Aerlix Labs / AI / Research interest
Human-Machine Teaming
How can automation reduce workload without hiding uncertainty?
SYSTEM ARCHITECTURE / COMMAND
Sensing → networking → compute → intelligence → human decision
Interactive model loads as you approach. The engineering scope and constraints are provided in the page text.
Research question
How can automation reduce workload without hiding uncertainty?
Approach to investigation
Explore mixed-initiative systems, explainable recommendations, adaptive interfaces, human authorization and supervisory autonomy through task-based evaluation.
Begin with a reproducible model and define the evidence that would challenge the hypothesis. Compare alternatives under both nominal and degraded conditions. Preserve assumptions, versioned inputs and observed failures.
Maturity & boundaries
Interface hypotheses need operator research before claims about workload reduction.
Potential collaboration can establish a scoped experiment, evaluation criteria and an integration decision. No completion date, funding source or deployment status is implied.
Define the mission
Bring the hard problem.
Start with the operating environment, the constraints and the decision your system needs to support.