Applied Research Projects
ArtificialGate conducts applied AI research projects for organizations that need rigorous, practical solutions beyond off-the-shelf tools.
We can lead a project from zero, beginning with the initial idea, research question, technical feasibility, experimental design, and model architecture.
When a client already has data, we build the full path from data preparation and modeling to training, validation, and delivery of a trained model ready for a deployment environment.
Improving Requirements Classification
A machine-learning study using imbalance-aware preprocessing for requirements classification.
Read Paper 02 Sensor AITransformer Behavior Classification
A transformer encoder for accurate real-time classification from motion sensor data.
Read Paper 03 Runtime StabilityAutomatic Stability and Recovery
A runtime controller that detects destabilizing training updates and recovers by rollback.
Read Paper 04 Agentic ReliabilityMTTR-A Cognitive Recovery Latency
A reliability metric for measuring cognitive recovery latency in multi-agent AI systems.
Read Paper 05 RAG EvaluationQuantifying Prior Dominance in RAG
A framework for measuring whether RAG models use retrieved evidence or override it with priors.
Read Paper 06 Kalman FilteringSelection-Induced Innovation Contraction
How validation gating and nearest-neighbor association reshape innovation statistics in Kalman tracking.
Read Paper 07 PINN OptimizationThe Direction-Execution Gap
An optimizer-aware audit for detecting when locally favorable PINN updates deteriorate after complete finite-step execution.
Read Paper