Each research area advances along its own trajectory. DeepCausality is the most mature: a published axiomatic foundation, a working implementation, and a growing catalog of cross-domain examples. Chronodynamics has produced a first concrete empirical result and is now expanding further. Deep Brain is in the architectural-design stage and will move to implementation once the foundational layers are stable.
DeepCausality
- Submission of the EPP monograph to a refereed open-access venue, following community feedback on the current preprint.
- Continued expansion of the cross-domain example catalog, with new pipelines in chronometric geodesy, materials science, and relativistic physics.
- Expansion of the causal-discovery pipeline (SURD and MRMR) on open scientific datasets, end-to-end from data to executable Causaloid.
Chronodynamics
- Extension of the inversion to additional gauges, beginning with the J2 oblateness correction and the kinetic gauge.
- Application of the chronometric-inversion method to additional satellite systems beyond the Galileo constellation.
- Investigation of pulsar timing data as a chronometric source for gravitational measurement at galactic scale.
Deep Brain
- Completion of the foundation layer: schema, embedding pipeline, named-entity recognition, and rule-based classification.
- Implementation of the three coordinated hypergraphs (content, context, and the relations between them) with coordinated freeze/unfreeze cycles.
- Publication of the Knowledge Propagation Process as the foundational paper of dynamic knowledge.