Overview
What I study
I work on making computer systems — especially the embedded systems inside cars, aircraft, industrial equipment, and everyday appliances — safer, more reliable, and more trustworthy.
My research covers system software (real-time operating systems (RTOS), scheduling, resource management), verification and testing (including fuzzing and formal methods), safety and security analysis, and assurance frameworks. I collaborate closely with both academic researchers and industry engineers.
Overview
Why it matters now
Embedded systems used to operate largely on their own. Today, most are connected to networks, cloud services, and other systems around them.
Because of this change, it is no longer enough to study a single device on its own. We also need to understand the larger systems formed by many parts interacting with each other.
Overview
Current topics
Current topics include: orchestrating mixed-criticality services (running programs of different importance safely on the same on-board computer) for software-defined vehicles (SDVs — cars whose features are updated through software); privacy-preserving IoT access control using blockchain and zero-knowledge proofs (cryptography that proves a statement without revealing the underlying data); concurrency-aware fuzzing; and resilience engineering for Mobility-as-a-Service (MaaS — services that combine trains, buses, ride-sharing, and other transport options) using multi-agent reinforcement learning.
A shared goal across these topics is to support systems not only at design time, but throughout their operation and evolution.
Overview
Two complementary approaches
One approach focuses on a single embedded system and builds it carefully from components whose behavior is well understood. This lets us reason step by step about performance and quality.
The other approach looks at larger systems that include unknown or changing parts, and that interact with people and society. Here the goal is to keep the system in as good a state as possible and to explain its behavior, even when full understanding is out of reach.
