tools grounded on optimization, control theory, and machine learning.
Our research has exciting applications in:
- High-tech systems
- Neuro-engineering
- Smart mobility
- Nuclear fusion
