Problems in focus
Transform incomplete sensor observations into representations and decisions that remain useful under changing light, terrain, connectivity and operating conditions.
- Robust perception↗
- State estimation↗
- Supervised planning↗
01
DISCIPLINE
AI & Autonomy
Build perception, planning and spatial intelligence that can be tested against the complexity of the physical world.
STATUSOPEN INTRODUCTIONS
CONTEXTPERCEPTION / PLANNING / CONTROL
PRINCIPLEEVIDENCE-DRIVEN WORK
THE OPERATING IDEA
Intelligence is useful only when its limits are understood.
FOCUS AREAS
01Computer vision
02Sensor fusion
03Spatial intelligence
04Local planning
05Uncertainty
06Evaluation
Engineering standard
Models are part of systems. Work includes data, evaluation, deployment constraints, failure analysis and interfaces that expose confidence to operators.
- Evidence-driven evaluation↗
- Edge constraints↗
- Interpretable system state↗
Signals we value
Strong foundations, experimental discipline and the ability to connect algorithms to measurable physical-world behavior matter more than fashionable terminology.
- Technical depth↗
- Clear reasoning↗
- System-level judgment↗