Research Topics

Systems Support for Intelligent Applications


This topic focuses on addressing timeliness, efficiency, and robustness challenges raised by emerging real-time intelligent and autonomous applications such as self-driving cars and robots. For instance, we develop new scheduling algorithms and runtime mechanisms that leverage application-level end-to-end requirements of autonomous systems, and software frameworks that support the concurrent execution of multiple DNN tasks with deterministic timing and dependability guarantees on heterogeneous hardware platforms.

Predictable Parallel Systems


In this topic, we aim to build predictable systems that can take advantage of modern parallel hardware platforms (e.g., multi-core CPUs and GPUs), which are imperative to the efficiency and usability of mission-critical applications such as avionics and automotive systems. In particular, our focus has been on enabling predictable systems from unpredictable commercial off-the-shelf hardware components as doing so greatly reduces development cost and allows for timely and wide acceptance of new technology.

Smart Sensing and Processing in Dynamic Environment


For robust and continuous operation of Cyber-Physical Systems (CPS) and the Internet of Things (IoT), a system must be able to deal with uncertainties under various environmental conditions. We have particularly focused on: (i) dynamically changing computing capacity due to extreme thermal conditions, (ii) fail-robust execution environment and uncertainty mitigation techniques, and (iii) continuous and reliable operation on batteryless, intermittently-powered devices.

Project Websites


Sponsors

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