Perception-Driven ML: How to develop benchmarks for camera- and LIDAR-related perception?

Embedded Cybersecurity for Edge AI and Autonomous Vehicles: How can embedded edge AI in autonomous vehicles be secured against real-time, evolving cyberattacks within resource constraints?

Next-Generation Radar: How to include intelligent radars into AV sensor suits?

Camera Technology & Computer Vision Algorithms: How to turn cameras into primary sensors for object recognition and classification, localization, decision-making, trajectory planning, and vehicle control?

Open/Modular Verification & Validation: How to manage rapidly changing test requirements?

Sensor Fusion: How to properly weigh sensors at run-time?

Perception Stress Testing: How to automatically identify where perception is brittle using unlabelled data?

Vision Geometry & Deep Neural Networks: How to verify deep learning detection with vision geometric principles?

Reinforcement Learning for Vehicular Path Planning: How to make use of deep learning for AVs?

Full Stack Software Suites for AI: How to develop hardware-agnostic and scalable solutions?

Self-Supervised Learning for AVs: How to collect and label data at scale?

Data Processing & AI: How to develop software architectures and overcome hardware challenges?

Interpretable Learning for AVs: How to use visual explanations that causally influence CNN output?

Sensor Selection, Design & Innovation: Which are the latest technologies?

Weather & Vision Environments: How to ensure safety in unfamiliar and challenging weather environments?

The Software-Defined Car: What is the role of SDV in ADAS?